GeoServer Web Map Tile Service A compliant implementation of WMTS service. OGC WMTS 1.0.0 NONE NONE http://geoserver.org/com Andrea de Bono Data officer Chemin des Anemones 11 Chatelaine 1219 Switzerland debono@unepgrid.ch KVP KVP KVP eth_natural_hazards_exposure 33.0000777214893 3.4041562230000286 47.701938752897306 14.894164106000062 mapx_chemobs:eth_natural_hazards_exposure image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 5 EPSG:3857:4 7 7 9 10 EPSG:3857:5 14 15 18 20 EPSG:3857:6 29 31 37 40 EPSG:3857:7 58 62 75 80 EPSG:3857:8 117 125 151 161 EPSG:3857:9 234 251 302 323 EPSG:3857:10 469 502 605 647 EPSG:3857:11 938 1004 1211 1295 EPSG:3857:12 1876 2009 2423 2590 EPSG:3857:13 3753 4018 4846 5181 EPSG:3857:14 7506 8036 9693 10362 EPSG:3857:15 15012 16073 19387 20725 EPSG:3857:16 30025 32147 38775 41451 EPSG:3857:17 60051 64295 77550 82903 EPSG:3857:18 120102 128591 155101 165807 EPSG:3857:19 240204 257183 310203 331614 EPSG:3857:20 480408 514366 620407 663229 EPSG:3857:21 960817 1028733 1240815 1326459 EPSG:3857:22 1921634 2057467 2481630 2652919 EPSG:3857:23 3843268 4114934 4963261 5305839 EPSG:3857:24 7686537 8229869 9926523 10611679 EPSG:3857:25 15373074 16459738 19853046 21223358 EPSG:3857:26 30746149 32919477 39706092 42446717 EPSG:3857:27 61492299 65838955 79412184 84893435 EPSG:3857:28 122984598 131677910 158824369 169786871 EPSG:3857:29 245969196 263355820 317648738 339573743 EPSG:3857:30 491938393 526711641 635297477 679147486 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 5 EPSG:4326:3 3 3 9 10 EPSG:4326:4 6 7 18 20 EPSG:4326:5 13 15 37 40 EPSG:4326:6 26 30 75 80 EPSG:4326:7 53 61 151 161 EPSG:4326:8 106 123 302 323 EPSG:4326:9 213 246 605 647 EPSG:4326:10 427 492 1211 1295 EPSG:4326:11 854 985 2423 2590 EPSG:4326:12 1709 1970 4846 5181 EPSG:4326:13 3418 3941 9693 10362 EPSG:4326:14 6836 7882 19387 20725 EPSG:4326:15 13672 15764 38775 41451 EPSG:4326:16 27345 31528 77550 82903 EPSG:4326:17 54690 63057 155101 165807 EPSG:4326:18 109380 126114 310203 331614 EPSG:4326:19 218761 252228 620407 663229 EPSG:4326:20 437523 504457 1240815 1326459 EPSG:4326:21 875046 1008914 2481630 2652919 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 5 EPSG:3857:4 7 7 9 10 EPSG:3857:5 14 15 18 20 EPSG:3857:6 29 31 37 40 EPSG:3857:7 58 62 75 80 EPSG:3857:8 117 125 151 161 EPSG:3857:9 234 251 302 323 EPSG:3857:10 469 502 605 647 EPSG:3857:11 938 1004 1211 1295 EPSG:3857:12 1876 2009 2423 2590 EPSG:3857:13 3753 4018 4846 5181 EPSG:3857:14 7506 8036 9693 10362 EPSG:3857:15 15012 16073 19387 20725 EPSG:3857:16 30025 32147 38775 41451 EPSG:3857:17 60051 64295 77550 82903 EPSG:3857:18 120102 128591 155101 165807 EPSG:3857:19 240204 257183 310203 331614 EPSG:3857:20 480408 514366 620407 663229 EPSG:3857:21 960817 1028733 1240815 1326459 EPSG:3857:22 1921634 2057467 2481630 2652919 EPSG:3857:23 3843268 4114934 4963261 5305839 EPSG:3857:24 7686537 8229869 9926523 10611679 EPSG:3857:25 15373074 16459738 19853046 21223358 EPSG:3857:26 30746149 32919477 39706092 42446717 EPSG:3857:27 61492299 65838955 79412184 84893435 EPSG:3857:28 122984598 131677910 158824369 169786871 EPSG:3857:29 245969196 263355820 317648738 339573743 EPSG:3857:30 491938393 526711641 635297477 679147486 Combination Flood/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_flo_for6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 20181230Classes Classification of a Sentinel-2 image with post-processing using field knowledge. This research was funded by the Copernicus RawMatCop programme, through funding from EIT RawMaterials and the European Commission DG Internal Market, Industry, Entrepreneurship and SMEs (DG GROW). https://eitrawmaterials.eu/eit-rm-academy/rawmatcop/, in the scope of project CopX: "Geospatial mining transparency through Copernicus and MapX" -74.86103149540197 7.565680150087606 -74.77551708391071 7.624603274629289 UNILIEGE:20181230Classes image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125503 125546 76559 76622 EPSG:3857:19 251006 251093 153119 153244 EPSG:3857:20 502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 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502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 morocco_remote_site_screening_res50 -13.168084726852316 27.664466294000036 -0.9980847268523156 35.921466294000034 mapx_chemobs:morocco_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 6 6 7 7 EPSG:3857:5 12 13 14 15 EPSG:3857:6 25 26 29 31 EPSG:3857:7 50 53 59 63 EPSG:3857:8 100 107 118 127 EPSG:3857:9 201 215 237 254 EPSG:3857:10 402 430 474 509 EPSG:3857:11 804 860 949 1018 EPSG:3857:12 1609 1720 1898 2036 EPSG:3857:13 3219 3440 3796 4073 EPSG:3857:14 6438 6880 7592 8146 EPSG:3857:15 12876 13761 15185 16293 EPSG:3857:16 25752 27523 30370 32586 EPSG:3857:17 51505 55047 60741 65172 EPSG:3857:18 103010 110095 121483 130345 EPSG:3857:19 206021 220191 242966 260690 EPSG:3857:20 412043 440382 485933 521380 EPSG:3857:21 824086 880765 971866 1042761 EPSG:3857:22 1648173 1761530 1943732 2085523 EPSG:3857:23 3296347 3523061 3887465 4171046 EPSG:3857:24 6592694 7046123 7774930 8342093 EPSG:3857:25 13185389 14092246 15549861 16684187 EPSG:3857:26 26370779 28184492 31099723 33368375 EPSG:3857:27 52741559 56368984 62199446 66736751 EPSG:3857:28 105483118 112737969 124398892 133473502 EPSG:3857:29 210966236 225475938 248797784 266947004 EPSG:3857:30 421932473 450951877 497595569 533894008 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 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3796 4073 EPSG:3857:14 6438 6880 7592 8146 EPSG:3857:15 12876 13761 15185 16293 EPSG:3857:16 25752 27523 30370 32586 EPSG:3857:17 51505 55047 60741 65172 EPSG:3857:18 103010 110095 121483 130345 EPSG:3857:19 206021 220191 242966 260690 EPSG:3857:20 412043 440382 485933 521380 EPSG:3857:21 824086 880765 971866 1042761 EPSG:3857:22 1648173 1761530 1943732 2085523 EPSG:3857:23 3296347 3523061 3887465 4171046 EPSG:3857:24 6592694 7046123 7774930 8342093 EPSG:3857:25 13185389 14092246 15549861 16684187 EPSG:3857:26 26370779 28184492 31099723 33368375 EPSG:3857:27 52741559 56368984 62199446 66736751 EPSG:3857:28 105483118 112737969 124398892 133473502 EPSG:3857:29 210966236 225475938 248797784 266947004 EPSG:3857:30 421932473 450951877 497595569 533894008 v432_CO2_excl_C_2012_opt_deflate -180.0 -77.95 179.95 88.15000000000002 wesr_climat:v432_CO2_excl_C_2012_opt_deflate image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 0 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 -1 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 0 115142440 0 134199086 EPSG:3857:28 -1 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 0 921139526 0 1073592693 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 -1 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 0 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 -1 115142440 0 134199086 EPSG:3857:28 0 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 -1 921139526 0 1073592693 Year precipitations 2017 - Central African Republic Total precipitations observed in 2017 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2017_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Kerala Flood 500 Years RP - RCP85 Kerala State flood hazard map - RCP 8.5 scenario. Maximum expected flood event water height in a 500 years return period, expressed in cm. 74.85958333333333 8.25375 77.49208333333334 12.842916666666673 ECO-DRR:Kerala_Flood_500_Yrs_RCP85 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185583 187500 EPSG:4326:18 112368 119051 371166 375000 EPSG:4326:19 224736 238103 742332 750000 EPSG:4326:20 449472 476206 1484664 1500000 EPSG:4326:21 898945 952412 2969329 3000000 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 2021-2022 Average year temperature change since previous decade (2011-2020) Average year temperature anomalies in °C across the period 2021-2022 calculated over the average temperature per year in the period 2011-2020. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_21_22_anom_11_20 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 col_forint100 The forest integrrity index is derived by overlaying the human footprint (Venter et al. 2016) on the forest structural condition. The name is consistent with the concept of ecological integrity. Ecological integrity has been defined as, “the system’s capacity to maintain structure and ecosystem functions using processes and elements characteristic for its ecoregion.” (Parks Canada 2008). This capacity is a result of the climate, soil, topography, biota and other biophysical properties of the ecoregion and the extent to which these properties are not altered by modern human pressures. Consistent with this definition, the forest integrity index is based on on the structural complexity of a stand relative to the natural potential of the ecoregion and level of human pressure. Thus, forest of high integrity are relatively tall, high in canopy cover, older, and with relatively low human pressure. An increasing number of studies have shown that human pressure in various forms can have negative effects on native species. Thus, high integrity forests may be uniquely important for conservation because they support species and processes that are require well-developed forests and are sensitive to human activities. Such forests often also have high economic value and have likely been preferentially converted to more intense human land uses. Thus, identifying remaining areas of high forest integrity is important for conservation planning.<br><br>Data is provided by Montana State University.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> -79.758379943848 -4.470114545847 -66.21837994384799 11.205885454153 wesr_biodiversity:col_forint100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 5 EPSG:3857:5 14 16 8 10 EPSG:3857:6 29 32 17 20 EPSG:3857:7 59 65 35 40 EPSG:3857:8 119 131 71 80 EPSG:3857:9 239 262 142 161 EPSG:3857:10 479 524 285 323 EPSG:3857:11 959 1049 570 647 EPSG:3857:12 1919 2098 1140 1294 EPSG:3857:13 3839 4197 2281 2589 EPSG:3857:14 7678 8395 4562 5178 EPSG:3857:15 15357 16791 9124 10356 EPSG:3857:16 30714 33582 18248 20713 EPSG:3857:17 61429 67165 36496 41426 EPSG:3857:18 122859 134330 72993 82853 EPSG:3857:19 245719 268660 145987 165706 EPSG:3857:20 491438 537321 291974 331412 EPSG:3857:21 982876 1074642 583949 662825 EPSG:3857:22 1965753 2149285 1167899 1325651 EPSG:3857:23 3931507 4298571 2335799 2651303 EPSG:3857:24 7863014 8597142 4671598 5302607 EPSG:3857:25 15726028 17194284 9343196 10605215 EPSG:3857:26 31452057 34388568 18686392 21210431 EPSG:3857:27 62904114 68777136 37372784 42420862 EPSG:3857:28 125808229 137554273 74745569 84841725 EPSG:3857:29 251616458 275108547 149491138 169683450 EPSG:3857:30 503232917 550217094 298982277 339366900 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 1 1 1 EPSG:4326:2 1 2 2 2 EPSG:4326:3 3 4 4 5 EPSG:4326:4 7 8 8 10 EPSG:4326:5 14 16 17 20 EPSG:4326:6 28 33 35 40 EPSG:4326:7 56 67 71 80 EPSG:4326:8 112 134 142 161 EPSG:4326:9 224 268 285 323 EPSG:4326:10 448 537 570 647 EPSG:4326:11 896 1074 1140 1294 EPSG:4326:12 1793 2149 2281 2589 EPSG:4326:13 3586 4299 4562 5178 EPSG:4326:14 7172 8598 9124 10356 EPSG:4326:15 14344 17197 18248 20713 EPSG:4326:16 28688 34395 36496 41426 EPSG:4326:17 57376 68791 72993 82853 EPSG:4326:18 114752 137582 145987 165706 EPSG:4326:19 229504 275164 291974 331412 EPSG:4326:20 459008 550328 583949 662825 EPSG:4326:21 918017 1100656 1167899 1325651 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 5 EPSG:3857:5 14 16 8 10 EPSG:3857:6 29 32 17 20 EPSG:3857:7 59 65 35 40 EPSG:3857:8 119 131 71 80 EPSG:3857:9 239 262 142 161 EPSG:3857:10 479 524 285 323 EPSG:3857:11 959 1049 570 647 EPSG:3857:12 1919 2098 1140 1294 EPSG:3857:13 3839 4197 2281 2589 EPSG:3857:14 7678 8395 4562 5178 EPSG:3857:15 15357 16791 9124 10356 EPSG:3857:16 30714 33582 18248 20713 EPSG:3857:17 61429 67165 36496 41426 EPSG:3857:18 122859 134330 72993 82853 EPSG:3857:19 245719 268660 145987 165706 EPSG:3857:20 491438 537321 291974 331412 EPSG:3857:21 982876 1074642 583949 662825 EPSG:3857:22 1965753 2149285 1167899 1325651 EPSG:3857:23 3931507 4298571 2335799 2651303 EPSG:3857:24 7863014 8597142 4671598 5302607 EPSG:3857:25 15726028 17194284 9343196 10605215 EPSG:3857:26 31452057 34388568 18686392 21210431 EPSG:3857:27 62904114 68777136 37372784 42420862 EPSG:3857:28 125808229 137554273 74745569 84841725 EPSG:3857:29 251616458 275108547 149491138 169683450 EPSG:3857:30 503232917 550217094 298982277 339366900 Kerala Flood 200 Years RP - RCP85 Kerala State flood hazard map - RCP 8.5 scenario. Maximum expected flood event water height in a 200 years return period, expressed in cm. 74.85958333333333 8.25375 77.49208333333334 12.842916666666673 ECO-DRR:Kerala_Flood_200_Yrs_RCP85 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185583 187500 EPSG:4326:18 112368 119051 371166 375000 EPSG:4326:19 224736 238103 742332 750000 EPSG:4326:20 449472 476206 1484664 1500000 EPSG:4326:21 898945 952412 2969329 3000000 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 Flooded areas in Kedougou between 2005 and 2014 Flood zone mapping is based on the analysis of Landsat satellite images (series 5, 7 and 8) covering the three decadal periods of the study (1995-2024). These data, available on GEE, offer spectral bands suitable for water detection. The green and short-wave infrared spectral bands were selected to calculate the Modified Normalized Difference Water Index (MNDWI), while the red and near-infrared (NIR) bands were used in the case of another hazard to calculate the NDVI to eliminate false detections linked to vegetation. -13.243723483393213 12.296539942972935 -11.335952171241116 13.472448719878967 risk_southeast_senegal:flood_2005_2014 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60584 61024 60714 61408 EPSG:3857:18 121169 122048 121428 122817 EPSG:3857:19 242339 244096 242856 245634 EPSG:3857:20 484679 488193 485712 491269 EPSG:3857:21 969359 976387 971425 982539 EPSG:3857:22 1938719 1952774 1942851 1965078 EPSG:3857:23 3877439 3905548 3885702 3930157 EPSG:3857:24 7754879 7811097 7771405 7860314 EPSG:3857:25 15509758 15622194 15542811 15720628 EPSG:3857:26 31019517 31244388 31085623 31441257 EPSG:3857:27 62039034 62488777 62171246 62882514 EPSG:3857:28 124078069 124977555 124342492 125765029 EPSG:3857:29 248156138 249955110 248684984 251530058 EPSG:3857:30 496312277 499910220 497369968 503060117 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 221 474 479 EPSG:4326:10 435 442 948 959 EPSG:4326:11 870 884 1897 1919 EPSG:4326:12 1741 1768 3794 3838 EPSG:4326:13 3482 3536 7589 7676 EPSG:4326:14 6965 7072 15178 15352 EPSG:4326:15 13931 14145 30357 30704 EPSG:4326:16 27862 28290 60714 61408 EPSG:4326:17 55725 56581 121428 122817 EPSG:4326:18 111451 113163 242856 245634 EPSG:4326:19 222902 226327 485712 491269 EPSG:4326:20 445805 452655 971425 982539 EPSG:4326:21 891610 905310 1942851 1965078 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60584 61024 60714 61408 EPSG:3857:18 121169 122048 121428 122817 EPSG:3857:19 242339 244096 242856 245634 EPSG:3857:20 484679 488193 485712 491269 EPSG:3857:21 969359 976387 971425 982539 EPSG:3857:22 1938719 1952774 1942851 1965078 EPSG:3857:23 3877439 3905548 3885702 3930157 EPSG:3857:24 7754879 7811097 7771405 7860314 EPSG:3857:25 15509758 15622194 15542811 15720628 EPSG:3857:26 31019517 31244388 31085623 31441257 EPSG:3857:27 62039034 62488777 62171246 62882514 EPSG:3857:28 124078069 124977555 124342492 125765029 EPSG:3857:29 248156138 249955110 248684984 251530058 EPSG:3857:30 496312277 499910220 497369968 503060117 Combination Tropical cyclone surge/ Mangroves at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_man6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 South America Forest Height (Montana State University) -117.0005 -32.0005 -33.9995 32.0005 MapX_UNDP:samerica_forheight image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 0 1 EPSG:3857:3 3 4 1 3 EPSG:3857:4 6 9 2 6 EPSG:3857:5 12 19 5 12 EPSG:3857:6 25 38 11 25 EPSG:3857:7 51 76 22 51 EPSG:3857:8 103 152 44 103 EPSG:3857:9 207 304 89 207 EPSG:3857:10 415 608 179 415 EPSG:3857:11 831 1216 358 830 EPSG:3857:12 1663 2432 716 1661 EPSG:3857:13 3326 4865 1433 3322 EPSG:3857:14 6653 9730 2867 6644 EPSG:3857:15 13306 19461 5734 13289 EPSG:3857:16 26613 38922 11468 26578 EPSG:3857:17 53227 77844 22937 53157 EPSG:3857:18 106454 155689 45874 106314 EPSG:3857:19 212909 311378 91749 212628 EPSG:3857:20 425818 622757 183499 425257 EPSG:3857:21 851636 1245515 366998 850514 EPSG:3857:22 1703272 2491031 733997 1701029 EPSG:3857:23 3406544 4982063 1467994 3402058 EPSG:3857:24 6813088 9964127 2935989 6804116 EPSG:3857:25 13626176 19928255 5871978 13608232 EPSG:3857:26 27252353 39856510 11743957 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23487915 54432931 EPSG:3857:28 109009413 159426042 46975831 108865863 EPSG:3857:29 218018827 318852084 93951663 217731726 EPSG:3857:30 436037654 637704169 187903327 435463453 mosaic_2020_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:mosaic_2020_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 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EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Difference in projected timing of annual severe bleaching between SSP5-8.5 and SSP2-4.5 The data and complementary report have two purposes, and are intended for use by the global coral reef scientific and management community, which had these 2 objectives. Objective 1. To present projections of coral bleaching conditions (i.e., exposure to the primary climate threat to coral reefs) and potential adaptation at a spatial scale that enables use of the data in management and conservation planning and in support of other decisions influencing coral reefs and reef use. Objective 2. To evaluate the implications of the Paris Agreement as well as failure to achieve its goal, by comparing the projected timing of annual severe bleaching between Shared Socioeconomic Pathways SSP5-8.5 and SSP2-4.5. Data source used: Intergovernmental Panel on Climate Change (IPCC) Coupled Model Interpolation Project Phase 6 (CMIP6) model outputs for sea surface temperature (https://www.ipcc-data.org/), combined with United States National Oceanic and Atmospheric Administration (NOAA) CoralTemp data from NOAA Coral Reef Watch (https://www.coralreefwatch.noaa.gov/product/5km/index_5km_sst.php). -180.0 -90.0 180.0 90.0 wesr_climat:diff_ssp245_ssp585 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Evapotranspiration Autumn 2020 (USGS) The original data is from the USGS FEWS Data Downloads (https://earlywarning.usgs.gov/fews/datadownloads/Global/PET). The present raster in the average monthly evapotranspiration for autumn 2020. It in the average of the various evapotranspiration files available in autumn 2020 (September 2020, October 2020 and November 2020). On vegetated landscapes, Evapotranspiration (ET) can be simplified as the combination of evaporation from soil and transpiration from vegetation. Actual ET (ETa) is produced using the Operational Simplified Surface Energy Balance (SSEBop) model (Senay et al., 2013) for 2003 to present using data stream from the Aqua satellite. The SSEBop setup is based on the original Simplified Surface Energy Balance (SSEB) approach (Senay et al., 2007, 2011) with unique and improved parameterizations for operational applications. It combines ET fractions generated from remotely sensed MODIS thermal imagery, summarized every 10 days (dekadal), with reference ET, generated from weather data fields using the Penman-Monteith Equation. The unique feature of the SSEBop parameterization is that it uses a pre-defined, seasonally dynamic surface psychrometer constant parameter that helps define the hot/dry and cold/wet reference limits, unique to each pixel. Furthermore, the cold/wet limit is determined using the daily maximum air temperature (Ta) using the c factor parameter which relates Ta to land surface temperature at well-vegetated/well-watered surfaces. The original SSEB model was formulated based on an adaptation of the hot and cold pixel principles of SEBAL (Bastiaanssen et al., 1998) and METRIC (Allen et al., 2007) models. NoData pixels are indicated as NoDATA in ArcGIS. However, other software (e.g., ERDAS imagine) show nodata as -32768.00. ETa data and anomaly products (current vs. 2003 &#8211; 2015 median), produced at 1 km resolution, are available at: https://earlywarning.usgs.gov/fews. -180.0 -60.00000000570601 180.0 80.002258848399 wesr_mountains:m202009-11_automne_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1838 11626 0 16383 EPSG:3857:15 3677 23252 0 32767 EPSG:3857:16 7354 46504 0 65535 EPSG:3857:17 14709 93008 0 131071 EPSG:3857:18 29418 186017 0 262143 EPSG:3857:19 58837 372034 0 524287 EPSG:3857:20 117674 744069 0 1048575 EPSG:3857:21 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EPSG:3857:30 120498807 761927583 0 1073741824 malawi_remote_site_screening_res50 32.67395 -17.130540000000007 35.93195 -9.367540000000007 mapx_chemobs:malawi_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 17 18 19 EPSG:3857:6 33 35 37 38 EPSG:3857:7 67 70 75 76 EPSG:3857:8 134 140 151 153 EPSG:3857:9 269 280 302 307 EPSG:3857:10 538 561 604 614 EPSG:3857:11 1077 1122 1209 1228 EPSG:3857:12 2155 2245 2419 2456 EPSG:3857:13 4310 4491 4839 4913 EPSG:3857:14 8620 8983 9679 9827 EPSG:3857:15 17240 17967 19358 19654 EPSG:3857:16 34480 35934 38716 39309 EPSG:3857:17 68961 71868 77432 78618 EPSG:3857:18 137923 143736 154864 157236 EPSG:3857:19 275847 287472 309728 314473 EPSG:3857:20 551695 574944 619457 628947 EPSG:3857:21 1103390 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17654250 18398232 19822648 20126316 EPSG:3857:26 35308500 36796464 39645297 40252632 EPSG:3857:27 70617000 73592928 79290595 80505265 EPSG:3857:28 141234000 147185857 158581190 161010531 EPSG:3857:29 282468000 294371715 317162381 322021063 EPSG:3857:30 564936000 588743430 634324763 644042127 Land Cover Source: ESA (European Space Agency), retrieved <a href="http://due.esrin.esa.int/page_globcover.php" target="_blank"> here </a> <br><br> Most of the country is covered with natural and semi-natural vegetation with variable tree density. Vegetation cover is mostly high in the southwest, with thick tropical forests in the Greater Equatoria region, and low in the southeast and north, where semi-arid savannah dominates. Grasslands, aquatic vegetation and open water occupy the wetter regions. A large part of South Sudan is covered by the Sudd swamp, a conglomeration of smaller wetlands. 24.15069586900006 3.4874709340000436 35.94791809216606 12.237470934700044 MAPX_nd:LandCover_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4016 4645 4914 EPSG:3857:14 7630 8033 9291 9828 EPSG:3857:15 15261 16066 18582 19656 EPSG:3857:16 30523 32132 37164 39312 EPSG:3857:17 61046 64265 74329 78624 EPSG:3857:18 122092 128530 148658 157248 EPSG:3857:19 244184 257061 297316 314496 EPSG:3857:20 488369 514123 594632 628993 EPSG:3857:21 976739 1028247 1189264 1257987 EPSG:3857:22 1953478 2056494 2378528 2515975 EPSG:3857:23 3906957 4112989 4757056 5031951 EPSG:3857:24 7813914 8225979 9514112 10063902 EPSG:3857:25 15627828 16451959 19028224 20127804 EPSG:3857:26 31255657 32903918 38056448 40255609 EPSG:3857:27 62511314 65807836 76112896 80511219 EPSG:3857:28 125022629 131615673 152225792 161022438 EPSG:3857:29 250045258 263231347 304451584 322044877 EPSG:3857:30 500090517 526462695 608903168 644089754 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 6 7 18 19 EPSG:4326:5 13 15 36 38 EPSG:4326:6 27 30 72 76 EPSG:4326:7 55 61 145 153 EPSG:4326:8 110 123 290 307 EPSG:4326:9 221 246 580 614 EPSG:4326:10 442 492 1161 1228 EPSG:4326:11 884 984 2322 2457 EPSG:4326:12 1769 1968 4645 4914 EPSG:4326:13 3539 3937 9291 9828 EPSG:4326:14 7078 7874 18582 19656 EPSG:4326:15 14156 15749 37164 39312 EPSG:4326:16 28312 31498 74329 78624 EPSG:4326:17 56624 62996 148658 157248 EPSG:4326:18 113249 125993 297316 314496 EPSG:4326:19 226499 251986 594632 628993 EPSG:4326:20 452999 503972 1189264 1257987 EPSG:4326:21 905999 1007944 2378528 2515975 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4016 4645 4914 EPSG:3857:14 7630 8033 9291 9828 EPSG:3857:15 15261 16066 18582 19656 EPSG:3857:16 30523 32132 37164 39312 EPSG:3857:17 61046 64265 74329 78624 EPSG:3857:18 122092 128530 148658 157248 EPSG:3857:19 244184 257061 297316 314496 EPSG:3857:20 488369 514123 594632 628993 EPSG:3857:21 976739 1028247 1189264 1257987 EPSG:3857:22 1953478 2056494 2378528 2515975 EPSG:3857:23 3906957 4112989 4757056 5031951 EPSG:3857:24 7813914 8225979 9514112 10063902 EPSG:3857:25 15627828 16451959 19028224 20127804 EPSG:3857:26 31255657 32903918 38056448 40255609 EPSG:3857:27 62511314 65807836 76112896 80511219 EPSG:3857:28 125022629 131615673 152225792 161022438 EPSG:3857:29 250045258 263231347 304451584 322044877 EPSG:3857:30 500090517 526462695 608903168 644089754 Spectral Acceleration 0.5 Sec 475 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_05_s_475_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Kerala Flood 100 Years RP - RCP85 Kerala State flood hazard map - RCP 8.5 scenario. Maximum expected flood event water height in a 100 years return period, expressed in cm. 74.85958333333333 8.25375 77.49208333333334 12.842916666666673 ECO-DRR:Kerala_Flood_100_Yrs_RCP85 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185583 187500 EPSG:4326:18 112368 119051 371166 375000 EPSG:4326:19 224736 238103 742332 750000 EPSG:4326:20 449472 476206 1484664 1500000 EPSG:4326:21 898945 952412 2969329 3000000 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 Tropical Cyclone Intensity -180.0 -90.0 179.99599307699998 83.99199665399996 wesr_risk:cy_intensity image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 63 2047 0 2047 EPSG:3857:12 126 4095 0 4095 EPSG:3857:13 253 8191 0 8191 EPSG:3857:14 506 16383 0 16383 EPSG:3857:15 1012 32767 0 32767 EPSG:3857:16 2025 65535 0 65535 EPSG:3857:17 4051 131071 0 131070 EPSG:3857:18 8103 262143 0 262141 EPSG:3857:19 16206 524287 0 524282 EPSG:3857:20 32413 1048575 0 1048564 EPSG:3857:21 64827 2097151 0 2097128 EPSG:3857:22 129655 4194303 0 4194257 EPSG:3857:23 259311 8388607 0 8388514 EPSG:3857:24 518622 16777215 0 16777029 EPSG:3857:25 1037245 33554431 0 33554058 EPSG:3857:26 2074490 67108863 0 67108117 EPSG:3857:27 4148981 134217727 0 134216234 EPSG:3857:28 8297963 268435455 0 268432468 EPSG:3857:29 16595927 536870911 0 536864936 EPSG:3857:30 33191854 1073741823 0 1073729872 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1093 32767 0 65535 EPSG:4326:16 2187 65535 0 131070 EPSG:4326:17 4374 131071 0 262141 EPSG:4326:18 8749 262143 0 524282 EPSG:4326:19 17499 524287 0 1048564 EPSG:4326:20 34999 1048575 0 2097128 EPSG:4326:21 69998 2097151 0 4194257 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 63 2047 0 2047 EPSG:3857:12 126 4095 0 4095 EPSG:3857:13 253 8191 0 8191 EPSG:3857:14 506 16383 0 16383 EPSG:3857:15 1012 32767 0 32767 EPSG:3857:16 2025 65535 0 65535 EPSG:3857:17 4051 131071 0 131070 EPSG:3857:18 8103 262143 0 262141 EPSG:3857:19 16206 524287 0 524282 EPSG:3857:20 32413 1048575 0 1048564 EPSG:3857:21 64827 2097151 0 2097128 EPSG:3857:22 129655 4194303 0 4194257 EPSG:3857:23 259311 8388607 0 8388514 EPSG:3857:24 518622 16777215 0 16777029 EPSG:3857:25 1037245 33554431 0 33554058 EPSG:3857:26 2074490 67108863 0 67108117 EPSG:3857:27 4148981 134217727 0 134216234 EPSG:3857:28 8297963 268435455 0 268432468 EPSG:3857:29 16595927 536870911 0 536864936 EPSG:3857:30 33191854 1073741823 0 1073729872 Automn precipitations change (%) for the period 2080 - 2099 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_son_ENDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Tsunami hazard frequency -180.0 -90.0 180.0 90.0 ECO-DRR:ts_freqaf_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Year precipitations 2009 - Central African Republic Total precipitations observed in 2009 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2009_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 pop_landscan2011 -180.0 -90.0 179.99999999999858 83.99999999999932 grid_data_core_pro:pop_landscan2011 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34952 1048575 0 2097151 EPSG:4326:21 69905 2097151 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 0 31 0 31 EPSG:900913:6 1 63 0 63 EPSG:900913:7 3 127 0 127 EPSG:900913:8 7 255 0 255 EPSG:900913:9 15 511 0 511 EPSG:900913:10 31 1023 0 1023 EPSG:900913:11 62 2047 0 2047 EPSG:900913:12 125 4095 0 4095 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760567125 Spectral Acceleration 0.5 Sec 250 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_05_s_250_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Summer temperature change (°C) for the period 2080 - 2099 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_jja_ENDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Spring temperature change (°C) for the period 2080 - 2099 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_mam_ENDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 frac_cats_transition_2020_2021_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_transition_2020_2021_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Annual Precipitation [mm/year] (2041-2060) RCP8.5 - CIMP5 Accumulated precipitation amount over 1 year [mm/year] for the period 2041-2060 based on RCP8.5. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_bio_mon_ACCESS1-0_rcp85_r1i1p1_g025.nc_12_2041-2060_V1.2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 Mean temperatures 2002 - Central African Republic Mean observed temperatures in 2002 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2002_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 MERIT Hydro DEM MERIT Hydro is a global hydrography datasets, developed based on the MERIT DEM and multiple inland water maps. It contains flow direction, flow accumulation, hydrologically adjusted elevations, and river channel width. Yamazaki D., D. Ikeshima, J. Sosa, P.D. Bates, G.H. Allen, T.M. Pavelsky MERIT Hydro: A high-resolution global hydrography map based on latest topography datasets Water Resources Research, vol.55, pp.5053-5073, 2019, doi: 10.1029/2019WR024873 -180.0 -90.0 180.0 90.0 testing:codeglob image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Landslide/Forest at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_lds_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 lebanon_remote_site_screening_res50 35.103656 33.05658 36.606156 34.69208 mapx_chemobs:lebanon_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml 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2000-2022, defined as a stand-replacement disturbance, or a change from a forest to non-forest state. 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4925113 EPSG:3857:24 8135263 9021906 8905402 9850226 EPSG:3857:25 16270527 18043812 17810804 19700452 EPSG:3857:26 32541054 36087624 35621608 39400904 EPSG:3857:27 65082108 72175248 71243216 78801809 EPSG:3857:28 130164216 144350496 142486433 157603619 EPSG:3857:29 260328432 288700992 284972866 315207238 EPSG:3857:30 520656865 577401984 569945732 630414477 Forest Integrity Colombia Forest Integrity (100m res.) in Colombia (Montana State University). -79.758379943848 -4.470114545847 -66.21837994384799 11.205885454153 MapX_UNDP:col_forint100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 5 EPSG:3857:5 14 16 8 10 EPSG:3857:6 29 32 17 20 EPSG:3857:7 59 65 35 40 EPSG:3857:8 119 131 71 80 EPSG:3857:9 239 262 142 161 EPSG:3857:10 479 524 285 323 EPSG:3857:11 959 1049 570 647 EPSG:3857:12 1919 2098 1140 1294 EPSG:3857:13 3839 4197 2281 2589 EPSG:3857:14 7678 8395 4562 5178 EPSG:3857:15 15357 16791 9124 10356 EPSG:3857:16 30714 33582 18248 20713 EPSG:3857:17 61429 67165 36496 41426 EPSG:3857:18 122859 134330 72993 82853 EPSG:3857:19 245719 268660 145987 165706 EPSG:3857:20 491438 537321 291974 331412 EPSG:3857:21 982876 1074642 583949 662825 EPSG:3857:22 1965753 2149285 1167899 1325651 EPSG:3857:23 3931507 4298571 2335799 2651303 EPSG:3857:24 7863014 8597142 4671598 5302607 EPSG:3857:25 15726028 17194284 9343196 10605215 EPSG:3857:26 31452057 34388568 18686392 21210431 EPSG:3857:27 62904114 68777136 37372784 42420862 EPSG:3857:28 125808229 137554273 74745569 84841725 EPSG:3857:29 251616458 275108547 149491138 169683450 EPSG:3857:30 503232917 550217094 298982277 339366900 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 1 1 1 EPSG:4326:2 1 2 2 2 EPSG:4326:3 3 4 4 5 EPSG:4326:4 7 8 8 10 EPSG:4326:5 14 16 17 20 EPSG:4326:6 28 33 35 40 EPSG:4326:7 56 67 71 80 EPSG:4326:8 112 134 142 161 EPSG:4326:9 224 268 285 323 EPSG:4326:10 448 537 570 647 EPSG:4326:11 896 1074 1140 1294 EPSG:4326:12 1793 2149 2281 2589 EPSG:4326:13 3586 4299 4562 5178 EPSG:4326:14 7172 8598 9124 10356 EPSG:4326:15 14344 17197 18248 20713 EPSG:4326:16 28688 34395 36496 41426 EPSG:4326:17 57376 68791 72993 82853 EPSG:4326:18 114752 137582 145987 165706 EPSG:4326:19 229504 275164 291974 331412 EPSG:4326:20 459008 550328 583949 662825 EPSG:4326:21 918017 1100656 1167899 1325651 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 0 EPSG:900913:2 1 2 1 1 EPSG:900913:3 3 4 2 2 EPSG:900913:4 7 8 4 5 EPSG:900913:5 14 16 8 10 EPSG:900913:6 29 32 17 20 EPSG:900913:7 59 65 35 40 EPSG:900913:8 119 131 71 80 EPSG:900913:9 239 262 142 161 EPSG:900913:10 479 524 285 323 EPSG:900913:11 959 1049 570 647 EPSG:900913:12 1919 2098 1140 1294 EPSG:900913:13 3839 4197 2281 2589 EPSG:900913:14 7678 8395 4562 5178 EPSG:900913:15 15357 16791 9124 10356 EPSG:900913:16 30714 33582 18248 20713 EPSG:900913:17 61429 67165 36496 41426 EPSG:900913:18 122859 134330 72993 82853 EPSG:900913:19 245719 268660 145987 165706 EPSG:900913:20 491438 537321 291974 331412 EPSG:900913:21 982876 1074642 583949 662825 EPSG:900913:22 1965753 2149285 1167899 1325651 EPSG:900913:23 3931507 4298571 2335799 2651303 EPSG:900913:24 7863014 8597142 4671598 5302607 EPSG:900913:25 15726028 17194284 9343196 10605215 EPSG:900913:26 31452057 34388568 18686392 21210431 EPSG:900913:27 62904114 68777136 37372784 42420862 EPSG:900913:28 125808229 137554273 74745569 84841725 EPSG:900913:29 251616458 275108547 149491138 169683450 EPSG:900913:30 503232917 550217094 298982277 339366900 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 5 EPSG:3857:5 14 16 8 10 EPSG:3857:6 29 32 17 20 EPSG:3857:7 59 65 35 40 EPSG:3857:8 119 131 71 80 EPSG:3857:9 239 262 142 161 EPSG:3857:10 479 524 285 323 EPSG:3857:11 959 1049 570 647 EPSG:3857:12 1919 2098 1140 1294 EPSG:3857:13 3839 4197 2281 2589 EPSG:3857:14 7678 8395 4562 5178 EPSG:3857:15 15357 16791 9124 10356 EPSG:3857:16 30714 33582 18248 20713 EPSG:3857:17 61429 67165 36496 41426 EPSG:3857:18 122859 134330 72993 82853 EPSG:3857:19 245719 268660 145987 165706 EPSG:3857:20 491438 537321 291974 331412 EPSG:3857:21 982876 1074642 583949 662825 EPSG:3857:22 1965753 2149285 1167899 1325651 EPSG:3857:23 3931507 4298571 2335799 2651303 EPSG:3857:24 7863014 8597142 4671598 5302607 EPSG:3857:25 15726028 17194284 9343196 10605215 EPSG:3857:26 31452057 34388568 18686392 21210431 EPSG:3857:27 62904114 68777136 37372784 42420862 EPSG:3857:28 125808229 137554273 74745569 84841725 EPSG:3857:29 251616458 275108547 149491138 169683450 EPSG:3857:30 503232917 550217094 298982277 339366900 Economical Exposition to Drought Events in GHA Region This dataset includes an estimation of the annual economical exposition to drought based on Standardized Precipitation Index. It is based on three sources: 1) A global monthly gridded precipitation dataset obtained from the Climatic Research Unit (University of East Anglia). 2) A GIS modeling of global Standardized Precipitation Index based on Brad Lyon (IRI, Columbia University) methodology. Data provided by ICPAC Geoportal at http://geoportal.icpac.net/. 21.838947 -11.745700000296004 51.440099935812 23.14286 wesr_cca:geonode_drought_econ_exposure_icpac image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 6 8 8 10 EPSG:3857:5 13 17 17 20 EPSG:3857:6 27 34 35 41 EPSG:3857:7 55 68 71 82 EPSG:3857:8 111 136 143 164 EPSG:3857:9 222 272 287 329 EPSG:3857:10 444 545 574 658 EPSG:3857:11 888 1091 1148 1316 EPSG:3857:12 1777 2182 2296 2633 EPSG:3857:13 3554 4365 4592 5266 EPSG:3857:14 7108 8730 9185 10533 EPSG:3857:15 14217 17460 18371 21066 EPSG:3857:16 28435 34921 36743 42132 EPSG:3857:17 56871 69842 73487 84264 EPSG:3857:18 113742 139685 146974 168529 EPSG:3857:19 227484 279371 293949 337059 EPSG:3857:20 454968 558742 587898 674118 EPSG:3857:21 909936 1117484 1175797 1348236 EPSG:3857:22 1819872 2234968 2351594 2696472 EPSG:3857:23 3639744 4469936 4703188 5392945 EPSG:3857:24 7279489 8939872 9406376 10785890 EPSG:3857:25 14558978 17879744 18812753 21571780 EPSG:3857:26 29117957 35759488 37625506 43143561 EPSG:3857:27 58235914 71518976 75251013 86287123 EPSG:3857:28 116471828 143037953 150502027 172574246 EPSG:3857:29 232943657 286075907 301004054 345148493 EPSG:3857:30 465887314 572151815 602008108 690296986 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 5 EPSG:4326:3 2 4 8 10 EPSG:4326:4 5 9 17 20 EPSG:4326:5 11 18 35 41 EPSG:4326:6 23 36 71 82 EPSG:4326:7 47 72 143 164 EPSG:4326:8 95 144 287 329 EPSG:4326:9 190 289 574 658 EPSG:4326:10 380 578 1148 1316 EPSG:4326:11 760 1157 2296 2633 EPSG:4326:12 1521 2315 4592 5266 EPSG:4326:13 3042 4630 9185 10533 EPSG:4326:14 6085 9261 18371 21066 EPSG:4326:15 12170 18522 36743 42132 EPSG:4326:16 24341 37044 73487 84264 EPSG:4326:17 48683 74088 146974 168529 EPSG:4326:18 97367 148177 293949 337059 EPSG:4326:19 194735 296355 587898 674118 EPSG:4326:20 389471 592711 1175797 1348236 EPSG:4326:21 778942 1185423 2351594 2696472 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 6 8 8 10 EPSG:3857:5 13 17 17 20 EPSG:3857:6 27 34 35 41 EPSG:3857:7 55 68 71 82 EPSG:3857:8 111 136 143 164 EPSG:3857:9 222 272 287 329 EPSG:3857:10 444 545 574 658 EPSG:3857:11 888 1091 1148 1316 EPSG:3857:12 1777 2182 2296 2633 EPSG:3857:13 3554 4365 4592 5266 EPSG:3857:14 7108 8730 9185 10533 EPSG:3857:15 14217 17460 18371 21066 EPSG:3857:16 28435 34921 36743 42132 EPSG:3857:17 56871 69842 73487 84264 EPSG:3857:18 113742 139685 146974 168529 EPSG:3857:19 227484 279371 293949 337059 EPSG:3857:20 454968 558742 587898 674118 EPSG:3857:21 909936 1117484 1175797 1348236 EPSG:3857:22 1819872 2234968 2351594 2696472 EPSG:3857:23 3639744 4469936 4703188 5392945 EPSG:3857:24 7279489 8939872 9406376 10785890 EPSG:3857:25 14558978 17879744 18812753 21571780 EPSG:3857:26 29117957 35759488 37625506 43143561 EPSG:3857:27 58235914 71518976 75251013 86287123 EPSG:3857:28 116471828 143037953 150502027 172574246 EPSG:3857:29 232943657 286075907 301004054 345148493 EPSG:3857:30 465887314 572151815 602008108 690296986 Forest Biodiversity Intactness <span style="font-size:1em"> This newly produced layer assesses the impacts of forest management on biodiversity intactness across the globe. This layer focuses on the forested regions of the planet (natural and non-natural) and estimates biodiversity intactness by using information on forest management based on the layer that has been produced under the umbrella of the Nature Map project (Lesiv et al., 2020) and biodiversity intactness from models derived from the PREDICTS database (Hudson et al., 2017). The Biodiversity Intactness Index (BII) describes the average abundance of a taxonomically and ecologically broad set of species in an area, relative to their abundances in an intact reference ecosystem (Scholes & Biggs, 2005). Demonstrating the relevance of the index, BII has recently been included as a core indicator by IPBES and as an Essential Biodiversity Variable by GEO BON. <br> <br> <u>References:</u> <ul> <li> Hill, S.L.L. et al. (2018) Worldwide Impacts of Past and Projected Future Land-Use Change on Local Species Richness and the Biodiversity Intactness Index. BioRxiv, May 1, 2018, 311787. <a href="https://doi.org/10.1101/311787" target="_blank">doi.org/10.1101/311787</a>. </li> <li>Hudson, L.N., et al. (2017) The Database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) Project. Ecology and Evolution 7, no. 1: 145–88. <a href="https://doi.org/10.1002/ece3.2579" target="_blank">doi.org/10.1002/ece3.2579</a>. </li> <li>Lesiv, M., et al. (2020) Methodology for Generating a Global Forest Management Layer. Zenodo, July 7, 2020. <a href="https://doi.org/10.5281/zenodo.3933966" target="_blank">doi.org/10.5281/zenodo.3933966</a>. </li> <li>Newbold, T. et al. (2016) Has Land Use Pushed Terrestrial Biodiversity beyond the Planetary Boundary? A Global Assessment. Science 353, no. 6296: 288–91.<a href="https://doi.org/10.1126/science.aaf2201" target="_blank">doi.org/10.1126/science.aaf2201.</a> </li> <li>Scholes, R. J. et al. (2005) A Biodiversity Intactness Index. Nature 434, no. 7029: 45–49.<a href=" https://doi.org/10.1038/nature03289." target="_blank">doi.org/10.1038/nature03289.</a> </li> <li>Steffen, W. et al. (2015) Planetary Boundaries: Guiding Human Development on a Changing Planet. Science 347, no. 6223.<a href="https://doi.org/10.1126/science.1259855."> doi.org/10.1126/science.1259855.</a> </li> </ul> </span> -179.991848215593 -81.8206539215438 179.9875281634017 81.8207424633558 MapX_UNDP:forest_biodiversity_intactness_index_naturemap_2020_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 1 14 0 15 EPSG:3857:5 2 29 0 31 EPSG:3857:6 5 58 0 63 EPSG:3857:7 10 117 0 127 EPSG:3857:8 20 235 0 255 EPSG:3857:9 41 470 0 511 EPSG:3857:10 82 941 0 1023 EPSG:3857:11 164 1883 0 2047 EPSG:3857:12 328 3767 0 4095 EPSG:3857:13 656 7535 0 8191 EPSG:3857:14 1312 15070 0 16383 EPSG:3857:15 2625 30141 0 32766 EPSG:3857:16 5251 60283 1 65533 EPSG:3857:17 10503 120567 2 131067 EPSG:3857:18 21007 241135 5 262134 EPSG:3857:19 42015 482271 11 524269 EPSG:3857:20 84030 964543 23 1048539 EPSG:3857:21 168060 1929087 47 2097079 EPSG:3857:22 336121 3858174 94 4194158 EPSG:3857:23 672243 7716349 189 8388317 EPSG:3857:24 1344487 15432699 379 16776634 EPSG:3857:25 2688975 30865398 759 33553269 EPSG:3857:26 5377951 61730796 1519 67106539 EPSG:3857:27 10755903 123461592 3039 134213078 EPSG:3857:28 21511806 246923185 6078 268426156 EPSG:3857:29 43023612 493846371 12156 536852312 EPSG:3857:30 86047224 987692743 24313 1073704625 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 30 0 63 EPSG:4326:6 2 61 0 127 EPSG:4326:7 5 122 0 255 EPSG:4326:8 11 244 0 511 EPSG:4326:9 23 488 0 1023 EPSG:4326:10 46 977 0 2047 EPSG:4326:11 93 1954 0 4095 EPSG:4326:12 186 3909 0 8191 EPSG:4326:13 372 7819 0 16383 EPSG:4326:14 744 15639 0 32766 EPSG:4326:15 1488 31278 1 65533 EPSG:4326:16 2977 62557 2 131067 EPSG:4326:17 5955 125115 5 262134 EPSG:4326:18 11911 250231 11 524269 EPSG:4326:19 23823 500463 23 1048539 EPSG:4326:20 47647 1000927 47 2097079 EPSG:4326:21 95295 2001855 94 4194158 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 1 14 0 15 EPSG:3857:5 2 29 0 31 EPSG:3857:6 5 58 0 63 EPSG:3857:7 10 117 0 127 EPSG:3857:8 20 235 0 255 EPSG:3857:9 41 470 0 511 EPSG:3857:10 82 941 0 1023 EPSG:3857:11 164 1883 0 2047 EPSG:3857:12 328 3767 0 4095 EPSG:3857:13 656 7535 0 8191 EPSG:3857:14 1312 15070 0 16383 EPSG:3857:15 2625 30141 0 32766 EPSG:3857:16 5251 60283 1 65533 EPSG:3857:17 10503 120567 2 131067 EPSG:3857:18 21007 241135 5 262134 EPSG:3857:19 42015 482271 11 524269 EPSG:3857:20 84030 964543 23 1048539 EPSG:3857:21 168060 1929087 47 2097079 EPSG:3857:22 336121 3858174 94 4194158 EPSG:3857:23 672243 7716349 189 8388317 EPSG:3857:24 1344487 15432699 379 16776634 EPSG:3857:25 2688975 30865398 759 33553269 EPSG:3857:26 5377951 61730796 1519 67106539 EPSG:3857:27 10755903 123461592 3039 134213078 EPSG:3857:28 21511806 246923185 6078 268426156 EPSG:3857:29 43023612 493846371 12156 536852312 EPSG:3857:30 86047224 987692743 24313 1073704625 med_00_ogs_nut_an-fc-m-avrg_year_2020_po3 -5.562499842 30.166666665 36.312501272 46.000001273 Medicip:med_00_ogs_nut_an-fc-m-avrg_year_2020_po3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 31 38 EPSG:3857:7 45 52 62 76 EPSG:3857:8 91 105 124 153 EPSG:3857:9 182 210 248 307 EPSG:3857:10 364 421 496 615 EPSG:3857:11 728 843 992 1230 EPSG:3857:12 1457 1687 1984 2461 EPSG:3857:13 2914 3375 3969 4922 EPSG:3857:14 5828 6750 7938 9844 EPSG:3857:15 11657 13501 15877 19689 EPSG:3857:16 23315 27003 31755 39378 EPSG:3857:17 46630 54006 63510 78756 EPSG:3857:18 93260 108013 127021 157513 EPSG:3857:19 186521 216027 254043 315027 EPSG:3857:20 373043 432055 508086 630055 EPSG:3857:21 746086 864110 1016172 1260111 EPSG:3857:22 1492173 1728221 2032344 2520223 EPSG:3857:23 2984346 3456443 4064688 5040446 EPSG:3857:24 5968692 6912887 8129376 10080893 EPSG:3857:25 11937384 13825774 16258753 20161786 EPSG:3857:26 23874768 27651548 32517506 40323572 EPSG:3857:27 47749536 55303096 65035013 80647145 EPSG:3857:28 95499073 110606193 130070027 161294291 EPSG:3857:29 190998146 221212386 260140054 322588582 EPSG:3857:30 381996293 442424772 520280109 645177165 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 15 19 EPSG:4326:5 7 10 31 38 EPSG:4326:6 15 21 62 76 EPSG:4326:7 31 42 124 153 EPSG:4326:8 62 85 248 307 EPSG:4326:9 125 170 496 615 EPSG:4326:10 250 340 992 1230 EPSG:4326:11 500 680 1984 2461 EPSG:4326:12 1001 1361 3969 4922 EPSG:4326:13 2002 2723 7938 9844 EPSG:4326:14 4004 5446 15877 19689 EPSG:4326:15 8009 10892 31755 39378 EPSG:4326:16 16019 21784 63510 78756 EPSG:4326:17 32039 43569 127021 157513 EPSG:4326:18 64079 87138 254043 315027 EPSG:4326:19 128159 174277 508086 630055 EPSG:4326:20 256318 348554 1016172 1260111 EPSG:4326:21 512637 697108 2032344 2520223 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 31 38 EPSG:3857:7 45 52 62 76 EPSG:3857:8 91 105 124 153 EPSG:3857:9 182 210 248 307 EPSG:3857:10 364 421 496 615 EPSG:3857:11 728 843 992 1230 EPSG:3857:12 1457 1687 1984 2461 EPSG:3857:13 2914 3375 3969 4922 EPSG:3857:14 5828 6750 7938 9844 EPSG:3857:15 11657 13501 15877 19689 EPSG:3857:16 23315 27003 31755 39378 EPSG:3857:17 46630 54006 63510 78756 EPSG:3857:18 93260 108013 127021 157513 EPSG:3857:19 186521 216027 254043 315027 EPSG:3857:20 373043 432055 508086 630055 EPSG:3857:21 746086 864110 1016172 1260111 EPSG:3857:22 1492173 1728221 2032344 2520223 EPSG:3857:23 2984346 3456443 4064688 5040446 EPSG:3857:24 5968692 6912887 8129376 10080893 EPSG:3857:25 11937384 13825774 16258753 20161786 EPSG:3857:26 23874768 27651548 32517506 40323572 EPSG:3857:27 47749536 55303096 65035013 80647145 EPSG:3857:28 95499073 110606193 130070027 161294291 EPSG:3857:29 190998146 221212386 260140054 322588582 EPSG:3857:30 381996293 442424772 520280109 645177165 Average year precipitations anomalies (2021-2022) against 1901-1920 Average year precipitations anomalies in mm across the period 2021-2022 calculated over the average precipitations per year in the period 1901-1920 (as close as possible to the pre-industrial era). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_21_22_anom_1901_1920 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 1991-2000 Average year temperature change since previous decade (1981-1990) Average year temperature anomalies in °C across the period 1991-2000calculated over the average temperature per year in the period 1981-1990. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_00_anom_81_90 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 aggregate_consumption_per_year_Mt -180.0 -90.0 180.0 90.0 sand:aggregate_consumption_per_year_Mt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Precipitation change trend (1991-2022) Trend of year precipitations in 'mm per year' across the period 1991-2022. Calculated at UNEP/GRID-Geneva in R using linear regression model's slope based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_91_22_lm image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Central Congo Basin peat carbon density (2022) Metadata for the file: Crezee_2022_Median_Carbon_density_2000runs.tif This is the file used to create Figure 4a of the paper: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This is a raster file representing modelled peat carbon density (in Mg C per ha) across the central Congo Basin peatland complex. For each pixel, the median value of 2,000 carbon density estimates is provided. The 2,000 carbon density estimates were obtained by multiplying 100 Random Forest peat thickness estimates with 20 bootstrapped peat thickness-carbon density regressions (ED Fig. 7), which were normally distributed arond the best-fitting peat thickness-carbon density regression. The peat thickness-carbon density regression is based on 80 peat cores sampled in the field. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 14.999619457 -5.015743389 24.000289446 3.511065288 peatlands:Crezee_2022_Median_Carbon_density_2000runs_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 72 EPSG:3857:8 125 131 138 145 EPSG:3857:9 251 263 277 290 EPSG:3857:10 502 526 554 580 EPSG:3857:11 1004 1052 1109 1160 EPSG:3857:12 2008 2105 2218 2321 EPSG:3857:13 4016 4210 4437 4642 EPSG:3857:14 8032 8420 8874 9284 EPSG:3857:15 16064 16841 17749 18568 EPSG:3857:16 32128 33682 35498 37137 EPSG:3857:17 64256 67364 70997 74274 EPSG:3857:18 128513 134729 141994 148548 EPSG:3857:19 257027 269458 283988 297096 EPSG:3857:20 514054 538916 567977 594193 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148548 EPSG:4326:18 125958 138376 283988 297096 EPSG:4326:19 251917 276753 567977 594193 EPSG:4326:20 503834 553506 1135955 1188387 EPSG:4326:21 1007669 1107013 2271910 2376775 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 72 EPSG:3857:8 125 131 138 145 EPSG:3857:9 251 263 277 290 EPSG:3857:10 502 526 554 580 EPSG:3857:11 1004 1052 1109 1160 EPSG:3857:12 2008 2105 2218 2321 EPSG:3857:13 4016 4210 4437 4642 EPSG:3857:14 8032 8420 8874 9284 EPSG:3857:15 16064 16841 17749 18568 EPSG:3857:16 32128 33682 35498 37137 EPSG:3857:17 64256 67364 70997 74274 EPSG:3857:18 128513 134729 141994 148548 EPSG:3857:19 257027 269458 283988 297096 EPSG:3857:20 514054 538916 567977 594193 EPSG:3857:21 1028109 1077832 1135955 1188387 EPSG:3857:22 2056219 2155664 2271910 2376775 EPSG:3857:23 4112438 4311328 4543820 4753551 EPSG:3857:24 8224877 8622657 9087640 9507102 EPSG:3857:25 16449755 17245315 18175281 19014205 EPSG:3857:26 32899511 34490630 36350563 38028410 EPSG:3857:27 65799023 68981261 72701127 76056820 EPSG:3857:28 131598047 137962523 145402254 152113640 EPSG:3857:29 263196095 275925046 290804509 304227281 EPSG:3857:30 526392191 551850093 581609019 608454563 eswatini_remote_site_screening_res50 30.794110000000003 -27.317150000000023 32.13711000000001 -25.719650000000023 mapx_chemobs:eswatini_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 9 9 9 9 EPSG:3857:5 18 18 18 18 EPSG:3857:6 36 37 37 37 EPSG:3857:7 73 74 74 75 EPSG:3857:8 146 148 149 150 EPSG:3857:9 293 296 299 301 EPSG:3857:10 587 592 599 603 EPSG:3857:11 1175 1185 1199 1206 EPSG:3857:12 2350 2371 2398 2413 EPSG:3857:13 4701 4742 4796 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151763 153495 154473 EPSG:3857:19 300926 303526 306991 308947 EPSG:3857:20 601852 607052 613982 617894 EPSG:3857:21 1203704 1214105 1227964 1235788 EPSG:3857:22 2407409 2428211 2455929 2471576 EPSG:3857:23 4814819 4856423 4911858 4943152 EPSG:3857:24 9629639 9712846 9823717 9886305 EPSG:3857:25 19259279 19425692 19647435 19772611 EPSG:3857:26 38518559 38851385 39294870 39545223 EPSG:3857:27 77037118 77702771 78589740 79090447 EPSG:3857:28 154074237 155405543 157179480 158180894 EPSG:3857:29 308148475 310811086 314358961 316361788 EPSG:3857:30 616296951 621622173 628717922 632723576 Ocean Pollution (Shipping Lanes, Ports) Pressures 2013 - KNB This data layer shows the ocean-based pollution from stressor data after adjusting for habitat/pressure vulnerability. This data layer combines estimates of pollution coming from commercial shipping and from ports. As such, it is a combination of the shipping and port volume data layers, with the port volume data plumed to estimate pollution from commercial ports (with exponential decline in intensity from the port). Ocean-based pollution is assumed to derive from commercial and recreational ship activity. No data on global recreational ship activity currently exist, and therefore we modelled this driver to oceans using a combination of the commercial shipping traffic data and port data. The shipping data provide an estimate of the occurrence of ships at a particular location, and therefore an estimate of the amount of pollution they produce (via fuel leaks, oil discharge, waste disposal, etc.) that is unique from their contribution to ship strikes, etc. described above. We recognize that ocean currents can disperse this pollution into untraveled regions, but small-scale oceanography is known for only a few select locations around the world, and pollutants are likely to be most concentrated in high traffic areas. The dispersal of port-derived pollution was modelled as a diffusive plume with a maximum distance of 100 km. These plumes were not clipped to shallow regions as was done for Invasive Species. Pressure data was calculated for each stressor by: (1) multiplying the rescaled stressor (rescaled using only the 2013 data) by each habitat layer and the corresponding stressor/habitat vulnerability score (for each stressor this generates: 20 rasters); (2) summing the resulting stressor/habitat/vulnerability rasters (generates 1 raster for each stressor); (3) dividing by the number of habitats found in each raster cell layer. Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: pressure and cumulative impacts data (2013, all pressures). Knowledge Network for Biocomplexity. doi:10.5063/F15718ZN. -179.9999997892864 -89.9976531808165 179.99802237904566 85.28467978960349 MapX_UNDP:13_ocean_pollution_pressures_halpern_KNB_WGS84 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262142 EPSG:3857:19 0 524287 0 524285 EPSG:3857:20 0 1048575 0 1048570 EPSG:3857:21 0 2097151 0 2097140 EPSG:3857:22 -1 4194303 0 4194280 EPSG:3857:23 -1 8388607 0 8388561 EPSG:3857:24 0 16777215 0 16777123 EPSG:3857:25 0 33554431 0 33554247 EPSG:3857:26 0 67108863 0 67108495 EPSG:3857:27 0 134217727 0 134216990 EPSG:3857:28 -1 268435455 0 268433981 EPSG:3857:29 0 536870911 0 536867962 EPSG:3857:30 0 1073741823 0 1073735925 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 6 255 0 511 EPSG:4326:9 13 511 0 1023 EPSG:4326:10 26 1023 0 2047 EPSG:4326:11 53 2047 0 4095 EPSG:4326:12 107 4095 0 8191 EPSG:4326:13 214 8191 0 16383 EPSG:4326:14 429 16383 0 32767 EPSG:4326:15 858 32767 0 65535 EPSG:4326:16 1716 65535 0 131071 EPSG:4326:17 3433 131070 0 262142 EPSG:4326:18 6867 262140 0 524285 EPSG:4326:19 13734 524281 0 1048570 EPSG:4326:20 27468 1048562 0 2097140 EPSG:4326:21 54937 2097124 0 4194280 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 0 31 0 31 EPSG:900913:6 0 63 0 63 EPSG:900913:7 0 127 0 127 EPSG:900913:8 0 255 0 255 EPSG:900913:9 0 511 0 511 EPSG:900913:10 0 1023 0 1023 EPSG:900913:11 0 2047 0 2047 EPSG:900913:12 0 4095 0 4095 EPSG:900913:13 0 8191 0 8191 EPSG:900913:14 0 16383 0 16383 EPSG:900913:15 0 32767 0 32767 EPSG:900913:16 0 65535 0 65535 EPSG:900913:17 0 131071 0 131071 EPSG:900913:18 0 262143 0 262142 EPSG:900913:19 0 524287 0 524285 EPSG:900913:20 0 1048575 0 1048570 EPSG:900913:21 0 2097151 0 2097140 EPSG:900913:22 0 4194303 0 4194280 EPSG:900913:23 0 8388607 0 8388561 EPSG:900913:24 0 16777215 0 16777123 EPSG:900913:25 0 33554431 0 33554247 EPSG:900913:26 0 67108863 0 67108495 EPSG:900913:27 0 134217727 0 134216990 EPSG:900913:28 0 268435455 0 268433981 EPSG:900913:29 0 536870911 0 536867962 EPSG:900913:30 0 1073741823 0 1073735925 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262142 EPSG:3857:19 0 524287 0 524285 EPSG:3857:20 0 1048575 0 1048570 EPSG:3857:21 -1 2097151 0 2097140 EPSG:3857:22 -1 4194303 0 4194280 EPSG:3857:23 0 8388607 0 8388561 EPSG:3857:24 0 16777215 0 16777123 EPSG:3857:25 0 33554431 0 33554247 EPSG:3857:26 0 67108863 0 67108495 EPSG:3857:27 -1 134217727 0 134216990 EPSG:3857:28 0 268435455 0 268433981 EPSG:3857:29 0 536870911 0 536867962 EPSG:3857:30 -1 1073741823 0 1073735925 Annual Precipitation - Anomaly [%] (2041-2060 vs 1979-2013) RCP4.5 - CIMP5 Anomaly [%] for the period 2041-2060 compared to climatological data (1979-2013) on the accumulated precipitation amount over 1 year based on RCP4.5. The layer is calculated at UNEP/GRID-Geneva from the layers on annual precipitation [mm/year] provided in the products CHELSA V1.2 and CHELSA-[CMIP5]. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:Perc_Diff_CHELSA_bio_mon_ACCESS1-0_rcp45_r1i1p1_g025.nc_12_2041-2060_V12_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 Global Emissions CO 1970 - EDGARD Global Emissions EDGAR v4.3.1 (January 2016) In EDGARv4.3.1 emissions are calculated for gaseous and particulate air pollutants per sector and country. For the energy related sectors the activity data are mainly based on the energy balance statistics of IEA (2014) Emission gridmaps are expressed in ton substance / 0.1degree x 0.1degree / year -180.0 -77.95 179.95 88.15000000000002 unea_pollution:edg70_co image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 13 0 15 EPSG:900913:5 0 27 0 31 EPSG:900913:6 0 54 0 63 EPSG:900913:7 0 109 0 127 EPSG:900913:8 0 219 0 255 EPSG:900913:9 0 439 0 511 EPSG:900913:10 0 878 0 1023 EPSG:900913:11 0 1756 0 2047 EPSG:900913:12 0 3513 0 4095 EPSG:900913:13 0 7027 0 8190 EPSG:900913:14 0 14055 0 16381 EPSG:900913:15 0 28110 0 32763 EPSG:900913:16 0 56221 0 65526 EPSG:900913:17 0 112443 0 131053 EPSG:900913:18 0 224887 0 262107 EPSG:900913:19 0 449775 0 524215 EPSG:900913:20 0 899550 0 1048430 EPSG:900913:21 0 1799100 0 2096860 EPSG:900913:22 0 3598201 0 4193721 EPSG:900913:23 0 7196402 0 8387442 EPSG:900913:24 0 14392805 0 16774885 EPSG:900913:25 0 28785610 0 33549771 EPSG:900913:26 0 57571220 0 67099543 EPSG:900913:27 0 115142440 0 134199086 EPSG:900913:28 0 230284881 0 268398173 EPSG:900913:29 0 460569763 0 536796346 EPSG:900913:30 0 921139526 0 1073592693 Forest Cover WRI This dataset shows the forest global coverage with canopy density higher than 10%. It is derived from the Current forest coverage from the World Resource Institute Atlas of Forest Landscape Restoration Opportunities, by extracting the 'close forest', 'open forest' and the 'woodlands' classes. Reference period 2000-2009. -180.0 -90.0 180.0 90.0 ECO-DRR:Forest_cover_WRI image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Disappearing Climates 2050 SRES A2 This is the disappearing climate risk dataset - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climatesThis dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007). <br> This dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007).The metrics represent dissimilarity measurements of the squared Euclidean distance between seasonal (June–August and December–February) temperature and precipitation variables in the 20th century climate and mid-21st century climate. (1) disappearing climate risk - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climates (2) novel climate risk - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates. <br> John W. Williams, Karyn Tabor. (2018). Novel and Disappearing Climates 2050 SRES A2 (Version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1559299 John W. Williams, Karyn Tabor. (2018). Novel and Disappearing Climates 2050 SRES A2 (Version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1559299 <br> Support for this project was provided by Conservation International, the Land Tenure Center at the University of Wisconsin, the Center for Climatic Research at the University of Wisconsin, and the Environment Program at the University of Wisconsin–Madison. This research has been funded in part by the Walton Family Foundation, the Gordon and Betty Moore Foundation, and a gift from Betty and Gordon Moore. -180.0 -59.16733350000001 180.0 83.66628549999999 LWP:disp_sresa2_2050_10min_int1000_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 45 0 63 EPSG:3857:7 5 90 0 127 EPSG:3857:8 10 180 0 255 EPSG:3857:9 20 360 0 511 EPSG:3857:10 40 721 0 1023 EPSG:3857:11 80 1443 0 2047 EPSG:3857:12 161 2887 0 4095 EPSG:3857:13 322 5775 0 8191 EPSG:3857:14 644 11551 0 16383 EPSG:3857:15 1288 23102 0 32767 EPSG:3857:16 2577 46204 0 65535 EPSG:3857:17 5155 92409 0 131071 EPSG:3857:18 10310 184819 0 262143 EPSG:3857:19 20620 369639 0 524287 EPSG:3857:20 41241 739279 0 1048575 EPSG:3857:21 82483 1478558 0 2097151 EPSG:3857:22 164966 2957116 0 4194304 EPSG:3857:23 329932 5914233 0 8388608 EPSG:3857:24 659865 11828466 0 16777215 EPSG:3857:25 1319731 23656932 0 33554431 EPSG:3857:26 2639463 47313865 0 67108863 EPSG:3857:27 5278927 94627731 0 134217727 EPSG:3857:28 10557855 189255462 0 268435456 EPSG:3857:29 21115710 378510924 0 536870911 EPSG:3857:30 42231421 757021849 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 9 212 0 511 EPSG:4326:9 18 424 0 1023 EPSG:4326:10 36 848 0 2047 EPSG:4326:11 72 1697 0 4095 EPSG:4326:12 144 3394 0 8191 EPSG:4326:13 288 6788 0 16383 EPSG:4326:14 576 13577 0 32767 EPSG:4326:15 1153 27155 0 65535 EPSG:4326:16 2306 54310 0 131071 EPSG:4326:17 4612 108620 0 262143 EPSG:4326:18 9224 217240 0 524287 EPSG:4326:19 18448 434481 0 1048575 EPSG:4326:20 36896 868962 0 2097151 EPSG:4326:21 73793 1737925 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 45 0 63 EPSG:3857:7 5 90 0 127 EPSG:3857:8 10 180 0 255 EPSG:3857:9 20 360 0 511 EPSG:3857:10 40 721 0 1023 EPSG:3857:11 80 1443 0 2047 EPSG:3857:12 161 2887 0 4095 EPSG:3857:13 322 5775 0 8191 EPSG:3857:14 644 11551 0 16383 EPSG:3857:15 1288 23102 0 32767 EPSG:3857:16 2577 46204 0 65535 EPSG:3857:17 5155 92409 0 131071 EPSG:3857:18 10310 184819 0 262143 EPSG:3857:19 20620 369639 0 524287 EPSG:3857:20 41241 739279 0 1048575 EPSG:3857:21 82483 1478558 0 2097152 EPSG:3857:22 164966 2957116 0 4194304 EPSG:3857:23 329932 5914233 0 8388607 EPSG:3857:24 659865 11828466 0 16777215 EPSG:3857:25 1319731 23656932 0 33554431 EPSG:3857:26 2639463 47313865 0 67108863 EPSG:3857:27 5278927 94627731 0 134217728 EPSG:3857:28 10557855 189255462 0 268435455 EPSG:3857:29 21115710 378510924 0 536870911 EPSG:3857:30 42231421 757021849 0 1073741824 Global Terrestrial Human Footprint (HFP) - 2000 To come -81.71613498761286 -20.61982884080102 153.4232678403954 26.041652531903203 MapX_UNDP:hfp2000_meris_wgs_subset image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27855 36605 17892 60697 EPSG:3857:17 55710 73210 35784 121395 EPSG:3857:18 111420 146421 71568 242791 EPSG:3857:19 222840 292843 143136 485582 EPSG:3857:20 445681 585687 286272 971165 EPSG:3857:21 891362 1171375 572545 1942331 EPSG:3857:22 1782724 2342750 1145090 3884662 EPSG:3857:23 3565448 4685501 2290180 7769325 EPSG:3857:24 7130896 9371002 4580360 15538650 EPSG:3857:25 14261793 18742005 9160720 31077301 EPSG:3857:26 28523587 37484011 18321440 62154602 EPSG:3857:27 57047174 74968023 36642880 124309204 EPSG:3857:28 114094349 149936046 73285761 248618408 EPSG:3857:29 228188699 299872092 146571522 497236816 EPSG:3857:30 456377398 599744184 293143045 994473632 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 90 157 139 474 EPSG:4326:9 181 314 279 948 EPSG:4326:10 363 629 559 1896 EPSG:4326:11 727 1258 1118 3793 EPSG:4326:12 1455 2517 2236 7587 EPSG:4326:13 2910 5034 4473 15174 EPSG:4326:14 5821 10068 8946 30348 EPSG:4326:15 11643 20137 17892 60697 EPSG:4326:16 23286 40275 35784 121395 EPSG:4326:17 46573 80550 71568 242791 EPSG:4326:18 93146 161101 143136 485582 EPSG:4326:19 186292 322203 286272 971165 EPSG:4326:20 372584 644407 572545 1942331 EPSG:4326:21 745168 1288814 1145090 3884662 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 1 2 1 3 EPSG:900913:3 3 4 2 7 EPSG:900913:4 6 8 4 14 EPSG:900913:5 13 17 8 29 EPSG:900913:6 27 35 17 59 EPSG:900913:7 54 71 34 118 EPSG:900913:8 108 142 69 237 EPSG:900913:9 217 285 139 474 EPSG:900913:10 435 571 279 948 EPSG:900913:11 870 1143 559 1896 EPSG:900913:12 1740 2287 1118 3793 EPSG:900913:13 3481 4575 2236 7587 EPSG:900913:14 6963 9151 4473 15174 EPSG:900913:15 13927 18302 8946 30348 EPSG:900913:16 27855 36605 17892 60697 EPSG:900913:17 55710 73210 35784 121395 EPSG:900913:18 111420 146421 71568 242791 EPSG:900913:19 222840 292843 143136 485582 EPSG:900913:20 445681 585687 286272 971165 EPSG:900913:21 891362 1171375 572545 1942331 EPSG:900913:22 1782724 2342750 1145090 3884662 EPSG:900913:23 3565448 4685501 2290180 7769325 EPSG:900913:24 7130896 9371002 4580360 15538650 EPSG:900913:25 14261793 18742005 9160720 31077301 EPSG:900913:26 28523587 37484011 18321440 62154602 EPSG:900913:27 57047174 74968023 36642880 124309204 EPSG:900913:28 114094349 149936046 73285761 248618408 EPSG:900913:29 228188699 299872092 146571522 497236816 EPSG:900913:30 456377398 599744184 293143045 994473632 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27855 36605 17892 60697 EPSG:3857:17 55710 73210 35784 121395 EPSG:3857:18 111420 146421 71568 242791 EPSG:3857:19 222840 292843 143136 485582 EPSG:3857:20 445681 585687 286272 971165 EPSG:3857:21 891362 1171375 572545 1942331 EPSG:3857:22 1782724 2342750 1145090 3884662 EPSG:3857:23 3565448 4685501 2290180 7769325 EPSG:3857:24 7130896 9371002 4580360 15538650 EPSG:3857:25 14261793 18742005 9160720 31077301 EPSG:3857:26 28523587 37484011 18321440 62154602 EPSG:3857:27 57047174 74968023 36642880 124309204 EPSG:3857:28 114094349 149936046 73285761 248618408 EPSG:3857:29 228188699 299872092 146571522 497236816 EPSG:3857:30 456377398 599744184 293143045 994473632 Combination Tropical cyclone surge/ Coral reefs at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_cor6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 indo_forint100 The forest integrrity index is derived by overlaying the human footprint (Venter et al. 2016) on the forest structural condition. The name is consistent with the concept of ecological integrity. Ecological integrity has been defined as, “the system’s capacity to maintain structure and ecosystem functions using processes and elements characteristic for its ecoregion.” (Parks Canada 2008). This capacity is a result of the climate, soil, topography, biota and other biophysical properties of the ecoregion and the extent to which these properties are not altered by modern human pressures. Consistent with this definition, the forest integrity index is based on on the structural complexity of a stand relative to the natural potential of the ecoregion and level of human pressure. Thus, forest of high integrity are relatively tall, high in canopy cover, older, and with relatively low human pressure. An increasing number of studies have shown that human pressure in various forms can have negative effects on native species. Thus, high integrity forests may be uniquely important for conservation because they support species and processes that are require well-developed forests and are sensitive to human activities. Such forests often also have high economic value and have likely been preferentially converted to more intense human land uses. Thus, identifying remaining areas of high forest integrity is important for conservation planning.<br><br>Data is provided by Montana State University.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> 100.0 -9.999861112471002 141.016129418236 23.384477504501 wesr_biodiversity:indo_forint100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 3 3 EPSG:3857:3 3 4 6 7 EPSG:3857:4 6 8 12 14 EPSG:3857:5 13 16 24 28 EPSG:3857:6 27 33 49 57 EPSG:3857:7 55 67 99 114 EPSG:3857:8 110 135 199 228 EPSG:3857:9 221 270 398 456 EPSG:3857:10 443 540 796 913 EPSG:3857:11 887 1081 1592 1826 EPSG:3857:12 1774 2162 3185 3652 EPSG:3857:13 3548 4324 6371 7304 EPSG:3857:14 7096 8649 12743 14609 EPSG:3857:15 14193 17298 25486 29219 EPSG:3857:16 28387 34597 50972 58439 EPSG:3857:17 56775 69195 101944 116878 EPSG:3857:18 113550 138390 203889 233756 EPSG:3857:19 227101 276781 407779 467513 EPSG:3857:20 454202 553563 815559 935027 EPSG:3857:21 908404 1107127 1631118 1870054 EPSG:3857:22 1816808 2214254 3262236 3740108 EPSG:3857:23 3633616 4428509 6524472 7480217 EPSG:3857:24 7267232 8857019 13048945 14960435 EPSG:3857:25 14534465 17714038 26097891 29920871 EPSG:3857:26 29068930 35428077 52195783 59841743 EPSG:3857:27 58137860 70856155 104391566 119683487 EPSG:3857:28 116275721 141712310 208783132 239366975 EPSG:3857:29 232551442 283424621 417566264 478733950 EPSG:3857:30 465102885 566849242 835132529 957467900 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 3 3 EPSG:4326:2 1 2 6 7 EPSG:4326:3 2 4 12 14 EPSG:4326:4 5 8 24 28 EPSG:4326:5 11 17 49 57 EPSG:4326:6 23 35 99 114 EPSG:4326:7 47 71 199 228 EPSG:4326:8 94 142 398 456 EPSG:4326:9 189 284 796 913 EPSG:4326:10 378 568 1592 1826 EPSG:4326:11 757 1137 3185 3652 EPSG:4326:12 1515 2275 6371 7304 EPSG:4326:13 3031 4551 12743 14609 EPSG:4326:14 6063 9102 25486 29219 EPSG:4326:15 12126 18204 50972 58439 EPSG:4326:16 24253 36408 101944 116878 EPSG:4326:17 48507 72817 203889 233756 EPSG:4326:18 97015 145635 407779 467513 EPSG:4326:19 194031 291270 815559 935027 EPSG:4326:20 388063 582541 1631118 1870054 EPSG:4326:21 776127 1165082 3262236 3740108 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 3 3 EPSG:3857:3 3 4 6 7 EPSG:3857:4 6 8 12 14 EPSG:3857:5 13 16 24 28 EPSG:3857:6 27 33 49 57 EPSG:3857:7 55 67 99 114 EPSG:3857:8 110 135 199 228 EPSG:3857:9 221 270 398 456 EPSG:3857:10 443 540 796 913 EPSG:3857:11 887 1081 1592 1826 EPSG:3857:12 1774 2162 3185 3652 EPSG:3857:13 3548 4324 6371 7304 EPSG:3857:14 7096 8649 12743 14609 EPSG:3857:15 14193 17298 25486 29219 EPSG:3857:16 28387 34597 50972 58439 EPSG:3857:17 56775 69195 101944 116878 EPSG:3857:18 113550 138390 203889 233756 EPSG:3857:19 227101 276781 407779 467513 EPSG:3857:20 454202 553563 815559 935027 EPSG:3857:21 908404 1107127 1631118 1870054 EPSG:3857:22 1816808 2214254 3262236 3740108 EPSG:3857:23 3633616 4428509 6524472 7480217 EPSG:3857:24 7267232 8857019 13048945 14960435 EPSG:3857:25 14534465 17714038 26097891 29920871 EPSG:3857:26 29068930 35428077 52195783 59841743 EPSG:3857:27 58137860 70856155 104391566 119683487 EPSG:3857:28 116275721 141712310 208783132 239366975 EPSG:3857:29 232551442 283424621 417566264 478733950 EPSG:3857:30 465102885 566849242 835132529 957467900 Combination Tsunami/Mangroves at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_man9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Annual Mean Temperature - Anomaly [°C] (2041-2060 vs 1979-2013) RCP4.5 - CIMP5 Anomaly [°C] for the period 2041-2060 compared to climatological data (1979-2013) on the mean annual daily mean air temperatures averaged over 1 year for the period 2041-2060 based on RCP4.5. The layer is calculated at UNEP/GRID-Geneva from the layers on annual precipitation [mm/year] provided in the products CHELSA V1.2 and CHELSA-[CMIP5]. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:Diff_CHELSA_bio_mon_ACCESS1-0_rcp45_r1i1p1_g025.nc_1_2041-2060_V12_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 population density 2015 gpw-v4 -180.0 -59.9999999999918 180.0 85.0000000000092 grid_data_core:gpw-v4-population-density-adjusted-to-2015-unwpp-country-totals_2015 image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 1 53 0 127 EPSG:4326:7 3 106 0 255 EPSG:4326:8 7 213 0 511 EPSG:4326:9 14 426 0 1023 EPSG:4326:10 28 853 0 2047 EPSG:4326:11 56 1706 0 4095 EPSG:4326:12 113 3413 0 8191 EPSG:4326:13 227 6826 0 16383 EPSG:4326:14 455 13653 0 32767 EPSG:4326:15 910 27306 0 65535 EPSG:4326:16 1820 54613 0 131071 EPSG:4326:17 3640 109226 0 262143 EPSG:4326:18 7281 218453 0 524287 EPSG:4326:19 14563 436906 0 1048575 EPSG:4326:20 29127 873813 0 2097151 EPSG:4326:21 58254 1747626 0 4194303 EPSG:900913 codemi 0.1675000015994978 11.697500041616369 16.000833334932196 23.52416670828256 risk_niger_undp:codemi image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 3 8 8 EPSG:4326:4 5 6 16 17 EPSG:4326:5 11 13 32 34 EPSG:4326:6 23 27 64 69 EPSG:4326:7 47 55 128 139 EPSG:4326:8 94 111 256 278 EPSG:4326:9 189 222 512 557 EPSG:4326:10 378 445 1024 1115 EPSG:4326:11 756 890 2049 2230 EPSG:4326:12 1512 1781 4099 4460 EPSG:4326:13 3025 3563 8199 8920 EPSG:4326:14 6050 7127 16399 17840 EPSG:4326:15 12101 14254 32798 35680 EPSG:4326:16 24203 28509 65596 71361 EPSG:4326:17 48406 57018 131193 142723 EPSG:4326:18 96812 114036 262387 285446 EPSG:4326:19 193624 228072 524775 570893 EPSG:4326:20 387249 456145 1049551 1141787 EPSG:4326:21 774499 912290 2099103 2283575 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 3 3 4 4 EPSG:900913:4 6 7 8 8 EPSG:900913:5 13 14 16 17 EPSG:900913:6 27 29 32 34 EPSG:900913:7 55 59 64 69 EPSG:900913:8 110 119 128 139 EPSG:900913:9 221 239 256 278 EPSG:900913:10 443 478 512 557 EPSG:900913:11 886 956 1024 1115 EPSG:900913:12 1772 1913 2049 2230 EPSG:900913:13 3544 3827 4099 4460 EPSG:900913:14 7089 7655 8199 8920 EPSG:900913:15 14179 15311 16399 17840 EPSG:900913:16 28359 30623 32798 35680 EPSG:900913:17 56719 61247 65596 71361 EPSG:900913:18 113439 122494 131193 142723 EPSG:900913:19 226879 244988 262387 285446 EPSG:900913:20 453758 489977 524775 570893 EPSG:900913:21 907517 979954 1049551 1141787 EPSG:900913:22 1815034 1959909 2099103 2283575 EPSG:900913:23 3630068 3919818 4198207 4567150 EPSG:900913:24 7260136 7839637 8396414 9134300 EPSG:900913:25 14520272 15679275 16792828 18268601 EPSG:900913:26 29040545 31358551 33585656 36537203 EPSG:900913:27 58081090 62717103 67171312 73074407 EPSG:900913:28 116162180 125434207 134342625 146148814 EPSG:900913:29 232324360 250868415 268685250 292297628 EPSG:900913:30 464648721 501736831 537370500 584595256 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 Combination Tropical cyclone/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcw_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 TZA_kilombero_BAU_LULC2030 34.553167266769464 -10.038048450490551 37.239835341004294 -7.663994368030097 TEEB:BAU_LULC2030_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 19 19 EPSG:4326:5 17 17 38 38 EPSG:4326:6 34 35 76 77 EPSG:4326:7 69 71 152 154 EPSG:4326:8 138 142 305 308 EPSG:4326:9 277 284 610 617 EPSG:4326:10 555 569 1220 1235 EPSG:4326:11 1111 1138 2441 2471 EPSG:4326:12 2222 2276 4882 4943 EPSG:4326:13 4444 4552 9764 9886 EPSG:4326:14 8889 9105 19529 19773 EPSG:4326:15 17779 18211 39058 39547 EPSG:4326:16 35558 36422 78116 79094 EPSG:4326:17 71116 72845 156232 158189 EPSG:4326:18 142233 145690 312465 316378 EPSG:4326:19 284467 291381 624931 632756 EPSG:4326:20 568934 582763 1249862 1265513 EPSG:4326:21 1137868 1165527 2499725 2531027 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 Mangroves total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:mangrokm2a_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Soil Erodibility (K- Factor) - GloSEM_25km - ESDAC - JRC The soil Erodibility (K-Factor) is one of the input layers used in the Global Soil Erosion map (GeoTIFF format) at 25km resolution is available for free download in the European Soil Data Centre (ESDAC). This is based on the Verion 1.1 of the JRC/ UniBasel "RUSLE-based Global Soil Erosion Modelling platform (GloSEM)". In addition to the K-factor, GloSEM provides the other 25km resolution resampled input datasets: * R-factor (the original one at 1km can be downloaded from https://esdac.jrc.ec.europa.eu/content/global-rainfall-erosivity * C-factor * LS-factor and the RUSLE outputs: - RUSLE Soil loss in 2012 (25km resolution) - RUSLE Soil loss in 2001 (25km resolution) Note: In case you use the data for applications in European Union, we recommend the European Soil Erosion dataset and the relevant K, LS, C, R, P factors. References Borrelli P., Robinson D.A., Fleischer L.R., Lugato E., Ballabio C., Alewell C., Meusburger K., Modugno, S., Schutt, B. Ferro, V. Bagarello, V. Van Oost, K., Montanarella, L., Panagos P. 2017. An assessment of the global impact of 21st century land use change on soil erosion. Nature Communications, 8 (1): art. no. 2013 -180.0 -56.6229166666667 179.99999999999943 83.58541666666642 UN_Sahel:RUSLE_KFactor_v1.1_25km image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 177 0 255 EPSG:3857:9 21 354 0 511 EPSG:3857:10 42 708 0 1023 EPSG:3857:11 84 1416 0 2047 EPSG:3857:12 169 2833 0 4095 EPSG:3857:13 338 5666 0 8191 EPSG:3857:14 677 11333 0 16383 EPSG:3857:15 1355 22666 0 32767 EPSG:3857:16 2710 45332 0 65535 EPSG:3857:17 5420 90665 0 131071 EPSG:3857:18 10840 181331 0 262143 EPSG:3857:19 21681 362663 0 524287 EPSG:3857:20 43363 725327 0 1048575 EPSG:3857:21 86726 1450655 0 2097151 EPSG:3857:22 173453 2901310 0 4194304 EPSG:3857:23 346906 5802620 0 8388608 EPSG:3857:24 693812 11605241 0 16777215 EPSG:3857:25 1387625 23210482 0 33554431 EPSG:3857:26 2775251 46420964 0 67108863 EPSG:3857:27 5550503 92841928 0 134217727 EPSG:3857:28 11101006 185683856 0 268435456 EPSG:3857:29 22202013 371367713 0 536870911 EPSG:3857:30 44404027 742735427 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 52 0 127 EPSG:4326:7 4 104 0 255 EPSG:4326:8 9 208 0 511 EPSG:4326:9 18 417 0 1023 EPSG:4326:10 36 834 0 2047 EPSG:4326:11 72 1668 0 4095 EPSG:4326:12 145 3336 0 8191 EPSG:4326:13 291 6672 0 16383 EPSG:4326:14 583 13345 0 32767 EPSG:4326:15 1167 26691 0 65535 EPSG:4326:16 2335 53383 0 131071 EPSG:4326:17 4670 106767 0 262143 EPSG:4326:18 9341 213535 0 524287 EPSG:4326:19 18683 427070 0 1048575 EPSG:4326:20 37367 854140 0 2097151 EPSG:4326:21 74735 1708280 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 177 0 255 EPSG:3857:9 21 354 0 511 EPSG:3857:10 42 708 0 1023 EPSG:3857:11 84 1416 0 2047 EPSG:3857:12 169 2833 0 4095 EPSG:3857:13 338 5666 0 8191 EPSG:3857:14 677 11333 0 16383 EPSG:3857:15 1355 22666 0 32767 EPSG:3857:16 2710 45332 0 65535 EPSG:3857:17 5420 90665 0 131071 EPSG:3857:18 10840 181331 0 262143 EPSG:3857:19 21681 362663 0 524287 EPSG:3857:20 43363 725327 0 1048575 EPSG:3857:21 86726 1450655 0 2097152 EPSG:3857:22 173453 2901310 0 4194304 EPSG:3857:23 346906 5802620 0 8388607 EPSG:3857:24 693812 11605241 0 16777215 EPSG:3857:25 1387625 23210482 0 33554431 EPSG:3857:26 2775251 46420964 0 67108863 EPSG:3857:27 5550503 92841928 0 134217728 EPSG:3857:28 11101006 185683856 0 268435455 EPSG:3857:29 22202013 371367713 0 536870911 EPSG:3857:30 44404027 742735427 0 1073741824 Average year temperature anomalies (2001-2010) over 1991-2020 climatology Average year temperature anomalies in °Celsius across the period 2001-2010 calculated over the average temperatures per year in the period 1991-2020 (climatology). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_01_10_anom9120 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_mambo_bado_20200515 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20200515 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 Tropical Cyclones Mortality Risk This dataset includes an estimate of the global risk induced by tropical cyclone hazard. Unit is estimated risk index from 1 (low) to 5 (extreme). This product was designed by UNEP/GRID-Geneva for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: UNEP/GRID-Geneva. -180.0 -90.0 179.99999999985602 83.99999999993042 wesr_risk:cy_risk image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097151 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388608 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217727 EPSG:3857:28 8240909 268435455 0 268435456 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34952 1048575 0 2097151 EPSG:4326:21 69905 2097151 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097152 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388607 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217728 EPSG:3857:28 8240909 268435455 0 268435455 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741824 Satellite Mogadisho Urban Growth 2014 Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2014-06-16. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov. 45.19537208608339 1.9551716669929171 45.47928595286078 2.1415394320566414 MAPX:Mogadisho_Landsat7_20140616-531 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 10 10 EPSG:3857:5 15 15 20 20 EPSG:3857:6 31 31 40 40 EPSG:3857:7 63 63 80 80 EPSG:3857:8 126 126 160 160 EPSG:3857:9 252 253 320 320 EPSG:3857:10 505 506 640 641 EPSG:3857:11 1011 1012 1281 1282 EPSG:3857:12 2023 2025 2562 2565 EPSG:3857:13 4047 4051 5124 5130 EPSG:3857:14 8094 8103 10248 10261 EPSG:3857:15 16189 16206 20497 20523 EPSG:3857:16 32378 32412 40995 41047 EPSG:3857:17 64756 64824 81991 82094 EPSG:3857:18 129512 129648 163982 164189 EPSG:3857:19 259024 259296 327964 328378 EPSG:3857:20 518048 518592 655929 656756 EPSG:3857:21 1036097 1037184 1311858 1313512 EPSG:3857:22 2072195 2074368 2623716 2627024 EPSG:3857:23 4144390 4148736 5247432 5254048 EPSG:3857:24 8288781 8297472 10494864 10508096 EPSG:3857:25 16577563 16594945 20989729 21016192 EPSG:3857:26 33155127 33189890 41979459 42032385 EPSG:3857:27 66310254 66379781 83958919 84064770 EPSG:3857:28 132620508 132759563 167917839 168129541 EPSG:3857:29 265241017 265519126 335835679 336259083 EPSG:3857:30 530482034 531038253 671671359 672518166 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 10 10 EPSG:4326:4 7 7 20 20 EPSG:4326:5 15 15 40 40 EPSG:4326:6 31 31 80 80 EPSG:4326:7 62 62 160 160 EPSG:4326:8 124 125 320 320 EPSG:4326:9 249 250 640 641 EPSG:4326:10 499 500 1281 1282 EPSG:4326:11 999 1001 2562 2565 EPSG:4326:12 1999 2003 5124 5130 EPSG:4326:13 3998 4007 10248 10261 EPSG:4326:14 7997 8014 20497 20523 EPSG:4326:15 15994 16028 40995 41047 EPSG:4326:16 31988 32056 81991 82094 EPSG:4326:17 63976 64112 163982 164189 EPSG:4326:18 127953 128224 327964 328378 EPSG:4326:19 255906 256449 655929 656756 EPSG:4326:20 511812 512898 1311858 1313512 EPSG:4326:21 1023625 1025796 2623716 2627024 EPSG:900913 Nutrient Pollution (fertilizers) 2008 - KNB Input data are from FAO statistics published in the time period 2003-2006. FAO data on annual country-level fertilizer were used were available, averaged over the time periods. Missing values were filled using a linear regression model of fertilizers as a function of pesticides (gaps: N=4; regression: R2 = 0.72) when pesticide data were available or agricultural GDP (gaps: N=22; regression: R2 = 0.62) when not. These country-level average fertilizer values were then dasymetrically distributed over a country’s landscape using global land cover data from 2005. Finally, spread of the driver values into coastal waters at each pour point was modelled with a cost-path surface on the basis of a decay function that assigns a fixed amount of the driver (0.5% of the value in the previous cell) in the initial cell and then evenly distributes the remaining amount of driver in all adjacent and ‘unvisited’ cells, repeated until a minimum threshold (0.05% of global maximum) is reached. This approach to modelling river plumes is diffusive and so allows drivers to wrap around headlands and islands. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS." -179.99999948447567 -57.923325435334434 179.99443435918158 84.90643464931345 unea_pollution:08_plumes_fert_halpern_KNB_WGS84 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 44 0 63 EPSG:3857:7 0 89 0 127 EPSG:3857:8 1 178 0 255 EPSG:3857:9 2 357 0 511 EPSG:3857:10 4 715 0 1023 EPSG:3857:11 9 1430 0 2047 EPSG:3857:12 18 2860 0 4095 EPSG:3857:13 37 5721 0 8191 EPSG:3857:14 75 11442 0 16383 EPSG:3857:15 150 22885 0 32767 EPSG:3857:16 300 45770 0 65534 EPSG:3857:17 601 91541 0 131069 EPSG:3857:18 1203 183083 0 262139 EPSG:3857:19 2407 366167 0 524279 EPSG:3857:20 4815 732334 0 1048559 EPSG:3857:21 9631 1464668 0 2097119 EPSG:3857:22 19262 2929337 0 4194239 EPSG:3857:23 38524 5858675 0 8388478 EPSG:3857:24 77049 11717351 0 16776956 EPSG:3857:25 154098 23434703 0 33553913 EPSG:3857:26 308196 46869407 0 67107826 EPSG:3857:27 616393 93738815 0 134215652 EPSG:3857:28 1232786 187477630 0 268431305 EPSG:3857:29 2465573 374955260 0 536862611 EPSG:3857:30 4931146 749910520 1 1073725223 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 1 52 0 127 EPSG:4326:7 3 105 0 255 EPSG:4326:8 7 210 0 511 EPSG:4326:9 14 420 0 1023 EPSG:4326:10 28 841 0 2047 EPSG:4326:11 57 1683 0 4095 EPSG:4326:12 115 3366 0 8191 EPSG:4326:13 231 6732 0 16383 EPSG:4326:14 463 13464 0 32767 EPSG:4326:15 927 26928 0 65534 EPSG:4326:16 1854 53857 0 131069 EPSG:4326:17 3709 107714 0 262139 EPSG:4326:18 7418 215428 0 524279 EPSG:4326:19 14836 430857 0 1048559 EPSG:4326:20 29672 861715 0 2097119 EPSG:4326:21 59344 1723431 0 4194239 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 22 0 31 EPSG:900913:6 0 44 0 63 EPSG:900913:7 0 89 0 127 EPSG:900913:8 1 178 0 255 EPSG:900913:9 2 357 0 511 EPSG:900913:10 4 715 0 1023 EPSG:900913:11 9 1430 0 2047 EPSG:900913:12 18 2860 0 4095 EPSG:900913:13 37 5721 0 8191 EPSG:900913:14 75 11442 0 16383 EPSG:900913:15 150 22885 0 32767 EPSG:900913:16 300 45770 0 65534 EPSG:900913:17 601 91541 0 131069 EPSG:900913:18 1203 183083 0 262139 EPSG:900913:19 2407 366167 0 524279 EPSG:900913:20 4815 732334 0 1048559 EPSG:900913:21 9631 1464668 0 2097119 EPSG:900913:22 19262 2929337 0 4194239 EPSG:900913:23 38524 5858675 0 8388478 EPSG:900913:24 77049 11717351 0 16776956 EPSG:900913:25 154098 23434703 0 33553913 EPSG:900913:26 308196 46869407 0 67107826 EPSG:900913:27 616393 93738815 0 134215652 EPSG:900913:28 1232786 187477630 0 268431305 EPSG:900913:29 2465573 374955260 0 536862611 EPSG:900913:30 4931146 749910520 1 1073725223 Average year precipitations (2011-2020) Average year precipitations in mm across the period 2011-2020. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_11_20_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 frac_cats_2019_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_2019_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Combination Tsunami/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 hfp2000_meris_wgs Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11 -179.99997804642848 -65.24741434935741 180.0 89.8976232152096 MapX_UNDP_nd:hfp2000_meris_wgs image/png image/vnd.jpeg-png image/jpeg image/png8 EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12146 0 16383 EPSG:3857:15 0 24293 0 32767 EPSG:3857:16 0 48587 0 65535 EPSG:3857:17 0 97175 0 131071 EPSG:3857:18 0 194351 0 262143 EPSG:3857:19 0 388703 0 524287 EPSG:3857:20 0 777407 0 1048575 EPSG:3857:21 0 1554814 0 2097151 EPSG:3857:22 -1 3109629 0 4194304 EPSG:3857:23 -1 6219258 0 8388608 EPSG:3857:24 0 12438517 1 16777215 EPSG:3857:25 0 24877035 2 33554431 EPSG:3857:26 0 49754070 4 67108863 EPSG:3857:27 0 99508140 8 134217727 EPSG:3857:28 -1 199016280 16 268435456 EPSG:3857:29 0 398032561 32 536870911 EPSG:3857:30 0 796065123 65 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 55 0 127 EPSG:4326:7 0 110 0 255 EPSG:4326:8 0 220 0 511 EPSG:4326:9 0 441 0 1023 EPSG:4326:10 0 883 0 2047 EPSG:4326:11 1 1766 0 4095 EPSG:4326:12 2 3532 0 8191 EPSG:4326:13 4 7065 0 16383 EPSG:4326:14 9 14130 0 32767 EPSG:4326:15 18 28261 0 65535 EPSG:4326:16 37 56523 0 131071 EPSG:4326:17 74 113047 0 262143 EPSG:4326:18 149 226095 0 524287 EPSG:4326:19 298 452190 0 1048575 EPSG:4326:20 596 904381 0 2097151 EPSG:4326:21 1192 1808763 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 23 0 31 EPSG:900913:6 0 47 0 63 EPSG:900913:7 0 94 0 127 EPSG:900913:8 0 189 0 255 EPSG:900913:9 0 379 0 511 EPSG:900913:10 0 759 0 1023 EPSG:900913:11 0 1518 0 2047 EPSG:900913:12 0 3036 0 4095 EPSG:900913:13 0 6073 0 8191 EPSG:900913:14 0 12146 0 16383 EPSG:900913:15 0 24293 0 32767 EPSG:900913:16 0 48587 0 65535 EPSG:900913:17 0 97175 0 131071 EPSG:900913:18 0 194351 0 262143 EPSG:900913:19 0 388703 0 524287 EPSG:900913:20 0 777407 0 1048575 EPSG:900913:21 0 1554814 0 2097151 EPSG:900913:22 0 3109629 0 4194303 EPSG:900913:23 0 6219258 0 8388607 EPSG:900913:24 0 12438517 1 16777215 EPSG:900913:25 0 24877035 2 33554431 EPSG:900913:26 0 49754070 4 67108863 EPSG:900913:27 0 99508140 8 134217727 EPSG:900913:28 0 199016280 16 268435455 EPSG:900913:29 0 398032561 32 536870911 EPSG:900913:30 0 796065123 65 1073741823 Mean temperatures 2010 - Central African Republic Mean observed temperatures in 2010 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2010_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Landslide hazard frequency -180.0 -90.0 180.0 90.0 ECO-DRR:ls_freq2af image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Historical Land Cover of emerging Northwest Mining Region of Ghana (2000) This shows a decade landscape perspective of the emerging Northwest mining region after the Rio De Jeneiro Conference on Sustainable Development with a focus on environmental resources. This data would highlight the appreciable contributions of illegal mining and the begining of large-scale exploration activities in the area. The trends and patterns of these actitivities' interactions with biodiversity can be observed and monitored for impact remediation in the area. The environmental responsiveness and mining generating carbon stock concentrations can be monitored as well. The activities of illegal mining in relation to the environment, water and vegetation can be tracked and regulated. -2.941942292 9.62626436 -1.427242947 11.030913256 MAPX:GHA_LULC2000 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245978 248058 257859 260065 EPSG:3857:20 491957 496116 515718 520130 EPSG:3857:21 983915 992233 1031437 1040261 EPSG:3857:22 1967831 1984466 2062875 2080523 EPSG:3857:23 3935662 3968933 4125751 4161046 EPSG:3857:24 7871324 7937866 8251503 8322093 EPSG:3857:25 15742649 15875732 16503007 16644187 EPSG:3857:26 31485298 31751464 33006014 33288374 EPSG:3857:27 62970596 63502928 66012028 66576749 EPSG:3857:28 125941193 127005856 132024056 133153498 EPSG:3857:29 251882387 254011712 264048113 266306997 EPSG:3857:30 503764775 508023424 528096227 532613994 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1828 4029 4063 EPSG:4326:13 3593 3657 8058 8127 EPSG:4326:14 7187 7315 16116 16254 EPSG:4326:15 14375 14631 32232 32508 EPSG:4326:16 28751 29263 64464 65016 EPSG:4326:17 57503 58526 128929 130032 EPSG:4326:18 115007 117052 257859 260065 EPSG:4326:19 230014 234105 515718 520130 EPSG:4326:20 460028 468210 1031437 1040261 EPSG:4326:21 920056 936421 2062875 2080523 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245978 248058 257859 260065 EPSG:3857:20 491957 496116 515718 520130 EPSG:3857:21 983915 992233 1031437 1040261 EPSG:3857:22 1967831 1984466 2062875 2080523 EPSG:3857:23 3935662 3968933 4125751 4161046 EPSG:3857:24 7871324 7937866 8251503 8322093 EPSG:3857:25 15742649 15875732 16503007 16644187 EPSG:3857:26 31485298 31751464 33006014 33288374 EPSG:3857:27 62970596 63502928 66012028 66576749 EPSG:3857:28 125941193 127005856 132024056 133153498 EPSG:3857:29 251882387 254011712 264048113 266306997 EPSG:3857:30 503764775 508023424 528096227 532613994 K1-KAPOS -179.99998890825066 -55.90638888888891 180.0 83.32902777777751 wesr_mountains:K1-KAPOS image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 3 44 0 63 EPSG:3857:7 6 88 0 127 EPSG:3857:8 12 176 0 255 EPSG:3857:9 24 352 0 511 EPSG:3857:10 48 704 0 1023 EPSG:3857:11 97 1409 0 2047 EPSG:3857:12 194 2818 0 4095 EPSG:3857:13 389 5637 0 8191 EPSG:3857:14 779 11274 0 16383 EPSG:3857:15 1559 22549 0 32767 EPSG:3857:16 3119 45098 0 65535 EPSG:3857:17 6239 90196 0 131071 EPSG:3857:18 12479 180392 0 262143 EPSG:3857:19 24959 360784 0 524287 EPSG:3857:20 49918 721569 0 1048575 EPSG:3857:21 99836 1443138 0 2097151 EPSG:3857:22 199672 2886277 0 4194304 EPSG:3857:23 399344 5772555 0 8388608 EPSG:3857:24 798689 11545110 0 16777215 EPSG:3857:25 1597378 23090221 1 33554431 EPSG:3857:26 3194756 46180443 2 67108863 EPSG:3857:27 6389512 92360886 4 134217727 EPSG:3857:28 12779025 184721772 8 268435456 EPSG:3857:29 25558051 369443544 16 536870911 EPSG:3857:30 51116102 738887089 33 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 4 103 0 255 EPSG:4326:8 9 207 0 511 EPSG:4326:9 18 415 0 1023 EPSG:4326:10 37 830 0 2047 EPSG:4326:11 75 1660 0 4095 EPSG:4326:12 151 3320 0 8191 EPSG:4326:13 303 6640 0 16383 EPSG:4326:14 607 13280 0 32767 EPSG:4326:15 1214 26561 0 65535 EPSG:4326:16 2428 53122 0 131071 EPSG:4326:17 4857 106245 0 262143 EPSG:4326:18 9715 212491 0 524287 EPSG:4326:19 19430 424983 0 1048575 EPSG:4326:20 38861 849966 0 2097151 EPSG:4326:21 77722 1699932 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 3 44 0 63 EPSG:3857:7 6 88 0 127 EPSG:3857:8 12 176 0 255 EPSG:3857:9 24 352 0 511 EPSG:3857:10 48 704 0 1023 EPSG:3857:11 97 1409 0 2047 EPSG:3857:12 194 2818 0 4095 EPSG:3857:13 389 5637 0 8191 EPSG:3857:14 779 11274 0 16383 EPSG:3857:15 1559 22549 0 32767 EPSG:3857:16 3119 45098 0 65535 EPSG:3857:17 6239 90196 0 131071 EPSG:3857:18 12479 180392 0 262143 EPSG:3857:19 24959 360784 0 524287 EPSG:3857:20 49918 721569 0 1048575 EPSG:3857:21 99836 1443138 0 2097152 EPSG:3857:22 199672 2886277 0 4194304 EPSG:3857:23 399344 5772555 0 8388607 EPSG:3857:24 798689 11545110 0 16777215 EPSG:3857:25 1597378 23090221 1 33554431 EPSG:3857:26 3194756 46180443 2 67108863 EPSG:3857:27 6389512 92360886 4 134217728 EPSG:3857:28 12779025 184721772 8 268435455 EPSG:3857:29 25558051 369443544 16 536870911 EPSG:3857:30 51116102 738887089 33 1073741824 Combination Tropical cyclone surge/ Coral reefs at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_cor9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Tropical cyclone hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:cy_phex image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Spectral Acceleration 1.0 Sec 250 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_10_s_250_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 171208_Zambia_Mantapala_Contours_etc 28.834857143 -9.630294321 28.907962887 -9.495541302 MAPX:171208_Zambia_Mantapala_Contours_etc image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 33 33 37 37 EPSG:3857:7 67 67 74 74 EPSG:3857:8 134 134 148 148 EPSG:3857:9 269 269 297 297 EPSG:3857:10 539 539 594 594 EPSG:3857:11 1078 1079 1188 1188 EPSG:3857:12 2156 2158 2376 2376 EPSG:3857:13 4313 4316 4752 4753 EPSG:3857:14 8626 8632 9504 9507 EPSG:3857:15 17252 17264 19008 19015 EPSG:3857:16 34504 34529 38017 38030 EPSG:3857:17 69009 69058 76034 76061 EPSG:3857:18 138018 138117 152068 152122 EPSG:3857:19 276036 276235 304137 304244 EPSG:3857:20 552073 552471 608275 608488 EPSG:3857:21 1104146 1104942 1216551 1216977 EPSG:3857:22 2208293 2209885 2433102 2433954 EPSG:3857:23 4416586 4419770 4866204 4867908 EPSG:3857:24 8833172 8839540 9732409 9735816 EPSG:3857:25 17666344 17679080 19464819 19471633 EPSG:3857:26 35332688 35358161 38929638 38943266 EPSG:3857:27 70665376 70716323 77859277 77886533 EPSG:3857:28 141330752 141432647 155718555 155773067 EPSG:3857:29 282661505 282865295 311437111 311546134 EPSG:3857:30 565323010 565730591 622874223 623092269 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 17 17 37 37 EPSG:4326:6 35 35 74 74 EPSG:4326:7 70 70 148 148 EPSG:4326:8 141 141 297 297 EPSG:4326:9 283 283 594 594 EPSG:4326:10 566 566 1188 1188 EPSG:4326:11 1132 1133 2376 2376 EPSG:4326:12 2264 2267 4752 4753 EPSG:4326:13 4528 4534 9504 9507 EPSG:4326:14 9056 9068 19008 19015 EPSG:4326:15 18112 18137 38017 38030 EPSG:4326:16 36225 36274 76034 76061 EPSG:4326:17 72450 72548 152068 152122 EPSG:4326:18 144900 145097 304137 304244 EPSG:4326:19 289801 290194 608275 608488 EPSG:4326:20 579603 580388 1216551 1216977 EPSG:4326:21 1159207 1160777 2433102 2433954 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 33 33 37 37 EPSG:3857:7 67 67 74 74 EPSG:3857:8 134 134 148 148 EPSG:3857:9 269 269 297 297 EPSG:3857:10 539 539 594 594 EPSG:3857:11 1078 1079 1188 1188 EPSG:3857:12 2156 2158 2376 2376 EPSG:3857:13 4313 4316 4752 4753 EPSG:3857:14 8626 8632 9504 9507 EPSG:3857:15 17252 17264 19008 19015 EPSG:3857:16 34504 34529 38017 38030 EPSG:3857:17 69009 69058 76034 76061 EPSG:3857:18 138018 138117 152068 152122 EPSG:3857:19 276036 276235 304137 304244 EPSG:3857:20 552073 552471 608275 608488 EPSG:3857:21 1104146 1104942 1216551 1216977 EPSG:3857:22 2208293 2209885 2433102 2433954 EPSG:3857:23 4416586 4419770 4866204 4867908 EPSG:3857:24 8833172 8839540 9732409 9735816 EPSG:3857:25 17666344 17679080 19464819 19471633 EPSG:3857:26 35332688 35358161 38929638 38943266 EPSG:3857:27 70665376 70716323 77859277 77886533 EPSG:3857:28 141330752 141432647 155718555 155773067 EPSG:3857:29 282661505 282865295 311437111 311546134 EPSG:3857:30 565323010 565730591 622874223 623092269 Combination Landslide/Forest at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_lds_for9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_mambo_bado_20210311 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20210311 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 frac_cats_2021_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_2021_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 sites_0016_0028_2 32.60687054879944 0.021034505865 105.74039483165862 12.481090912222495 hotspots:sites_0016_0028_2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 3 EPSG:3857:3 3 3 4 6 EPSG:3857:4 7 7 9 12 EPSG:3857:5 14 15 18 25 EPSG:3857:6 29 31 37 50 EPSG:3857:7 59 63 75 101 EPSG:3857:8 119 127 151 203 EPSG:3857:9 238 255 302 406 EPSG:3857:10 476 511 604 812 EPSG:3857:11 952 1023 1209 1625 EPSG:3857:12 1904 2047 2418 3251 EPSG:3857:13 3809 4095 4837 6502 EPSG:3857:14 7619 8191 9675 13004 EPSG:3857:15 15238 16382 19351 26008 EPSG:3857:16 30477 32764 38703 52017 EPSG:3857:17 60955 65528 77407 104034 EPSG:3857:18 121910 131056 154815 208069 EPSG:3857:19 243821 262113 309631 416139 EPSG:3857:20 487643 524226 619262 832279 EPSG:3857:21 975286 1048453 1238524 1664558 EPSG:3857:22 1950572 2096906 2477049 3329116 EPSG:3857:23 3901145 4193813 4954099 6658233 EPSG:3857:24 7802291 8387627 9908198 13316467 EPSG:3857:25 15604582 16775255 19816396 26632935 EPSG:3857:26 31209165 33550510 39632793 53265870 EPSG:3857:27 62418331 67101021 79265586 106531740 EPSG:3857:28 124836663 134202043 158531172 213063481 EPSG:3857:29 249673326 268404087 317062345 426126962 EPSG:3857:30 499346652 536808174 634124691 852253924 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 3 EPSG:4326:2 1 1 4 6 EPSG:4326:3 3 3 9 12 EPSG:4326:4 6 7 18 25 EPSG:4326:5 13 15 37 50 EPSG:4326:6 27 31 75 101 EPSG:4326:7 55 63 151 203 EPSG:4326:8 110 127 302 406 EPSG:4326:9 220 255 604 812 EPSG:4326:10 440 511 1209 1625 EPSG:4326:11 881 1023 2418 3251 EPSG:4326:12 1763 2047 4837 6502 EPSG:4326:13 3527 4095 9675 13004 EPSG:4326:14 7055 8190 19351 26008 EPSG:4326:15 14111 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3329116 EPSG:3857:23 3901145 4193813 4954099 6658233 EPSG:3857:24 7802291 8387627 9908198 13316467 EPSG:3857:25 15604582 16775255 19816396 26632935 EPSG:3857:26 31209165 33550510 39632793 53265870 EPSG:3857:27 62418331 67101021 79265586 106531740 EPSG:3857:28 124836663 134202043 158531172 213063481 EPSG:3857:29 249673326 268404087 317062345 426126962 EPSG:3857:30 499346652 536808174 634124691 852253924 Precipitation averages (mm) 1986-2005 (RCP8.5) Yearly precipitation averages in the reference period 1986-2005 based on the climate scenario RCP8.5. -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:pr_85_86_05 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 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37212187 EPSG:3857:27 48135316 49543465 72972960 74424375 EPSG:3857:28 96270632 99086930 145945920 148848751 EPSG:3857:29 192541264 198173860 291891841 297697503 EPSG:3857:30 385082528 396347721 583783682 595395007 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 0 1 4 4 EPSG:4326:3 1 2 8 8 EPSG:4326:4 3 4 17 17 EPSG:4326:5 7 8 34 35 EPSG:4326:6 15 16 69 70 EPSG:4326:7 31 33 139 141 EPSG:4326:8 63 67 278 283 EPSG:4326:9 127 134 556 567 EPSG:4326:10 254 269 1113 1135 EPSG:4326:11 508 539 2226 2271 EPSG:4326:12 1017 1079 4453 4542 EPSG:4326:13 2035 2159 8907 9085 EPSG:4326:14 4070 4318 17815 18170 EPSG:4326:15 8141 8636 35631 36340 EPSG:4326:16 16283 17273 71262 72680 EPSG:4326:17 32566 34547 142525 145360 EPSG:4326:18 65133 69094 285050 290720 EPSG:4326:19 130266 138189 570101 581440 EPSG:4326:20 260533 276378 1140202 1162880 EPSG:4326:21 521066 552756 2280405 2325761 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 2 2 4 4 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291891841 297697503 EPSG:900913:30 385082528 396347721 583783682 595395007 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 2 4 4 EPSG:3857:4 5 5 8 8 EPSG:3857:5 11 11 17 17 EPSG:3857:6 22 23 34 35 EPSG:3857:7 45 47 69 70 EPSG:3857:8 91 94 139 141 EPSG:3857:9 183 188 278 283 EPSG:3857:10 367 377 556 567 EPSG:3857:11 734 755 1113 1135 EPSG:3857:12 1468 1511 2226 2271 EPSG:3857:13 2937 3023 4453 4542 EPSG:3857:14 5875 6047 8907 9085 EPSG:3857:15 11751 12095 17815 18170 EPSG:3857:16 23503 24191 35631 36340 EPSG:3857:17 47007 48382 71262 72680 EPSG:3857:18 94014 96764 142525 145360 EPSG:3857:19 188028 193529 285050 290720 EPSG:3857:20 376057 387058 570101 581440 EPSG:3857:21 752114 774116 1140202 1162880 EPSG:3857:22 1504228 1548233 2280405 2325761 EPSG:3857:23 3008457 3096466 4560810 4651523 EPSG:3857:24 6016914 6192933 9121620 9303046 EPSG:3857:25 12033829 12385866 18243240 18606093 EPSG:3857:26 24067658 24771732 36486480 37212187 EPSG:3857:27 48135316 49543465 72972960 74424375 EPSG:3857:28 96270632 99086930 145945920 148848751 EPSG:3857:29 192541264 198173860 291891841 297697503 EPSG:3857:30 385082528 396347721 583783682 595395007 Self-calibrating Palmer Drought Severity Index (scPDSI) 1961-1970 (CRU) This layer shows the average values over the 1961 to 1970 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_61_70_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 eth_wb_buffer_100m 33.00029156227385 3.4089243300132126 47.276572438492494 14.866325792845133 mapx_chemobs:eth_wb_buffer_100m image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 5 EPSG:3857:4 7 7 9 10 EPSG:3857:5 14 15 18 20 EPSG:3857:6 29 31 37 40 EPSG:3857:7 58 62 75 80 EPSG:3857:8 117 125 151 161 EPSG:3857:9 234 251 302 323 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EPSG:3857:15 15015 16073 19387 20687 EPSG:3857:16 30030 32147 38775 41374 EPSG:3857:17 60061 64294 77551 82748 EPSG:3857:18 120123 128588 155102 165497 EPSG:3857:19 240246 257176 310204 330995 EPSG:3857:20 480492 514352 620408 661990 EPSG:3857:21 960984 1028705 1240816 1323981 EPSG:3857:22 1921969 2057411 2481633 2647963 EPSG:3857:23 3843939 4114823 4963266 5295927 EPSG:3857:24 7687879 8229646 9926533 10591855 EPSG:3857:25 15375759 16459293 19853066 21183711 EPSG:3857:26 30751519 32918587 39706132 42367423 EPSG:3857:27 61503038 65837174 79412264 84734847 EPSG:3857:28 123006076 131674348 158824528 169469695 EPSG:3857:29 246012152 263348697 317649057 338939390 EPSG:3857:30 492024305 526697395 635298115 677878781 site_0336_20010128_enhanced 21.804453393351142 2.163950346428799 22.972377367092143 3.360478793316272 hotspots:site_0336_20010128_enhanced image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml 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131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 15 15 35 36 EPSG:4326:6 30 31 71 72 EPSG:4326:7 61 62 143 144 EPSG:4326:8 123 124 287 288 EPSG:4326:9 246 249 574 577 EPSG:4326:10 492 499 1148 1154 EPSG:4326:11 985 999 2296 2309 EPSG:4326:12 1971 1998 4592 4618 EPSG:4326:13 3943 3997 9184 9237 EPSG:4326:14 7886 7995 18368 18474 EPSG:4326:15 15772 15990 36737 36949 EPSG:4326:16 31544 31980 73474 73899 EPSG:4326:17 63088 63960 146949 147799 EPSG:4326:18 126177 127920 293899 295599 EPSG:4326:19 252355 255841 587798 591199 EPSG:4326:20 504711 511682 1175596 1182399 EPSG:4326:21 1009423 1023364 2351192 2364799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 Combination Tropical cyclone/Forest at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcw_for9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mean temperatures 2003 - Central African Republic Mean observed temperatures in 2003 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2003_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Ba200804 0.166015625 11.6953125 15.995117188 23.525390625 MAPX:Ba200804 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1114 EPSG:3857:12 1772 1913 2049 2229 EPSG:3857:13 3544 3827 4099 4459 EPSG:3857:14 7089 7655 8199 8919 EPSG:3857:15 14179 15311 16399 17839 EPSG:3857:16 28359 30623 32798 35679 EPSG:3857:17 56719 61247 65596 71359 EPSG:3857:18 113438 122495 131192 142719 EPSG:3857:19 226877 244991 262385 285438 EPSG:3857:20 453754 489983 524771 570877 EPSG:3857:21 907509 979967 1049543 1141754 EPSG:3857:22 1815018 1959935 2099086 2283508 EPSG:3857:23 3630037 3919871 4198172 4567017 EPSG:3857:24 7260074 7839742 8396344 9134034 EPSG:3857:25 14520148 15679484 16792689 18268068 EPSG:3857:26 29040296 31358968 33585379 36536137 EPSG:3857:27 58080592 62717936 67170759 73072275 EPSG:3857:28 116161185 125435873 134341518 146144551 EPSG:3857:29 232322370 250871747 268683036 292289103 EPSG:3857:30 464644740 501743494 537366072 584578207 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 3 8 8 EPSG:4326:4 5 6 16 17 EPSG:4326:5 11 13 32 34 EPSG:4326:6 23 27 64 69 EPSG:4326:7 47 55 128 139 EPSG:4326:8 94 111 256 278 EPSG:4326:9 189 222 512 557 EPSG:4326:10 378 445 1024 1114 EPSG:4326:11 756 890 2049 2229 EPSG:4326:12 1512 1781 4099 4459 EPSG:4326:13 3025 3563 8199 8919 EPSG:4326:14 6050 7127 16399 17839 EPSG:4326:15 12101 14254 32798 35679 EPSG:4326:16 24202 28509 65596 71359 EPSG:4326:17 48405 57019 131192 142719 EPSG:4326:18 96810 114039 262385 285438 EPSG:4326:19 193621 228078 524771 570877 EPSG:4326:20 387242 456157 1049543 1141754 EPSG:4326:21 774485 912315 2099086 2283508 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 3 3 4 4 EPSG:900913:4 6 7 8 8 EPSG:900913:5 13 14 16 17 EPSG:900913:6 27 29 32 34 EPSG:900913:7 55 59 64 69 EPSG:900913:8 110 119 128 139 EPSG:900913:9 221 239 256 278 EPSG:900913:10 443 478 512 557 EPSG:900913:11 886 956 1024 1114 EPSG:900913:12 1772 1913 2049 2229 EPSG:900913:13 3544 3827 4099 4459 EPSG:900913:14 7089 7655 8199 8919 EPSG:900913:15 14179 15311 16399 17839 EPSG:900913:16 28359 30623 32798 35679 EPSG:900913:17 56719 61247 65596 71359 EPSG:900913:18 113438 122495 131192 142719 EPSG:900913:19 226877 244991 262385 285438 EPSG:900913:20 453754 489983 524771 570877 EPSG:900913:21 907509 979967 1049543 1141754 EPSG:900913:22 1815018 1959935 2099086 2283508 EPSG:900913:23 3630037 3919871 4198172 4567017 EPSG:900913:24 7260074 7839742 8396344 9134034 EPSG:900913:25 14520148 15679484 16792689 18268068 EPSG:900913:26 29040296 31358968 33585379 36536137 EPSG:900913:27 58080592 62717936 67170759 73072275 EPSG:900913:28 116161185 125435873 134341518 146144551 EPSG:900913:29 232322370 250871747 268683036 292289103 EPSG:900913:30 464644740 501743494 537366072 584578207 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1114 EPSG:3857:12 1772 1913 2049 2229 EPSG:3857:13 3544 3827 4099 4459 EPSG:3857:14 7089 7655 8199 8919 EPSG:3857:15 14179 15311 16399 17839 EPSG:3857:16 28359 30623 32798 35679 EPSG:3857:17 56719 61247 65596 71359 EPSG:3857:18 113438 122495 131192 142719 EPSG:3857:19 226877 244991 262385 285438 EPSG:3857:20 453754 489983 524771 570877 EPSG:3857:21 907509 979967 1049543 1141754 EPSG:3857:22 1815018 1959935 2099086 2283508 EPSG:3857:23 3630037 3919871 4198172 4567017 EPSG:3857:24 7260074 7839742 8396344 9134034 EPSG:3857:25 14520148 15679484 16792689 18268068 EPSG:3857:26 29040296 31358968 33585379 36536137 EPSG:3857:27 58080592 62717936 67170759 73072275 EPSG:3857:28 116161185 125435873 134341518 146144551 EPSG:3857:29 232322370 250871747 268683036 292289103 EPSG:3857:30 464644740 501743494 537366072 584578207 Global Emissions NOx 1990 - EDGARD Global Emissions EDGAR v4.3.1 (January 2016) In EDGARv4.3.1 emissions are calculated for gaseous and particulate air pollutants per sector and country. For the energy related sectors the activity data are mainly based on the energy balance statistics of IEA (2014) Emission gridmaps are expressed in ton substance / 0.1degree x 0.1degree / year -180.0 -77.95 179.95 88.15000000000002 unea_pollution:edg90_nx image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 13 0 15 EPSG:900913:5 0 27 0 31 EPSG:900913:6 0 54 0 63 EPSG:900913:7 0 109 0 127 EPSG:900913:8 0 219 0 255 EPSG:900913:9 0 439 0 511 EPSG:900913:10 0 878 0 1023 EPSG:900913:11 0 1756 0 2047 EPSG:900913:12 0 3513 0 4095 EPSG:900913:13 0 7027 0 8190 EPSG:900913:14 0 14055 0 16381 EPSG:900913:15 0 28110 0 32763 EPSG:900913:16 0 56221 0 65526 EPSG:900913:17 0 112443 0 131053 EPSG:900913:18 0 224887 0 262107 EPSG:900913:19 0 449775 0 524215 EPSG:900913:20 0 899550 0 1048430 EPSG:900913:21 0 1799100 0 2096860 EPSG:900913:22 0 3598201 0 4193721 EPSG:900913:23 0 7196402 0 8387442 EPSG:900913:24 0 14392805 0 16774885 EPSG:900913:25 0 28785610 0 33549771 EPSG:900913:26 0 57571220 0 67099543 EPSG:900913:27 0 115142440 0 134199086 EPSG:900913:28 0 230284881 0 268398173 EPSG:900913:29 0 460569763 0 536796346 EPSG:900913:30 0 921139526 0 1073592693 wld__pvout_opt_deflate -180.0 -55.0 180.0 60.0 MAPX:wld__pvout_opt_deflate image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 594 1400 0 2047 EPSG:3857:12 1189 2800 0 4095 EPSG:3857:13 2378 5600 0 8191 EPSG:3857:14 4757 11201 0 16383 EPSG:3857:15 9515 22403 0 32767 EPSG:3857:16 19031 44807 0 65535 EPSG:3857:17 38063 89614 0 131071 EPSG:3857:18 76126 179228 0 262143 EPSG:3857:19 152253 358456 0 524287 EPSG:3857:20 304506 716913 0 1048575 EPSG:3857:21 609012 1433827 0 2097151 EPSG:3857:22 1218024 2867654 0 4194304 EPSG:3857:23 2436048 5735309 0 8388608 EPSG:3857:24 4872097 11470618 0 16777215 EPSG:3857:25 9744195 22941236 0 33554431 EPSG:3857:26 19488390 45882473 0 67108863 EPSG:3857:27 38976780 91764947 0 134217727 EPSG:3857:28 77953560 183529894 0 268435456 EPSG:3857:29 155907120 367059788 0 536870911 EPSG:3857:30 311814240 734119577 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 0 15 EPSG:4326:4 2 12 0 31 EPSG:4326:5 5 25 0 63 EPSG:4326:6 10 51 0 127 EPSG:4326:7 21 103 0 255 EPSG:4326:8 42 206 0 511 EPSG:4326:9 85 412 0 1023 EPSG:4326:10 170 824 0 2047 EPSG:4326:11 341 1649 0 4095 EPSG:4326:12 682 3299 0 8191 EPSG:4326:13 1365 6599 0 16383 EPSG:4326:14 2730 13198 0 32767 EPSG:4326:15 5461 26396 0 65535 EPSG:4326:16 10922 52792 0 131071 EPSG:4326:17 21845 105585 0 262143 EPSG:4326:18 43690 211171 0 524287 EPSG:4326:19 87381 422343 0 1048575 EPSG:4326:20 174762 844686 0 2097151 EPSG:4326:21 349525 1689372 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 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image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 15 15 22 22 EPSG:3857:6 30 30 45 45 EPSG:3857:7 61 61 90 90 EPSG:3857:8 123 123 180 180 EPSG:3857:9 247 247 360 360 EPSG:3857:10 495 495 720 721 EPSG:3857:11 990 990 1441 1442 EPSG:3857:12 1981 1981 2883 2884 EPSG:3857:13 3962 3963 5767 5768 EPSG:3857:14 7924 7927 11534 11537 EPSG:3857:15 15849 15855 23068 23075 EPSG:3857:16 31699 31710 46136 46150 EPSG:3857:17 63399 63420 92273 92300 EPSG:3857:18 126798 126840 184546 184601 EPSG:3857:19 253596 253680 369093 369202 EPSG:3857:20 507192 507361 738186 738404 EPSG:3857:21 1014384 1014722 1476372 1476809 EPSG:3857:22 2028769 2029445 2952744 2953619 EPSG:3857:23 4057539 4058891 5905488 5907238 EPSG:3857:24 8115078 8117783 11810976 11814476 EPSG:3857:25 16230157 16235566 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189031631 EPSG:3857:29 259682527 259769071 377951247 378063263 EPSG:3857:30 519365055 519538143 755902495 756126527 Crop Suitability 2011-2040 This dataset show general agricultural suitability at a spatial resolution of 30 arc-second (~1km), considering rainfed conditions and irrigation on currently irrigated areas. The agricultural suitability represents for each pixel the maximum suitability value of considered 16 plants, including: We show a subset of the data that covers three time periods (1981-2010, 2011-2040, 2071-2100), as well as changes in agricultural suitability over the same periods.<br><br>For futher details see: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107522">Zabel F., Putzenlechner B., Mauser W. (2014): Global agricultural land resources – a high resolution suitability evaluation and its perspectives until 2100 under climate change conditions</a><br/><br>Data can also be downloaded from <a href="http://geoportal-glues.ufz.de/stories/globalsuitability.html">here</a>.<br/> -180.0 -60.0 180.0 90.0 MapX_UNDP:overall_cropsuit_i_2011-2040 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 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EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Travel_time_final_Lekoumou_opt 12.796059046335326 -4.052797249963222 14.35138242981778 -2.088002670078685 AccessMod:Travel_time_final_Lekoumou_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 8 8 EPSG:3857:5 16 16 17 17 EPSG:3857:6 32 32 34 34 EPSG:3857:7 64 65 68 69 EPSG:3857:8 129 130 137 138 EPSG:3857:9 258 261 274 276 EPSG:3857:10 517 523 548 552 EPSG:3857:11 1035 1047 1096 1105 EPSG:3857:12 2071 2094 2193 2211 EPSG:3857:13 4143 4188 4387 4422 EPSG:3857:14 8287 8376 8774 8845 EPSG:3857:15 16574 16753 17548 17690 EPSG:3857:16 33148 33506 35097 35380 EPSG:3857:17 66296 67012 70194 70761 EPSG:3857:18 132592 134025 140389 141522 EPSG:3857:19 265185 268051 280779 283044 EPSG:3857:20 530371 536102 561559 566089 EPSG:3857:21 1060742 1072204 1123118 1132178 EPSG:3857:22 2121484 2144409 2246236 2264357 EPSG:3857:23 4242968 4288819 4492473 4528715 EPSG:3857:24 8485937 8577639 8984947 9057430 EPSG:3857:25 16971875 17155279 17969895 18114861 EPSG:3857:26 33943750 34310558 35939790 36229723 EPSG:3857:27 67887500 68621117 71879580 72459447 EPSG:3857:28 135775000 137242235 143759161 144918894 EPSG:3857:29 271550000 274484471 287518322 289837788 EPSG:3857:30 543100001 548968943 575036644 579675577 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 8 8 EPSG:4326:4 8 8 17 17 EPSG:4326:5 16 16 34 34 EPSG:4326:6 32 33 68 69 EPSG:4326:7 65 66 137 138 EPSG:4326:8 130 133 274 276 EPSG:4326:9 261 267 548 552 EPSG:4326:10 523 535 1096 1105 EPSG:4326:11 1047 1070 2193 2211 EPSG:4326:12 2095 2140 4387 4422 EPSG:4326:13 4191 4280 8774 8845 EPSG:4326:14 8382 8560 17548 17690 EPSG:4326:15 16764 17121 35097 35380 EPSG:4326:16 33528 34243 70194 70761 EPSG:4326:17 67056 68487 140389 141522 EPSG:4326:18 134112 136974 280779 283044 EPSG:4326:19 268225 273948 561559 566089 EPSG:4326:20 536451 547897 1123118 1132178 EPSG:4326:21 1072902 1095794 2246236 2264357 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 8 8 EPSG:3857:5 16 16 17 17 EPSG:3857:6 32 32 34 34 EPSG:3857:7 64 65 68 69 EPSG:3857:8 129 130 137 138 EPSG:3857:9 258 261 274 276 EPSG:3857:10 517 523 548 552 EPSG:3857:11 1035 1047 1096 1105 EPSG:3857:12 2071 2094 2193 2211 EPSG:3857:13 4143 4188 4387 4422 EPSG:3857:14 8287 8376 8774 8845 EPSG:3857:15 16574 16753 17548 17690 EPSG:3857:16 33148 33506 35097 35380 EPSG:3857:17 66296 67012 70194 70761 EPSG:3857:18 132592 134025 140389 141522 EPSG:3857:19 265185 268051 280779 283044 EPSG:3857:20 530371 536102 561559 566089 EPSG:3857:21 1060742 1072204 1123118 1132178 EPSG:3857:22 2121484 2144409 2246236 2264357 EPSG:3857:23 4242968 4288819 4492473 4528715 EPSG:3857:24 8485937 8577639 8984947 9057430 EPSG:3857:25 16971875 17155279 17969895 18114861 EPSG:3857:26 33943750 34310558 35939790 36229723 EPSG:3857:27 67887500 68621117 71879580 72459447 EPSG:3857:28 135775000 137242235 143759161 144918894 EPSG:3857:29 271550000 274484471 287518322 289837788 EPSG:3857:30 543100001 548968943 575036644 579675577 Forest Integrity Ecuador Forest Integrity (100m res.) in Ecuador (Montana State University) The forest integrrity index is derived by overlaying the human footprint (Venter et al. 2016) on the forest structural condition. The name is consistent with the concept of ecological integrity. Ecological integrity has been defined as, “the system’s capacity to maintain structure and ecosystem functions using processes and elements characteristic for its ecoregion.” (Parks Canada 2008).  This capacity is a result of the climate, soil, topography, biota and other biophysical properties of the ecoregion and the extent to which these properties are not altered by modern human pressures. Consistent with this definition, the forest integrity index is based on on the structural complexity of a stand relative to the natural potential of the ecoregion and level of human pressure. Thus, forest of high integrity are relatively tall, high in canopy cover, older, and with relatively low human pressure.  An increasing number of studies have shown that human pressure in various forms can have negative effects on native species.  Thus, high integrity forests may be uniquely important for conservation because they support species and processes that are require well-developed forests and are sensitive to human activities.  Such forests often also have high economic value and have likely been preferentially converted to more intense human land uses.  Thus, identifying remaining areas of high forest integrity is important for conservation planning.<br><br>Data is provided by Montana State University.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/">CC-4.0 Attribution</a>.<br/> -81.007003784197 -5.015087128068 -75.189781557321 1.4260239881959995 MapX_UNDP:ecu_forint100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 16 8 9 EPSG:3857:6 31 32 17 18 EPSG:3857:7 63 65 35 37 EPSG:3857:8 126 131 70 74 EPSG:3857:9 253 263 140 149 EPSG:3857:10 507 526 281 298 EPSG:3857:11 1015 1052 563 596 EPSG:3857:12 2031 2105 1126 1192 EPSG:3857:13 4063 4210 2252 2385 EPSG:3857:14 8127 8420 4505 4770 EPSG:3857:15 16254 16841 9010 9540 EPSG:3857:16 32508 33682 18021 19080 EPSG:3857:17 65016 67364 36042 38160 EPSG:3857:18 130033 134728 72084 76320 EPSG:3857:19 260066 269457 144168 152640 EPSG:3857:20 520133 538914 288337 305281 EPSG:3857:21 1040267 1077828 576675 610563 EPSG:3857:22 2080535 2155656 1153351 1221127 EPSG:3857:23 4161071 4311313 2306703 2442255 EPSG:3857:24 8322143 8622627 4613407 4884510 EPSG:3857:25 16644287 17245254 9226815 9769020 EPSG:3857:26 33288574 34490508 18453631 19538040 EPSG:3857:27 66577148 68981016 36907263 39076081 EPSG:3857:28 133154297 137962032 73814527 78152163 EPSG:3857:29 266308595 275924064 147629055 156304326 EPSG:3857:30 532617190 551848128 295258111 312608653 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 1 1 1 EPSG:4326:2 1 2 2 2 EPSG:4326:3 3 4 4 4 EPSG:4326:4 7 8 8 9 EPSG:4326:5 15 16 17 18 EPSG:4326:6 31 33 35 37 EPSG:4326:7 62 67 70 74 EPSG:4326:8 125 135 140 149 EPSG:4326:9 251 270 281 298 EPSG:4326:10 503 540 563 596 EPSG:4326:11 1007 1081 1126 1192 EPSG:4326:12 2015 2162 2252 2385 EPSG:4326:13 4031 4324 4505 4770 EPSG:4326:14 8062 8648 9010 9540 EPSG:4326:15 16124 17296 18021 19080 EPSG:4326:16 32248 34593 36042 38160 EPSG:4326:17 64497 69187 72084 76320 EPSG:4326:18 128995 138375 144168 152640 EPSG:4326:19 257990 276751 288337 305281 EPSG:4326:20 515980 553503 576675 610563 EPSG:4326:21 1031961 1107006 1153351 1221127 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 0 EPSG:900913:2 1 2 1 1 EPSG:900913:3 3 4 2 2 EPSG:900913:4 7 8 4 4 EPSG:900913:5 15 16 8 9 EPSG:900913:6 31 32 17 18 EPSG:900913:7 63 65 35 37 EPSG:900913:8 126 131 70 74 EPSG:900913:9 253 263 140 149 EPSG:900913:10 507 526 281 298 EPSG:900913:11 1015 1052 563 596 EPSG:900913:12 2031 2105 1126 1192 EPSG:900913:13 4063 4210 2252 2385 EPSG:900913:14 8127 8420 4505 4770 EPSG:900913:15 16254 16841 9010 9540 EPSG:900913:16 32508 33682 18021 19080 EPSG:900913:17 65016 67364 36042 38160 EPSG:900913:18 130033 134728 72084 76320 EPSG:900913:19 260066 269457 144168 152640 EPSG:900913:20 520133 538914 288337 305281 EPSG:900913:21 1040267 1077828 576675 610563 EPSG:900913:22 2080535 2155656 1153351 1221127 EPSG:900913:23 4161071 4311313 2306703 2442255 EPSG:900913:24 8322143 8622627 4613407 4884510 EPSG:900913:25 16644287 17245254 9226815 9769020 EPSG:900913:26 33288574 34490508 18453631 19538040 EPSG:900913:27 66577148 68981016 36907263 39076081 EPSG:900913:28 133154297 137962032 73814527 78152163 EPSG:900913:29 266308595 275924064 147629055 156304326 EPSG:900913:30 532617190 551848128 295258111 312608653 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 16 8 9 EPSG:3857:6 31 32 17 18 EPSG:3857:7 63 65 35 37 EPSG:3857:8 126 131 70 74 EPSG:3857:9 253 263 140 149 EPSG:3857:10 507 526 281 298 EPSG:3857:11 1015 1052 563 596 EPSG:3857:12 2031 2105 1126 1192 EPSG:3857:13 4063 4210 2252 2385 EPSG:3857:14 8127 8420 4505 4770 EPSG:3857:15 16254 16841 9010 9540 EPSG:3857:16 32508 33682 18021 19080 EPSG:3857:17 65016 67364 36042 38160 EPSG:3857:18 130033 134728 72084 76320 EPSG:3857:19 260066 269457 144168 152640 EPSG:3857:20 520133 538914 288337 305281 EPSG:3857:21 1040267 1077828 576675 610563 EPSG:3857:22 2080535 2155656 1153351 1221127 EPSG:3857:23 4161071 4311313 2306703 2442255 EPSG:3857:24 8322143 8622627 4613407 4884510 EPSG:3857:25 16644287 17245254 9226815 9769020 EPSG:3857:26 33288574 34490508 18453631 19538040 EPSG:3857:27 66577148 68981016 36907263 39076081 EPSG:3857:28 133154297 137962032 73814527 78152163 EPSG:3857:29 266308595 275924064 147629055 156304326 EPSG:3857:30 532617190 551848128 295258111 312608653 Automn precipitations change (%) for the period 2040 - 2059 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_son_MIDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Combination Tsunami/Forest at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_for9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Historical Land Cover of emerging Northwest Mining Region of Ghana (2010) The 2010 land use and land cover data of the emerging Northwest mining region shows the current state of environmental conditions in the area, two decades after the Rio Conference, and how this has been impacted by illegal mining or quarrying or large-scale exploration activities in the area. This data could also be used to identify the gaps that need to be filled before the commencement of large-scale mining in the very nearest future. It is important to ask how this data could be used to inform relevant decision making on illegal mining in the area. The simple answer to the question is that environmental and land use impacts of the activities can be identified and mitigated, the presence and movement patterns of both illegal small-scale gold mining (galamsey) and large-scale mining can be tracked and estimate their environmental footprint using this data. Potential conflicts with regards to land use and concession encroachment could also be averted with these data. -2.941952153 9.62648323 -1.4272597149999997 11.03077215 MAPX:GHA_LULC2010 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124028 128929 130032 EPSG:3857:19 245979 248057 257859 260065 EPSG:3857:20 491958 496115 515718 520130 EPSG:3857:21 983916 992231 1031437 1040261 EPSG:3857:22 1967832 1984463 2062875 2080523 EPSG:3857:23 3935665 3968927 4125751 4161046 EPSG:3857:24 7871331 7937855 8251503 8322092 EPSG:3857:25 15742662 15875711 16503006 16644185 EPSG:3857:26 31485325 31751422 33006012 33288371 EPSG:3857:27 62970650 63502845 66012024 66576743 EPSG:3857:28 125941301 127005690 132024049 133153486 EPSG:3857:29 251882602 254011381 264048098 266306972 EPSG:3857:30 503765204 508022762 528096197 532613944 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1828 4029 4063 EPSG:4326:13 3593 3657 8058 8127 EPSG:4326:14 7187 7315 16116 16254 EPSG:4326:15 14375 14631 32232 32508 EPSG:4326:16 28751 29263 64464 65016 EPSG:4326:17 57503 58526 128929 130032 EPSG:4326:18 115007 117052 257859 260065 EPSG:4326:19 230014 234104 515718 520130 EPSG:4326:20 460029 468209 1031437 1040261 EPSG:4326:21 920058 936419 2062875 2080523 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124028 128929 130032 EPSG:3857:19 245979 248057 257859 260065 EPSG:3857:20 491958 496115 515718 520130 EPSG:3857:21 983916 992231 1031437 1040261 EPSG:3857:22 1967832 1984463 2062875 2080523 EPSG:3857:23 3935665 3968927 4125751 4161046 EPSG:3857:24 7871331 7937855 8251503 8322092 EPSG:3857:25 15742662 15875711 16503006 16644185 EPSG:3857:26 31485325 31751422 33006012 33288371 EPSG:3857:27 62970650 63502845 66012024 66576743 EPSG:3857:28 125941301 127005690 132024049 133153486 EPSG:3857:29 251882602 254011381 264048098 266306972 EPSG:3857:30 503765204 508022762 528096197 532613944 20190927_843_mergedQG 149.66386433258654 -36.214355797728665 150.97478007537504 -32.49681353198739 wesr_swipe:20190927_843_mergedQG image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 152 155 234 235 EPSG:3857:9 304 311 468 470 EPSG:3857:10 609 622 937 941 EPSG:3857:11 1219 1245 1875 1882 EPSG:3857:12 2439 2490 3750 3765 EPSG:3857:13 4878 4981 7501 7531 EPSG:3857:14 9757 9962 15003 15063 EPSG:3857:15 19514 19924 30006 30126 EPSG:3857:16 39029 39849 60013 60252 EPSG:3857:17 78058 79698 120026 120504 EPSG:3857:18 156116 159396 240053 241008 EPSG:3857:19 312233 318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 EPSG:3857:22 2497869 2550351 3840862 3856135 EPSG:3857:23 4995738 5100703 7681724 7712271 EPSG:3857:24 9991476 10201407 15363449 15424542 EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 3 3 EPSG:4326:2 2 2 7 7 EPSG:4326:3 5 5 14 14 EPSG:4326:4 10 11 29 29 EPSG:4326:5 21 22 58 58 EPSG:4326:6 43 44 117 117 EPSG:4326:7 87 89 234 235 EPSG:4326:8 174 179 468 470 EPSG:4326:9 348 359 937 941 EPSG:4326:10 696 718 1875 1882 EPSG:4326:11 1393 1436 3750 3765 EPSG:4326:12 2787 2872 7501 7531 EPSG:4326:13 5574 5744 15003 15063 EPSG:4326:14 11149 11488 30006 30126 EPSG:4326:15 22299 22976 60013 60252 EPSG:4326:16 44599 45953 120026 120504 EPSG:4326:17 89199 91906 240053 241008 EPSG:4326:18 178398 183812 480107 482016 EPSG:4326:19 356797 367625 960215 964033 EPSG:4326:20 713595 735251 1920431 1928067 EPSG:4326:21 1427191 1470503 3840862 3856135 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 152 155 234 235 EPSG:3857:9 304 311 468 470 EPSG:3857:10 609 622 937 941 EPSG:3857:11 1219 1245 1875 1882 EPSG:3857:12 2439 2490 3750 3765 EPSG:3857:13 4878 4981 7501 7531 EPSG:3857:14 9757 9962 15003 15063 EPSG:3857:15 19514 19924 30006 30126 EPSG:3857:16 39029 39849 60013 60252 EPSG:3857:17 78058 79698 120026 120504 EPSG:3857:18 156116 159396 240053 241008 EPSG:3857:19 312233 318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 EPSG:3857:22 2497869 2550351 3840862 3856135 EPSG:3857:23 4995738 5100703 7681724 7712271 EPSG:3857:24 9991476 10201407 15363449 15424542 EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 Inorganic Pollution 2008 - KNB Non-point source inorganic pollution was modelled with global 1 km2 impervious surface area data (http://www.ngdc.noaa.gov/dmsp/) under the assumption that most of this pollution comes from urban runoff. These data will not capture point-sources of pollution or nonpoint sources where paved roads do not exist (e.g., select places in developing countries). These values were then aggregated to the watershed and distributed to the pour point (i.e., stream and river mouths) for the watershed with raster statistics (i.e., aggregation by watershed). Finally, spread of the driver values into coastal waters at each pour point was modelled with a cost-path surface on the basis of a decay function that assigns a fixed amount of the driver (0.5% of the value in the previous cell) in the initial cell and then evenly distributes the remaining amount of driver in all adjacent and ‘unvisited’ cells, repeated until a minimum threshold (0.05% of global maximum) is reached. This approach to modelling river plumes is diffusive and so allows drivers to wrap around headlands and islands. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS." -179.99998890825066 -89.90931632117805 180.0 83.62149081142242 unea_pollution:08_inorganic_poll_halpern_KNB_WGS84 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 41 1023 0 1023 EPSG:3857:11 82 2047 0 2047 EPSG:3857:12 165 4095 0 4095 EPSG:3857:13 331 8191 0 8191 EPSG:3857:14 662 16383 0 16383 EPSG:3857:15 1325 32767 0 32767 EPSG:3857:16 2651 65535 0 65535 EPSG:3857:17 5302 131071 0 131071 EPSG:3857:18 10605 262143 0 262143 EPSG:3857:19 21210 524287 0 524287 EPSG:3857:20 42420 1048575 0 1048575 EPSG:3857:21 84840 2097151 0 2097151 EPSG:3857:22 169680 4194303 0 4194304 EPSG:3857:23 339361 8388607 0 8388608 EPSG:3857:24 678722 16777215 0 16777215 EPSG:3857:25 1357445 33554431 1 33554431 EPSG:3857:26 2714891 67108863 2 67108863 EPSG:3857:27 5429782 134217727 4 134217727 EPSG:3857:28 10859564 268435455 8 268435456 EPSG:3857:29 21719128 536870911 16 536870911 EPSG:3857:30 43438256 1073741823 33 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 9 255 0 511 EPSG:4326:9 18 511 0 1023 EPSG:4326:10 36 1023 0 2047 EPSG:4326:11 72 2046 0 4095 EPSG:4326:12 145 4093 0 8191 EPSG:4326:13 290 8187 0 16383 EPSG:4326:14 580 16375 0 32767 EPSG:4326:15 1161 32751 0 65535 EPSG:4326:16 2322 65502 0 131071 EPSG:4326:17 4644 131005 0 262143 EPSG:4326:18 9289 262011 0 524287 EPSG:4326:19 18578 524023 0 1048575 EPSG:4326:20 37157 1048047 0 2097151 EPSG:4326:21 74315 2096095 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 1 31 0 31 EPSG:900913:6 2 63 0 63 EPSG:900913:7 5 127 0 127 EPSG:900913:8 10 255 0 255 EPSG:900913:9 20 511 0 511 EPSG:900913:10 41 1023 0 1023 EPSG:900913:11 82 2047 0 2047 EPSG:900913:12 165 4095 0 4095 EPSG:900913:13 331 8191 0 8191 EPSG:900913:14 662 16383 0 16383 EPSG:900913:15 1325 32767 0 32767 EPSG:900913:16 2651 65535 0 65535 EPSG:900913:17 5302 131071 0 131071 EPSG:900913:18 10605 262143 0 262143 EPSG:900913:19 21210 524287 0 524287 EPSG:900913:20 42420 1048575 0 1048575 EPSG:900913:21 84840 2097151 0 2097151 EPSG:900913:22 169680 4194303 0 4194303 EPSG:900913:23 339361 8388607 0 8388607 EPSG:900913:24 678722 16777215 0 16777215 EPSG:900913:25 1357445 33554431 1 33554431 EPSG:900913:26 2714891 67108863 2 67108863 EPSG:900913:27 5429782 134217727 4 134217727 EPSG:900913:28 10859564 268435455 8 268435455 EPSG:900913:29 21719128 536870911 16 536870911 EPSG:900913:30 43438256 1073741823 33 1073741823 Livelihood Zones (FEWS NET Data Center) Livelihood zone maps define geographic areas of a country where people generally share similar options for obtaining food and income and similar access to markets. An understanding of geographic livelihood systems is a key component of FEWS NET’s food security analysis. The maps are produced through multi-day workshops during which food security stakeholders and country experts identify zones. Factors considered include agro-climatology, elevation, land-cover, market accessibility, sources of food, and major economic activities. A livelihood zone map is typically accompanied by a livelihood description which outlines the key characteristics of each zone. In some cases, maps may also be accompanied by livelihood profiles, which are in-depth descriptions of the characteristics of wealth groups within each zone. The zone maps are available for download as PDFs, PNGs, and GIS shapefiles. The shapefiles and maps are all produced and maintained by FEWS NET. Please consult the logos in maps for the full list of organizations who participated in and/or funded the zoning workshop. For more information on FEWS NET’s livelihood approach and to view our other livelihood products, please click <a href="https://fews.net/sectors-topics/sectors/livelihoods"target=_blank>here</a>. <br><br> Data sourced from <a href="http://fews.net/fews-data/335"target=_blank>FEWS NET Data Center</a>. -90.12866210916894 -30.668964385997583 74.87943118699972 38.48342611122613 UN_Sahel:FEWS_NET_LH_World image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 2 EPSG:3857:3 3 4 1 5 EPSG:3857:4 6 9 3 11 EPSG:3857:5 12 18 7 22 EPSG:3857:6 24 37 15 45 EPSG:3857:7 49 75 31 90 EPSG:3857:8 98 150 63 181 EPSG:3857:9 196 301 127 362 EPSG:3857:10 393 603 255 724 EPSG:3857:11 786 1207 511 1449 EPSG:3857:12 1572 2414 1022 2899 EPSG:3857:13 3145 4829 2045 5799 EPSG:3857:14 6291 9659 4090 11599 EPSG:3857:15 12583 19319 8180 23199 EPSG:3857:16 25167 38638 16360 46399 EPSG:3857:17 50334 77277 32721 92798 EPSG:3857:18 100668 154554 65442 185597 EPSG:3857:19 201336 309108 130884 371195 EPSG:3857:20 402672 618217 261769 742390 EPSG:3857:21 805345 1236434 523538 1484780 EPSG:3857:22 1610691 2472868 1047076 2969560 EPSG:3857:23 3221383 4945737 2094153 5939121 EPSG:3857:24 6442767 9891474 4188307 11878242 EPSG:3857:25 12885535 19782948 8376615 23756484 EPSG:3857:26 25771071 39565896 16753231 47512969 EPSG:3857:27 51542143 79131793 33506463 95025939 EPSG:3857:28 103084287 158263587 67012926 190051878 EPSG:3857:29 206168575 316527174 134025853 380103757 EPSG:3857:30 412337151 633054349 268051706 760207514 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 2 EPSG:4326:2 1 2 1 5 EPSG:4326:3 2 5 3 11 EPSG:4326:4 4 10 7 22 EPSG:4326:5 9 21 15 45 EPSG:4326:6 18 42 31 90 EPSG:4326:7 36 85 63 181 EPSG:4326:8 73 171 127 362 EPSG:4326:9 146 343 255 724 EPSG:4326:10 293 686 511 1449 EPSG:4326:11 586 1372 1022 2899 EPSG:4326:12 1172 2745 2045 5799 EPSG:4326:13 2344 5491 4090 11599 EPSG:4326:14 4689 10983 8180 23199 EPSG:4326:15 9378 21967 16360 46399 EPSG:4326:16 18756 43934 32721 92798 EPSG:4326:17 37513 87868 65442 185597 EPSG:4326:18 75026 175736 130884 371195 EPSG:4326:19 150052 351473 261769 742390 EPSG:4326:20 300105 702947 523538 1484780 EPSG:4326:21 600211 1405895 1047076 2969560 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 2 EPSG:3857:3 3 4 1 5 EPSG:3857:4 6 9 3 11 EPSG:3857:5 12 18 7 22 EPSG:3857:6 24 37 15 45 EPSG:3857:7 49 75 31 90 EPSG:3857:8 98 150 63 181 EPSG:3857:9 196 301 127 362 EPSG:3857:10 393 603 255 724 EPSG:3857:11 786 1207 511 1449 EPSG:3857:12 1572 2414 1022 2899 EPSG:3857:13 3145 4829 2045 5799 EPSG:3857:14 6291 9659 4090 11599 EPSG:3857:15 12583 19319 8180 23199 EPSG:3857:16 25167 38638 16360 46399 EPSG:3857:17 50334 77277 32721 92798 EPSG:3857:18 100668 154554 65442 185597 EPSG:3857:19 201336 309108 130884 371195 EPSG:3857:20 402672 618217 261769 742390 EPSG:3857:21 805345 1236434 523538 1484780 EPSG:3857:22 1610691 2472868 1047076 2969560 EPSG:3857:23 3221383 4945737 2094153 5939121 EPSG:3857:24 6442767 9891474 4188307 11878242 EPSG:3857:25 12885535 19782948 8376615 23756484 EPSG:3857:26 25771071 39565896 16753231 47512969 EPSG:3857:27 51542143 79131793 33506463 95025939 EPSG:3857:28 103084287 158263587 67012926 190051878 EPSG:3857:29 206168575 316527174 134025853 380103757 EPSG:3857:30 412337151 633054349 268051706 760207514 Yearly emissions of CH4 - 1980 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -88.79999999998984 179.99999999997954 90.0 wesr_climat:v60_CH4_1980_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 254 0 511 EPSG:4326:9 0 508 0 1023 EPSG:4326:10 0 1017 0 2047 EPSG:4326:11 0 2034 0 4095 EPSG:4326:12 0 4068 0 8191 EPSG:4326:13 0 8137 0 16383 EPSG:4326:14 0 16274 0 32767 EPSG:4326:15 0 32549 0 65535 EPSG:4326:16 0 65099 0 131071 EPSG:4326:17 0 130198 0 262143 EPSG:4326:18 0 260396 0 524287 EPSG:4326:19 0 520792 0 1048575 EPSG:4326:20 0 1041585 0 2097151 EPSG:4326:21 0 2083170 0 4194303 EPSG:900913 EPSG:3857_512 Forest Fragmentation (2012) 500m The fragmentation dataset classifies forested areas into several fragmentation classes using spatial pattern analysis, and includes effects of both deforestation and regrowth on forest fragmentation. Multiple variations of this dataset are available for the years 2000 and 2012, each making different assumptions about: the distance that fragmentation effects extend into forests (500 metres or 1000 metres); the canopy cover (%) that defines forest area (25 or 50%); and the minimum area (in hectares) of a fragment to be be considered a forest fragment (0, 1 or 5 ha). The map presented here shows effects extending 500 metres into forest interiors. This dataset has a 30-metre spatial resolution. Data derived from: Hansen, M.C., et al. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342, 850–853. 10.1126/science.1244693 Created as part of the GEF-funded Global Support to Sixth National Report Project in collaboration with the NASA-funded Forest Integrity Project. -119.36170706306382 -34.213866389533806 179.99995545035347 30.001378 MapX_UNDP_nd:frag_2012_500_25_0 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 13 19 5 31 EPSG:3857:6 26 38 10 63 EPSG:3857:7 52 76 21 127 EPSG:3857:8 105 153 43 255 EPSG:3857:9 211 307 86 511 EPSG:3857:10 422 615 172 1023 EPSG:3857:11 844 1231 344 2047 EPSG:3857:12 1689 2462 689 4095 EPSG:3857:13 3379 4925 1379 8191 EPSG:3857:14 6759 9850 2759 16383 EPSG:3857:15 13519 19701 5519 32767 EPSG:3857:16 27038 39403 11038 65535 EPSG:3857:17 54076 78806 22077 131071 EPSG:3857:18 108152 157613 44155 262143 EPSG:3857:19 216305 315227 88310 524287 EPSG:3857:20 432611 630455 176621 1048575 EPSG:3857:21 865223 1260910 353243 2097151 EPSG:3857:22 1730447 2521821 706487 4194303 EPSG:3857:23 3460894 5043642 1412974 8388606 EPSG:3857:24 6921789 10087284 2825949 16777213 EPSG:3857:25 13843578 20174568 5651898 33554427 EPSG:3857:26 27687157 40349137 11303797 67108855 EPSG:3857:27 55374314 80698274 22607594 134217711 EPSG:3857:28 110748628 161396549 45215188 268435422 EPSG:3857:29 221497257 322793098 90430376 536870845 EPSG:3857:30 442994514 645586197 180860753 1073741691 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 1 2 1 7 EPSG:4326:3 2 5 2 15 EPSG:4326:4 5 11 5 31 EPSG:4326:5 10 22 10 63 EPSG:4326:6 21 44 21 127 EPSG:4326:7 42 88 43 255 EPSG:4326:8 85 176 86 511 EPSG:4326:9 170 353 172 1023 EPSG:4326:10 341 706 344 2047 EPSG:4326:11 682 1413 689 4095 EPSG:4326:12 1365 2826 1379 8191 EPSG:4326:13 2730 5653 2759 16383 EPSG:4326:14 5461 11306 5519 32767 EPSG:4326:15 10922 22612 11038 65535 EPSG:4326:16 21844 45224 22077 131071 EPSG:4326:17 43689 90449 44155 262143 EPSG:4326:18 87379 180899 88310 524287 EPSG:4326:19 174758 361799 176621 1048575 EPSG:4326:20 349517 723598 353243 2097151 EPSG:4326:21 699034 1447196 706487 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 13 19 5 31 EPSG:3857:6 26 38 10 63 EPSG:3857:7 52 76 21 127 EPSG:3857:8 105 153 43 255 EPSG:3857:9 211 307 86 511 EPSG:3857:10 422 615 172 1023 EPSG:3857:11 844 1231 344 2047 EPSG:3857:12 1689 2462 689 4095 EPSG:3857:13 3379 4925 1379 8191 EPSG:3857:14 6759 9850 2759 16383 EPSG:3857:15 13519 19701 5519 32767 EPSG:3857:16 27038 39403 11038 65535 EPSG:3857:17 54076 78806 22077 131071 EPSG:3857:18 108152 157613 44155 262143 EPSG:3857:19 216305 315227 88310 524287 EPSG:3857:20 432611 630455 176621 1048575 EPSG:3857:21 865223 1260910 353243 2097151 EPSG:3857:22 1730447 2521821 706487 4194303 EPSG:3857:23 3460894 5043642 1412974 8388606 EPSG:3857:24 6921789 10087284 2825949 16777213 EPSG:3857:25 13843578 20174568 5651898 33554427 EPSG:3857:26 27687157 40349137 11303797 67108855 EPSG:3857:27 55374314 80698274 22607594 134217711 EPSG:3857:28 110748628 161396549 45215188 268435422 EPSG:3857:29 221497257 322793098 90430376 536870845 EPSG:3857:30 442994514 645586197 180860753 1073741691 Historical Land Cover of emerging Northwest Mining Region of Ghana (2019) The 2019 land cover data mark the biophysical state of the area, three decades after the Rio conference: (1) after the government of Ghana fight against galamsey (illegal artisanal small-scale gold mining), and (2) the initial environmental parameters for validating the environmental and social impact assessment reports prior to the finalisation of construction of large-scale mining sites waiting for commissioning. This data makes it possible to map the mining activities onto the Agenda 2030 SDGs, making it easy to take critically relevant decisions, track the activities of the large-scale operations as well as small-scale illegal mining operations, and mitigate the environmental hazards -2.941804951 9.626453977 -1.42736896 11.030613419 MAPX:GHA_LULC2019 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1828 4029 4063 EPSG:4326:13 3593 3657 8058 8127 EPSG:4326:14 7187 7315 16116 16254 EPSG:4326:15 14375 14631 32232 32508 EPSG:4326:16 28751 29263 64464 65016 EPSG:4326:17 57503 58526 128929 130032 EPSG:4326:18 115007 117052 257859 260065 EPSG:4326:19 230015 234104 515719 520130 EPSG:4326:20 460030 468209 1031438 1040260 EPSG:4326:21 920060 936419 2062877 2080521 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 tsm_col_zaragoza_20210821 -74.8651063820499 7.579889039548307 -74.7899249680916 7.640072688469066 rs_for_asgm:tsm_col_zaragoza_20210821 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7496 7502 9569 9576 EPSG:4326:15 14993 15004 19139 19152 EPSG:4326:16 29986 30008 38278 38305 EPSG:4326:17 59972 60016 76556 76611 EPSG:4326:18 119945 120032 153113 153223 EPSG:4326:19 239890 240065 306227 306446 EPSG:4326:20 479781 480131 612455 612893 EPSG:4326:21 959562 960263 1224910 1225786 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 Combination Tsunami/Sea grasses at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_sea6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 wesr_climate_sta_an -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_sta_an image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone surge/ Mangroves at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_man6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Yearly emissions of N2O - 1980 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -90.0 180.0 90.0 wesr_climat:v60_N2O_1980_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Tropical cyclone surge hazard frequency -180.0 -90.0 180.0 90.0 ECO-DRR:cs_freqaf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Hydrography Water bodies and lines 14.277696102783837 2.062153738845037 27.534422769575563 11.020837401603712 cc_and_health:hydrography application/json;type=utfgrid image/png image/vnd.jpeg-png image/jpeg application/json;type=topojson image/gif image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 253 276 295 EPSG:3857:10 480 506 552 590 EPSG:3857:11 960 1012 1105 1180 EPSG:3857:12 1921 2024 2210 2361 EPSG:3857:13 3843 4049 4420 4722 EPSG:3857:14 7687 8098 8841 9445 EPSG:3857:15 15374 16196 17683 18890 EPSG:3857:16 30749 32392 35367 37780 EPSG:3857:17 61498 64785 70734 75560 EPSG:3857:18 122996 129570 141468 151121 EPSG:3857:19 245993 259140 282937 302243 EPSG:3857:20 491987 518280 565874 604487 EPSG:3857:21 983975 1036560 1131749 1208975 EPSG:3857:22 1967950 2073120 2263499 2417951 EPSG:3857:23 3935901 4146241 4526998 4835902 EPSG:3857:24 7871803 8292483 9053996 9671805 EPSG:3857:25 15743606 16584967 18107993 19343610 EPSG:3857:26 31487212 33169935 36215987 38687220 EPSG:3857:27 62974424 66339871 72431974 77374440 EPSG:3857:28 125948848 132679742 144863949 154748881 EPSG:3857:29 251897696 265359485 289727899 309497763 EPSG:3857:30 503795393 530718970 579455799 618995526 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 125 276 295 EPSG:4326:9 224 250 552 590 EPSG:4326:10 449 500 1105 1180 EPSG:4326:11 898 1000 2210 2361 EPSG:4326:12 1797 2001 4420 4722 EPSG:4326:13 3594 4002 8841 9445 EPSG:4326:14 7188 8004 17683 18890 EPSG:4326:15 14377 16008 35367 37780 EPSG:4326:16 28755 32017 70734 75560 EPSG:4326:17 57510 64034 141468 151121 EPSG:4326:18 115021 128068 282937 302243 EPSG:4326:19 230043 256137 565874 604487 EPSG:4326:20 460086 512275 1131749 1208975 EPSG:4326:21 920173 1024550 2263499 2417951 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 253 276 295 EPSG:3857:10 480 506 552 590 EPSG:3857:11 960 1012 1105 1180 EPSG:3857:12 1921 2024 2210 2361 EPSG:3857:13 3843 4049 4420 4722 EPSG:3857:14 7687 8098 8841 9445 EPSG:3857:15 15374 16196 17683 18890 EPSG:3857:16 30749 32392 35367 37780 EPSG:3857:17 61498 64785 70734 75560 EPSG:3857:18 122996 129570 141468 151121 EPSG:3857:19 245993 259140 282937 302243 EPSG:3857:20 491987 518280 565874 604487 EPSG:3857:21 983975 1036560 1131749 1208975 EPSG:3857:22 1967950 2073120 2263499 2417951 EPSG:3857:23 3935901 4146241 4526998 4835902 EPSG:3857:24 7871803 8292483 9053996 9671805 EPSG:3857:25 15743606 16584967 18107993 19343610 EPSG:3857:26 31487212 33169935 36215987 38687220 EPSG:3857:27 62974424 66339871 72431974 77374440 EPSG:3857:28 125948848 132679742 144863949 154748881 EPSG:3857:29 251897696 265359485 289727899 309497763 EPSG:3857:30 503795393 530718970 579455799 618995526 Spring temperature change (°C) for the period 2040 - 2059 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_mam_MIDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Flood hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:fl_phex_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Travel_time_final_Benin_opt 0.7572938644426767 6.232483045915507 3.847729210168526 12.414186738808102 AccessMod:Travel_time_final_Benin_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 15 16 16 EPSG:3857:6 29 30 32 32 EPSG:3857:7 59 61 64 65 EPSG:3857:8 119 123 128 130 EPSG:3857:9 238 247 257 261 EPSG:3857:10 476 494 514 522 EPSG:3857:11 952 988 1028 1045 EPSG:3857:12 1905 1976 2056 2091 EPSG:3857:13 3811 3953 4113 4183 EPSG:3857:14 7622 7907 8226 8367 EPSG:3857:15 15245 15815 16452 16734 EPSG:3857:16 30490 31631 32905 33468 EPSG:3857:17 60980 63262 65811 66936 EPSG:3857:18 121960 126524 131623 133873 EPSG:3857:19 243921 253049 263246 267747 EPSG:3857:20 487842 506098 526493 535495 EPSG:3857:21 975685 1012197 1052987 1070990 EPSG:3857:22 1951371 2024394 2105975 2141981 EPSG:3857:23 3902742 4048789 4211950 4283962 EPSG:3857:24 7805484 8097578 8423900 8567925 EPSG:3857:25 15610968 16195157 16847800 17135850 EPSG:3857:26 31221937 32390314 33695601 34271700 EPSG:3857:27 62443875 64780629 67391203 68543401 EPSG:3857:28 124887751 129561259 134782407 137086802 EPSG:3857:29 249775502 259122519 269564814 274173605 EPSG:3857:30 499551005 518245039 539129628 548347211 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 6 7 16 16 EPSG:4326:5 13 14 32 32 EPSG:4326:6 27 29 64 65 EPSG:4326:7 55 59 128 130 EPSG:4326:8 110 119 257 261 EPSG:4326:9 220 238 514 522 EPSG:4326:10 441 476 1028 1045 EPSG:4326:11 882 953 2056 2091 EPSG:4326:12 1765 1906 4113 4183 EPSG:4326:13 3531 3812 8226 8367 EPSG:4326:14 7062 7624 16452 16734 EPSG:4326:15 14124 15249 32905 33468 EPSG:4326:16 28248 30498 65811 66936 EPSG:4326:17 56496 60997 131623 133873 EPSG:4326:18 112992 121995 263246 267747 EPSG:4326:19 225985 243990 526493 535495 EPSG:4326:20 451970 487981 1052987 1070990 EPSG:4326:21 903940 975962 2105975 2141981 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 15 16 16 EPSG:3857:6 29 30 32 32 EPSG:3857:7 59 61 64 65 EPSG:3857:8 119 123 128 130 EPSG:3857:9 238 247 257 261 EPSG:3857:10 476 494 514 522 EPSG:3857:11 952 988 1028 1045 EPSG:3857:12 1905 1976 2056 2091 EPSG:3857:13 3811 3953 4113 4183 EPSG:3857:14 7622 7907 8226 8367 EPSG:3857:15 15245 15815 16452 16734 EPSG:3857:16 30490 31631 32905 33468 EPSG:3857:17 60980 63262 65811 66936 EPSG:3857:18 121960 126524 131623 133873 EPSG:3857:19 243921 253049 263246 267747 EPSG:3857:20 487842 506098 526493 535495 EPSG:3857:21 975685 1012197 1052987 1070990 EPSG:3857:22 1951371 2024394 2105975 2141981 EPSG:3857:23 3902742 4048789 4211950 4283962 EPSG:3857:24 7805484 8097578 8423900 8567925 EPSG:3857:25 15610968 16195157 16847800 17135850 EPSG:3857:26 31221937 32390314 33695601 34271700 EPSG:3857:27 62443875 64780629 67391203 68543401 EPSG:3857:28 124887751 129561259 134782407 137086802 EPSG:3857:29 249775502 259122519 269564814 274173605 EPSG:3857:30 499551005 518245039 539129628 548347211 Year precipitations 2016 - Central African Republic Total precipitations observed in 2016 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2016_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 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579874153 618804814 Combination Tropical cyclone surge/ Sea grasses at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_sea6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Precipitation Anomaly 2020 (1991-2020) This variable is the accumulated liquid and frozen water, including rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation (that precipitation which is generated by large-scale weather patterns, such as troughs and cold fronts) and convective precipitation (generated by convection which occurs when air at lower levels in the atmosphere is warmer and less dense than the air above, so it rises). Precipitation variables do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. Monthly mean precipitation data is in units of “m”, effectively accumulated over a day, thereby giving “m day-1”. For consistency with the ECMWF parameter database, the units in the GRIB files are “m”. 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The layer is calculated at UNEP/GRID-Geneva from the layers on annual precipitation [mm/year] provided in the products CHELSA V1.2 and CHELSA-[CMIP5]. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:Diff_CHELSA_bio_mon_ACCESS1-0_rcp85_r1i1p1_g025.nc_1_2041-2060_V12_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 Burnt areas in Kedougou between 2015 and 2024 Forest fire hazard assessment is based on a retrospective analysis of burnt areas, using satellite data from different time periods. The methodology uses the Normalized Burn Ratio (NBR) index, calculated from the near-infrared (NIR) and short-wave infrared (SWIR) spectral bands of the Landsat. -13.238921499711449 12.308356696892037 -11.345452543844322 13.463410489212919 risk_southeast_senegal:burn_2015_2024 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30702 EPSG:3857:17 60588 61019 60715 61405 EPSG:3857:18 121176 122039 121431 122810 EPSG:3857:19 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EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7509 7512 7401 7405 EPSG:3857:15 15019 15025 14803 14810 EPSG:3857:16 30038 30050 29606 29621 EPSG:3857:17 60077 60100 59212 59242 EPSG:3857:18 120155 120200 118425 118484 EPSG:3857:19 240311 240401 236851 236968 EPSG:3857:20 480623 480802 473702 473937 EPSG:3857:21 961247 961605 947405 947874 EPSG:3857:22 1922495 1923210 1894810 1895748 EPSG:3857:23 3844990 3846420 3789620 3791496 EPSG:3857:24 7689980 7692840 7579241 7582992 EPSG:3857:25 15379960 15385681 15158483 15165984 EPSG:3857:26 30759920 30771362 30316966 30331968 EPSG:3857:27 61519840 61542725 60633932 60663937 EPSG:3857:28 123039681 123085451 121267864 121327875 EPSG:3857:29 246079362 246170903 242535729 242655750 EPSG:3857:30 492158724 492341807 485071459 485311501 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 462 EPSG:4326:10 427 428 925 925 EPSG:4326:11 855 856 1850 1851 EPSG:4326:12 1710 1712 3700 3702 EPSG:4326:13 3421 3424 7401 7405 EPSG:4326:14 6842 6848 14803 14810 EPSG:4326:15 13685 13696 29606 29621 EPSG:4326:16 27371 27392 59212 59242 EPSG:4326:17 54742 54785 118425 118484 EPSG:4326:18 109484 109571 236851 236968 EPSG:4326:19 218969 219142 473702 473937 EPSG:4326:20 437939 438284 947405 947874 EPSG:4326:21 875878 876569 1894810 1895748 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7509 7512 7401 7405 EPSG:3857:15 15019 15025 14803 14810 EPSG:3857:16 30038 30050 29606 29621 EPSG:3857:17 60077 60100 59212 59242 EPSG:3857:18 120155 120200 118425 118484 EPSG:3857:19 240311 240401 236851 236968 EPSG:3857:20 480623 480802 473702 473937 EPSG:3857:21 961247 961605 947405 947874 EPSG:3857:22 1922495 1923210 1894810 1895748 EPSG:3857:23 3844990 3846420 3789620 3791496 EPSG:3857:24 7689980 7692840 7579241 7582992 EPSG:3857:25 15379960 15385681 15158483 15165984 EPSG:3857:26 30759920 30771362 30316966 30331968 EPSG:3857:27 61519840 61542725 60633932 60663937 EPSG:3857:28 123039681 123085451 121267864 121327875 EPSG:3857:29 246079362 246170903 242535729 242655750 EPSG:3857:30 492158724 492341807 485071459 485311501 Spring precipitations change (%) for the period 2080 - 2099 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_mam_ENDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Average year temperature (2021-2022) Average year temperature in °Celsius across the period 2021-2022. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_21_22_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_col_zaragoza_20210617 -74.8651063820499 7.579889039548307 -74.7899249680916 7.640072688469066 rs_for_asgm:tsm_col_zaragoza_20210617 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7496 7502 9569 9576 EPSG:4326:15 14993 15004 19139 19152 EPSG:4326:16 29986 30008 38278 38305 EPSG:4326:17 59972 60016 76556 76611 EPSG:4326:18 119945 120032 153113 153223 EPSG:4326:19 239890 240065 306227 306446 EPSG:4326:20 479781 480131 612455 612893 EPSG:4326:21 959562 960263 1224910 1225786 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 World Urban Areas - Esri -176.982559204102 -46.4931335449219 180.0 69.942024230957 grid_data_core:esri_urban_areas image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 0 31 EPSG:4326:5 3 24 0 63 EPSG:4326:6 7 48 1 127 EPSG:4326:7 14 97 2 255 EPSG:4326:8 28 194 4 511 EPSG:4326:9 57 388 8 1023 EPSG:4326:10 114 776 17 2047 EPSG:4326:11 228 1552 34 4095 EPSG:4326:12 456 3105 68 8191 EPSG:4326:13 912 6211 137 16383 EPSG:4326:14 1825 12423 274 32767 EPSG:4326:15 3651 24847 549 65535 EPSG:4326:16 7302 49695 1098 131071 EPSG:4326:17 14605 99391 2197 262143 EPSG:4326:18 29211 198782 4394 524287 EPSG:4326:19 58423 397565 8788 1048575 EPSG:4326:20 116846 795130 17577 2097151 EPSG:4326:21 233692 1590260 35155 4194303 EPSG:900913 Tree Cover Based on Satellite Data (University of Maryland - 2018) Source: The map is published on UNEP's South Sudan: First State of Environment and Outlook Report 2018 with a source identified as University of Maryland, 2018, no date indicated. The UNEP's report could be found <a href="https://www.unenvironment.org/resources/report/south-sudan-first-state-environment-and-outlook-report-2018" target="_blank"> here </a> <br><br>There are no reliable data on the extent of forests in South Sudan, since a detailed forest survey and inventory has never been carried out. Analyses based on remote sensing exist, which provide different estimates, but they have not been verified on the ground, so the accuracy of such products is unknown. The map is a satellite image that suggests the total area of tree cover in South Sudan is almost 20,000,000 ha (19,166,700 ha or 191,667 km2), which represents about 30 per cent of the country’s total land area (<a href="https://www.cbd.int/doc/world/ss/ss-nr-05-en.pdf" target="_blank"> MOE, 2015 </a>). This includes natural forests and woodlands, tropical moist forests on the hills, in the mountains and in the Nile-Congo watershed, and forests in National Parks and game reserves. 24.147119842068182 3.4562049048399057 36.000094869180025 12.24945847146474 MAPX_nd:SSD_treecover_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4017 4645 4915 EPSG:3857:14 7630 8034 9290 9830 EPSG:3857:15 15260 16069 18581 19660 EPSG:3857:16 30520 32138 37163 39321 EPSG:3857:17 61041 64276 74327 78643 EPSG:3857:18 122083 128553 148655 157286 EPSG:3857:19 244166 257107 297310 314572 EPSG:3857:20 488333 514214 594621 629145 EPSG:3857:21 976667 1028429 1189243 1258291 EPSG:3857:22 1953335 2056859 2378486 2516583 EPSG:3857:23 3906671 4113719 4756972 5033167 EPSG:3857:24 7813342 8227439 9513945 10066334 EPSG:3857:25 15626685 16454878 19027890 20132668 EPSG:3857:26 31253370 32909757 38055781 40265336 EPSG:3857:27 62506741 65819515 76111562 80530672 EPSG:3857:28 125013482 131639030 152223125 161061344 EPSG:3857:29 250026965 263278060 304446251 322122688 EPSG:3857:30 500053931 526556121 608892502 644245377 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 6 7 18 19 EPSG:4326:5 13 15 36 38 EPSG:4326:6 27 30 72 76 EPSG:4326:7 55 61 145 153 EPSG:4326:8 110 123 290 307 EPSG:4326:9 221 246 580 614 EPSG:4326:10 442 492 1161 1228 EPSG:4326:11 884 984 2322 2457 EPSG:4326:12 1769 1969 4645 4915 EPSG:4326:13 3538 3938 9290 9830 EPSG:4326:14 7077 7877 18581 19660 EPSG:4326:15 14154 15754 37163 39321 EPSG:4326:16 28308 31509 74327 78643 EPSG:4326:17 56616 63019 148655 157286 EPSG:4326:18 113232 126038 297310 314572 EPSG:4326:19 226464 252077 594621 629145 EPSG:4326:20 452929 504154 1189243 1258291 EPSG:4326:21 905859 1008308 2378486 2516583 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4017 4645 4915 EPSG:3857:14 7630 8034 9290 9830 EPSG:3857:15 15260 16069 18581 19660 EPSG:3857:16 30520 32138 37163 39321 EPSG:3857:17 61041 64276 74327 78643 EPSG:3857:18 122083 128553 148655 157286 EPSG:3857:19 244166 257107 297310 314572 EPSG:3857:20 488333 514214 594621 629145 EPSG:3857:21 976667 1028429 1189243 1258291 EPSG:3857:22 1953335 2056859 2378486 2516583 EPSG:3857:23 3906671 4113719 4756972 5033167 EPSG:3857:24 7813342 8227439 9513945 10066334 EPSG:3857:25 15626685 16454878 19027890 20132668 EPSG:3857:26 31253370 32909757 38055781 40265336 EPSG:3857:27 62506741 65819515 76111562 80530672 EPSG:3857:28 125013482 131639030 152223125 161061344 EPSG:3857:29 250026965 263278060 304446251 322122688 EPSG:3857:30 500053931 526556121 608892502 644245377 Combination Flood/Forest at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_flo_for6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 emodnet_open_maplibrary_mediseh_posidonia_opt -6.557323 29.437318067526018 42.965205499824044 47.30077599999999 Medicip:emodnet_open_maplibrary_mediseh_posidonia image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 30 39 EPSG:3857:7 44 53 61 79 EPSG:3857:8 89 106 123 158 EPSG:3857:9 179 212 246 317 EPSG:3857:10 358 424 493 634 EPSG:3857:11 717 848 986 1268 EPSG:3857:12 1435 1697 1973 2536 EPSG:3857:13 2871 3394 3946 5073 EPSG:3857:14 5742 6789 7893 10147 EPSG:3857:15 11485 13578 15787 20294 EPSG:3857:16 22970 27156 31574 40589 EPSG:3857:17 45940 54312 63148 81179 EPSG:3857:18 91880 108625 126297 162358 EPSG:3857:19 183761 217251 252594 324716 EPSG:3857:20 367523 434503 505188 649433 EPSG:3857:21 735046 869007 1010376 1298866 EPSG:3857:22 1470093 1738014 2020753 2597732 EPSG:3857:23 2940187 3476028 4041507 5195465 EPSG:3857:24 5880375 6952057 8083014 10390931 EPSG:3857:25 11760751 13904115 16166029 20781863 EPSG:3857:26 23521502 27808231 32332058 41563726 EPSG:3857:27 47043004 55616463 64664116 83127453 EPSG:3857:28 94086008 111232927 129328233 166254907 EPSG:3857:29 188172017 222465855 258656467 332509814 EPSG:3857:30 376344035 444931710 517312934 665019629 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 15 19 EPSG:4326:5 7 10 30 39 EPSG:4326:6 15 21 61 79 EPSG:4326:7 30 43 123 158 EPSG:4326:8 60 86 246 317 EPSG:4326:9 121 172 493 634 EPSG:4326:10 242 344 986 1268 EPSG:4326:11 485 689 1973 2536 EPSG:4326:12 971 1378 3946 5073 EPSG:4326:13 1943 2756 7893 10147 EPSG:4326:14 3886 5512 15787 20294 EPSG:4326:15 7773 11025 31574 40589 EPSG:4326:16 15546 22050 63148 81179 EPSG:4326:17 31092 44100 126297 162358 EPSG:4326:18 62185 88200 252594 324716 EPSG:4326:19 124370 176401 505188 649433 EPSG:4326:20 248741 352803 1010376 1298866 EPSG:4326:21 497482 705606 2020753 2597732 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 30 39 EPSG:3857:7 44 53 61 79 EPSG:3857:8 89 106 123 158 EPSG:3857:9 179 212 246 317 EPSG:3857:10 358 424 493 634 EPSG:3857:11 717 848 986 1268 EPSG:3857:12 1435 1697 1973 2536 EPSG:3857:13 2871 3394 3946 5073 EPSG:3857:14 5742 6789 7893 10147 EPSG:3857:15 11485 13578 15787 20294 EPSG:3857:16 22970 27156 31574 40589 EPSG:3857:17 45940 54312 63148 81179 EPSG:3857:18 91880 108625 126297 162358 EPSG:3857:19 183761 217251 252594 324716 EPSG:3857:20 367523 434503 505188 649433 EPSG:3857:21 735046 869007 1010376 1298866 EPSG:3857:22 1470093 1738014 2020753 2597732 EPSG:3857:23 2940187 3476028 4041507 5195465 EPSG:3857:24 5880375 6952057 8083014 10390931 EPSG:3857:25 11760751 13904115 16166029 20781863 EPSG:3857:26 23521502 27808231 32332058 41563726 EPSG:3857:27 47043004 55616463 64664116 83127453 EPSG:3857:28 94086008 111232927 129328233 166254907 EPSG:3857:29 188172017 222465855 258656467 332509814 EPSG:3857:30 376344035 444931710 517312934 665019629 Combination Landslide/Forest at 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62717323 67171186 73074651 EPSG:3857:28 116162067 125434646 134342373 146149302 EPSG:3857:29 232324135 250869292 268684747 292298604 EPSG:3857:30 464648270 501738584 537369494 584597209 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 3 8 8 EPSG:4326:4 5 6 16 17 EPSG:4326:5 11 13 32 34 EPSG:4326:6 23 27 64 69 EPSG:4326:7 47 55 128 139 EPSG:4326:8 94 111 256 278 EPSG:4326:9 189 222 512 557 EPSG:4326:10 378 445 1024 1115 EPSG:4326:11 756 890 2049 2230 EPSG:4326:12 1512 1781 4099 4460 EPSG:4326:13 3025 3563 8199 8920 EPSG:4326:14 6050 7127 16399 17840 EPSG:4326:15 12101 14254 32798 35680 EPSG:4326:16 24203 28509 65596 71361 EPSG:4326:17 48406 57018 131193 142723 EPSG:4326:18 96812 114037 262387 285447 EPSG:4326:19 193624 228074 524774 570895 EPSG:4326:20 387248 456148 1049549 1141791 EPSG:4326:21 774497 912296 2099099 2283582 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 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584597209 Word Land Cover FAO ? -180.0 -90.0 180.0 90.0 unep_storymap:WordLandCover image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:900913 Self-calibrating Palmer Drought Severity Index (scPDSI) 2014 (CRU) This layer shows the average values for 2014 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_14_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Yearly emissions of CO2 (short cycle organic Carbon) - 2000 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -55.59999999999249 179.99999999997954 76.5 wesr_climat:v60_CO2_org_short-cycle_C_2000_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 10 0 15 EPSG:3857:5 5 21 0 31 EPSG:3857:6 10 43 0 63 EPSG:3857:7 20 87 0 127 EPSG:3857:8 41 175 0 255 EPSG:3857:9 82 351 0 511 EPSG:3857:10 164 703 0 1023 EPSG:3857:11 328 1406 0 2047 EPSG:3857:12 656 2812 0 4095 EPSG:3857:13 1313 5624 0 8191 EPSG:3857:14 2627 11249 0 16383 EPSG:3857:15 5254 22499 0 32767 EPSG:3857:16 10509 44998 0 65535 EPSG:3857:17 21018 89997 0 131071 EPSG:3857:18 42036 179995 0 262143 EPSG:3857:19 84072 359991 0 524287 EPSG:3857:20 168145 719983 0 1048575 EPSG:3857:21 336291 1439967 0 2097151 EPSG:3857:22 672583 2879934 0 4194304 EPSG:3857:23 1345167 5759868 0 8388608 EPSG:3857:24 2690335 11519737 0 16777215 EPSG:3857:25 5380671 23039475 0 33554431 EPSG:3857:26 10761342 46078951 0 67108863 EPSG:3857:27 21522685 92157902 0 134217727 EPSG:3857:28 43045370 184315805 0 268435456 EPSG:3857:29 86090740 368631610 0 536870911 EPSG:3857:30 172181481 737263220 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 0 31 EPSG:4326:5 2 25 0 63 EPSG:4326:6 4 51 0 127 EPSG:4326:7 9 103 0 255 EPSG:4326:8 19 207 0 511 EPSG:4326:9 38 414 0 1023 EPSG:4326:10 76 828 0 2047 EPSG:4326:11 153 1656 0 4095 EPSG:4326:12 307 3313 0 8191 EPSG:4326:13 614 6626 0 16383 EPSG:4326:14 1228 13252 0 32767 EPSG:4326:15 2457 26505 0 65535 EPSG:4326:16 4915 53011 0 131071 EPSG:4326:17 9830 106022 0 262143 EPSG:4326:18 19660 212045 0 524287 EPSG:4326:19 39321 424090 0 1048575 EPSG:4326:20 78643 848181 0 2097151 EPSG:4326:21 157286 1696362 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 10 0 15 EPSG:3857:5 5 21 0 31 EPSG:3857:6 10 43 0 63 EPSG:3857:7 20 87 0 127 EPSG:3857:8 41 175 0 255 EPSG:3857:9 82 351 0 511 EPSG:3857:10 164 703 0 1023 EPSG:3857:11 328 1406 0 2047 EPSG:3857:12 656 2812 0 4095 EPSG:3857:13 1313 5624 0 8191 EPSG:3857:14 2627 11249 0 16383 EPSG:3857:15 5254 22499 0 32767 EPSG:3857:16 10509 44998 0 65535 EPSG:3857:17 21018 89997 0 131071 EPSG:3857:18 42036 179995 0 262143 EPSG:3857:19 84072 359991 0 524287 EPSG:3857:20 168145 719983 0 1048575 EPSG:3857:21 336291 1439967 0 2097152 EPSG:3857:22 672583 2879934 0 4194304 EPSG:3857:23 1345167 5759868 0 8388607 EPSG:3857:24 2690335 11519737 0 16777215 EPSG:3857:25 5380671 23039475 0 33554431 EPSG:3857:26 10761342 46078951 0 67108863 EPSG:3857:27 21522685 92157902 0 134217728 EPSG:3857:28 43045370 184315805 0 268435455 EPSG:3857:29 86090740 368631610 0 536870911 EPSG:3857:30 172181481 737263220 0 1073741824 Organic Pollution (pesticides) 2008 - KNB Pesticides were used as a proxy measure for organic pollution. Input data are from FAO statistics published in the time period 2003-2006. Missing pesticide values were filled using a linear regression model of pesticides as a function of fertilizers (gaps: N=69; regression: R2 = 0.72) when fertilizer data were available or agricultural GDP (gaps: N=22; regression: R2 = 0.82) when not. These country-level average pesticides values were then dasymetrically distributed over a country’s landscape using global land cover data from 2005. Finally, spread of the driver values into coastal waters at each pour point was modelled with a cost-path surface on the basis of a decay function that assigns a fixed amount of the driver (0.5% of the value in the previous cell) in the initial cell and then evenly distributes the remaining amount of driver in all adjacent and ‘unvisited’ cells, repeated until a minimum threshold (0.05% of global maximum) is reached. This approach to modelling river plumes is diffusive and so allows drivers to wrap around headlands and islands. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS." -179.99999948447567 -57.923325435334434 179.99443435918158 84.90643464931345 unea_pollution:08_plumes_pest_halpern_KNB_WGS84 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 44 0 63 EPSG:3857:7 0 89 0 127 EPSG:3857:8 1 178 0 255 EPSG:3857:9 2 357 0 511 EPSG:3857:10 4 715 0 1023 EPSG:3857:11 9 1430 0 2047 EPSG:3857:12 18 2860 0 4095 EPSG:3857:13 37 5721 0 8191 EPSG:3857:14 75 11442 0 16383 EPSG:3857:15 150 22885 0 32767 EPSG:3857:16 300 45770 0 65534 EPSG:3857:17 601 91541 0 131069 EPSG:3857:18 1203 183083 0 262139 EPSG:3857:19 2407 366167 0 524279 EPSG:3857:20 4815 732334 0 1048559 EPSG:3857:21 9631 1464668 0 2097119 EPSG:3857:22 19262 2929337 0 4194239 EPSG:3857:23 38524 5858675 0 8388478 EPSG:3857:24 77049 11717351 0 16776956 EPSG:3857:25 154098 23434703 0 33553913 EPSG:3857:26 308196 46869407 0 67107826 EPSG:3857:27 616393 93738815 0 134215652 EPSG:3857:28 1232786 187477630 0 268431305 EPSG:3857:29 2465573 374955260 0 536862611 EPSG:3857:30 4931146 749910520 1 1073725223 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 1 52 0 127 EPSG:4326:7 3 105 0 255 EPSG:4326:8 7 210 0 511 EPSG:4326:9 14 420 0 1023 EPSG:4326:10 28 841 0 2047 EPSG:4326:11 57 1683 0 4095 EPSG:4326:12 115 3366 0 8191 EPSG:4326:13 231 6732 0 16383 EPSG:4326:14 463 13464 0 32767 EPSG:4326:15 927 26928 0 65534 EPSG:4326:16 1854 53857 0 131069 EPSG:4326:17 3709 107714 0 262139 EPSG:4326:18 7418 215428 0 524279 EPSG:4326:19 14836 430857 0 1048559 EPSG:4326:20 29672 861715 0 2097119 EPSG:4326:21 59344 1723431 0 4194239 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 22 0 31 EPSG:900913:6 0 44 0 63 EPSG:900913:7 0 89 0 127 EPSG:900913:8 1 178 0 255 EPSG:900913:9 2 357 0 511 EPSG:900913:10 4 715 0 1023 EPSG:900913:11 9 1430 0 2047 EPSG:900913:12 18 2860 0 4095 EPSG:900913:13 37 5721 0 8191 EPSG:900913:14 75 11442 0 16383 EPSG:900913:15 150 22885 0 32767 EPSG:900913:16 300 45770 0 65534 EPSG:900913:17 601 91541 0 131069 EPSG:900913:18 1203 183083 0 262139 EPSG:900913:19 2407 366167 0 524279 EPSG:900913:20 4815 732334 0 1048559 EPSG:900913:21 9631 1464668 0 2097119 EPSG:900913:22 19262 2929337 0 4194239 EPSG:900913:23 38524 5858675 0 8388478 EPSG:900913:24 77049 11717351 0 16776956 EPSG:900913:25 154098 23434703 0 33553913 EPSG:900913:26 308196 46869407 0 67107826 EPSG:900913:27 616393 93738815 0 134215652 EPSG:900913:28 1232786 187477630 0 268431305 EPSG:900913:29 2465573 374955260 0 536862611 EPSG:900913:30 4931146 749910520 1 1073725223 Kerala Flood 25 Years RP - Historical Kerala State flood hazard map - Historical. Maximum expected flood event water height in a 25 years return period, expressed in cm. 74.85875 8.25375 77.49291666666667 12.842916666666673 ECO-DRR:Kerala_Flood_25_Yrs_Historical image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185582 187500 EPSG:4326:18 112368 119051 371164 375001 EPSG:4326:19 224736 238103 742329 750002 EPSG:4326:20 449472 476206 1484659 1500004 EPSG:4326:21 898945 952412 2969319 3000009 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 Year precipitations 2021 - Reference - Central African Republic Total precipitations observed in 2021 in the Central African Republic. Reference layer. 14.41796031 2.218838752 27.470481388 11.013345383 cc_and_health:precip_2021_ref_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 RGI_Global This layer contains the Randolph Glacier Inventory (RGI) version 6 (released in July 2017), which is a global inventory of glacier outlines representative of the situation at the beginning of the XXIst century (see details in the detailed description mentioned hereafter). It is a subset of the Global Land Ice Measurements from Space initiative (GLIMS). The complete description of the Randolph Glacier Inventory (RGI) can be found here: http://www.glims.org/RGI/00_rgi60_TechnicalNote.pdf. The attribute table contains 22 fields for each glacier, including: a unique RGI code (RGIId); the corresponding GLIMS database code (GLIMSId); the date or date ranges of the source from which the outline was taken (BgnDate, EndDate), the majority being after 1998; the coordinates of a point representing the location of the glacier (CenLon, CenLat); the region (01Region) or sub-region (02Region) to which the glacier belongs; its area (Area) in km2; its minimum (Zmin), maximum (Zmax) and median (Zmed) elevation in meters; the Mean slope of the glacier surface (slope); the mean orientation (aspect) of the glacier; the length (Lmax) of the longest surface flowline of the glacier; the name of the glacier as well as several other specific fields. -179.93483169799998 -78.30914570999994 179.7511910390001 83.60812590700004 wesr_mountains:RGI_Global image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 1 27 0 31 EPSG:3857:6 2 55 0 63 EPSG:3857:7 5 110 0 127 EPSG:3857:8 10 220 0 255 EPSG:3857:9 20 441 0 511 EPSG:3857:10 41 883 0 1023 EPSG:3857:11 83 1766 0 2046 EPSG:3857:12 167 3533 0 4093 EPSG:3857:13 334 7067 1 8186 EPSG:3857:14 668 14134 2 16372 EPSG:3857:15 1336 28269 5 32745 EPSG:3857:16 2673 56539 11 65490 EPSG:3857:17 5346 113079 23 130981 EPSG:3857:18 10692 226159 47 261962 EPSG:3857:19 21385 452318 94 523925 EPSG:3857:20 42770 904636 189 1047851 EPSG:3857:21 85540 1809272 379 2095702 EPSG:3857:22 171080 3618544 759 4191405 EPSG:3857:23 342161 7237089 1518 8382810 EPSG:3857:24 684323 14474179 3037 16765620 EPSG:3857:25 1368646 28948359 6074 33531241 EPSG:3857:26 2737293 57896718 12148 67062482 EPSG:3857:27 5474586 115793437 24296 134124965 EPSG:3857:28 10949173 231586874 48592 268249930 EPSG:3857:29 21898346 463173748 97185 536499861 EPSG:3857:30 43796692 926347497 194371 1072999722 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 1 29 0 63 EPSG:4326:6 2 59 0 127 EPSG:4326:7 4 119 0 255 EPSG:4326:8 9 239 0 511 EPSG:4326:9 18 478 0 1023 EPSG:4326:10 36 957 0 2046 EPSG:4326:11 72 1914 0 4093 EPSG:4326:12 145 3829 1 8186 EPSG:4326:13 290 7659 2 16372 EPSG:4326:14 581 15319 5 32745 EPSG:4326:15 1163 30639 11 65490 EPSG:4326:16 2327 61279 23 130981 EPSG:4326:17 4654 122558 47 261962 EPSG:4326:18 9308 245117 94 523925 EPSG:4326:19 18617 490235 189 1047851 EPSG:4326:20 37235 980471 379 2095702 EPSG:4326:21 74470 1960943 759 4191405 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 1 27 0 31 EPSG:3857:6 2 55 0 63 EPSG:3857:7 5 110 0 127 EPSG:3857:8 10 220 0 255 EPSG:3857:9 20 441 0 511 EPSG:3857:10 41 883 0 1023 EPSG:3857:11 83 1766 0 2046 EPSG:3857:12 167 3533 0 4093 EPSG:3857:13 334 7067 1 8186 EPSG:3857:14 668 14134 2 16372 EPSG:3857:15 1336 28269 5 32745 EPSG:3857:16 2673 56539 11 65490 EPSG:3857:17 5346 113079 23 130981 EPSG:3857:18 10692 226159 47 261962 EPSG:3857:19 21385 452318 94 523925 EPSG:3857:20 42770 904636 189 1047851 EPSG:3857:21 85540 1809272 379 2095702 EPSG:3857:22 171080 3618544 759 4191405 EPSG:3857:23 342161 7237089 1518 8382810 EPSG:3857:24 684323 14474179 3037 16765620 EPSG:3857:25 1368646 28948359 6074 33531241 EPSG:3857:26 2737293 57896718 12148 67062482 EPSG:3857:27 5474586 115793437 24296 134124965 EPSG:3857:28 10949173 231586874 48592 268249930 EPSG:3857:29 21898346 463173748 97185 536499861 EPSG:3857:30 43796692 926347497 194371 1072999722 Population density in Dakar Senegal (2025) This layer shows the estimated population distribution for the Dakar region in 2025, based on the Global Human Settlement Layer (GHSL, open access). The dataset is provided as a raster at 100 m spatial resolution. Each pixel contains the estimated number of inhabitants living within a 100 m × 100 m cell. This gridded representation allows the analysis of population patterns and supports the derivation of population density values at different spatial scales. This layer serves as an input for the project, supporting the identification of areas where higher population concentrations may increase the susceptibility of illegal dumping sites. -17.574657994490252 14.62972698943294 -17.17229869382342 14.86844154301869 dakar_waste:popu_2025_Dakar image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 463 EPSG:3857:11 938 939 924 926 EPSG:3857:12 1876 1879 1848 1852 EPSG:3857:13 3753 3759 3696 3705 EPSG:3857:14 7507 7518 7392 7410 EPSG:3857:15 15015 15037 14784 14820 EPSG:3857:16 30030 30075 29568 29641 EPSG:3857:17 60060 60150 59137 59283 EPSG:3857:18 120121 120301 118274 118567 EPSG:3857:19 240243 240602 236549 237135 EPSG:3857:20 480486 481205 473098 474270 EPSG:3857:21 960972 962410 946196 948540 EPSG:3857:22 1921944 1924820 1892392 1897080 EPSG:3857:23 3843888 3849640 3784784 3794160 EPSG:3857:24 7687777 7699281 7569569 7588320 EPSG:3857:25 15375555 15398563 15139139 15176641 EPSG:3857:26 30751111 30797126 30278278 30353283 EPSG:3857:27 61502222 61594253 60556556 60706567 EPSG:3857:28 123004444 123188507 121113113 121413134 EPSG:3857:29 246008888 246377015 242226226 242826268 EPSG:3857:30 492017776 492754030 484452452 485652536 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 463 EPSG:4326:10 427 428 924 926 EPSG:4326:11 854 857 1848 1852 EPSG:4326:12 1709 1715 3696 3705 EPSG:4326:13 3419 3430 7392 7410 EPSG:4326:14 6838 6860 14784 14820 EPSG:4326:15 13677 13720 29568 29641 EPSG:4326:16 27354 27441 59137 59283 EPSG:4326:17 54709 54882 118274 118567 EPSG:4326:18 109418 109765 236549 237135 EPSG:4326:19 218836 219531 473098 474270 EPSG:4326:20 437673 439063 946196 948540 EPSG:4326:21 875346 878127 1892392 1897080 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 463 EPSG:3857:11 938 939 924 926 EPSG:3857:12 1876 1879 1848 1852 EPSG:3857:13 3753 3759 3696 3705 EPSG:3857:14 7507 7518 7392 7410 EPSG:3857:15 15015 15037 14784 14820 EPSG:3857:16 30030 30075 29568 29641 EPSG:3857:17 60060 60150 59137 59283 EPSG:3857:18 120121 120301 118274 118567 EPSG:3857:19 240243 240602 236549 237135 EPSG:3857:20 480486 481205 473098 474270 EPSG:3857:21 960972 962410 946196 948540 EPSG:3857:22 1921944 1924820 1892392 1897080 EPSG:3857:23 3843888 3849640 3784784 3794160 EPSG:3857:24 7687777 7699281 7569569 7588320 EPSG:3857:25 15375555 15398563 15139139 15176641 EPSG:3857:26 30751111 30797126 30278278 30353283 EPSG:3857:27 61502222 61594253 60556556 60706567 EPSG:3857:28 123004444 123188507 121113113 121413134 EPSG:3857:29 246008888 246377015 242226226 242826268 EPSG:3857:30 492017776 492754030 484452452 485652536 Precipitation Anomalies Apr-May-Jun_2016_(mm) - CHIRPS -19.125063083055668 -35.37238257858172 52.6296893492118 38.256795423617206 MAPX:CHIRPS_Anomaly_3-Monthly_Apr-May-Jun_2016_(mm) image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 1 2 3 5 EPSG:4326:3 2 5 7 10 EPSG:4326:4 4 11 14 20 EPSG:4326:5 9 22 28 41 EPSG:4326:6 18 44 57 82 EPSG:4326:7 36 89 114 165 EPSG:4326:8 73 178 228 330 EPSG:4326:9 147 356 457 661 EPSG:4326:10 294 713 915 1323 EPSG:4326:11 588 1426 1830 2646 EPSG:4326:12 1177 2852 3660 5293 EPSG:4326:13 2354 5705 7321 10587 EPSG:4326:14 4709 11411 14643 21174 EPSG:4326:15 9419 22823 29286 42348 EPSG:4326:16 18839 45646 58572 84697 EPSG:4326:17 37678 91293 117145 169395 EPSG:4326:18 75356 182586 234291 338791 EPSG:4326:19 150713 365173 468582 677583 EPSG:4326:20 301426 730347 937164 1355166 EPSG:4326:21 602852 1460694 1874328 2710332 EPSG:900913 Global Estimated Risk Index For Landslide Hazard Triggered By Precipitations This dataset includes an estimate of the global risk induced by landslide hazard triggered by precipitations. Unit is estimated risk index from 1 (low) to 5 (extreme). This product was designed by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: UNEP/GRID-Europe. -180.0 -90.0 180.0 90.0 wesr_risk:ls_risk image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Temperature averages (°C) 1986-2005 (RCP4.5) Temperatures averages in the reference period 1986-2005 based on the climate scenario RCP4.5. -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:tas_45_86_05 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 6 11 EPSG:4326:4 3 8 13 22 EPSG:4326:5 7 17 27 45 EPSG:4326:6 15 34 54 90 EPSG:4326:7 31 68 109 181 EPSG:4326:8 63 137 218 363 EPSG:4326:9 127 275 436 726 EPSG:4326:10 255 550 872 1453 EPSG:4326:11 510 1101 1745 2906 EPSG:4326:12 1021 2203 3490 5813 EPSG:4326:13 2043 4406 6980 11626 EPSG:4326:14 4086 8812 13960 23252 EPSG:4326:15 8173 17625 27921 46505 EPSG:4326:16 16347 35251 55843 93010 EPSG:4326:17 32695 70502 111687 186020 EPSG:4326:18 65390 141004 223375 372040 EPSG:4326:19 130780 282008 446751 744081 EPSG:4326:20 261561 564017 893503 1488162 EPSG:4326:21 523122 1128034 1787006 2976324 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 Spatial distribution of Drought risk Drought risk in Kédougou is manifested by the combination of a climatic phenomenon and local vulnerability that amplify its impacts on agriculture and livelihoods. Indeed, data from Think Hazard indicate that a water shortage, a direct consequence of marked variability in rainfall and rising temperatures, could occur with a probability of around 20% over the next ten years. Furthermore, the study by (Boissy et al., 2024) highlights that the degradation of vegetation cover, due in particular to intensive agricultural practices and mining expansion, weakens soils and reduces their water retention capacity, thus increasing the vulnerability of local systems. -13.239445601904379 12.307811091287101 -11.342383384900774 13.461068253039743 risk_southeast_senegal:drought_risk image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242357 244079 242862 245625 EPSG:3857:20 484714 488159 485725 491250 EPSG:3857:21 969428 976319 971450 982501 EPSG:3857:22 1938856 1952639 1942901 1965003 EPSG:3857:23 3877712 3905279 3885802 3930007 EPSG:3857:24 7755424 7810559 7771605 7860014 EPSG:3857:25 15510849 15621119 15543210 15720029 EPSG:3857:26 31021698 31242238 31086420 31440058 EPSG:3857:27 62043397 62484476 62172840 62880116 EPSG:3857:28 124086795 124968953 124345681 125760233 EPSG:3857:29 248173590 249937906 248691363 251520467 EPSG:3857:30 496347181 499875813 497382727 503040935 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491250 EPSG:4326:20 445871 452589 971450 982501 EPSG:4326:21 891743 905179 1942901 1965003 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242357 244079 242862 245625 EPSG:3857:20 484714 488159 485725 491250 EPSG:3857:21 969428 976319 971450 982501 EPSG:3857:22 1938856 1952639 1942901 1965003 EPSG:3857:23 3877712 3905279 3885802 3930007 EPSG:3857:24 7755424 7810559 7771605 7860014 EPSG:3857:25 15510849 15621119 15543210 15720029 EPSG:3857:26 31021698 31242238 31086420 31440058 EPSG:3857:27 62043397 62484476 62172840 62880116 EPSG:3857:28 124086795 124968953 124345681 125760233 EPSG:3857:29 248173590 249937906 248691363 251520467 EPSG:3857:30 496347181 499875813 497382727 503040935 Automn temperature change (°C) for the period 2080 - 2099 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_son_ENDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 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1108273 1317705 1376429 EPSG:3857:22 2140424 2216546 2635411 2752858 EPSG:3857:23 4280849 4433093 5270823 5505716 EPSG:3857:24 8561698 8866186 10541646 11011432 EPSG:3857:25 17123396 17732373 21083293 22022864 EPSG:3857:26 34246793 35464746 42166587 44045729 EPSG:3857:27 68493587 70929492 84333175 88091458 EPSG:3857:28 136987174 141858984 168666350 176182916 EPSG:3857:29 273974349 283717968 337332701 352365833 EPSG:3857:30 547948698 567435936 674665403 704731666 Average temperature of the 3 hottest months (1991-2020) Average temperature of the 3 hottest months per pixel in °Celsius across the period 1991-2020. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_20_3hottest_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_mambo_bado_20210520 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20210520 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 Spatial distribution of Extreme Heat risk In Kédougou, the risk of extreme heat is exacerbated by the interaction between increasing climate hazards and marked socioeconomic vulnerability. On the one hand, meteorological records (ANACIM, 2021) show that during the dry season, temperature peaks regularly exceeding 40°C occur, in line with regional warming trends (IPCC, 2021). On the other hand, local vulnerability is amplified by precarious socioeconomic and physical conditions. Furthermore, the study by Faye et al. (2021) conducted in Bandafassi, a commune of Kédougou, demonstrates that exposure to heat waves, defined here by the 90th percentile of minimum and maximum temperatures over three consecutive days, leads to a significant increase in daily mortality, particularly among women and people over 55 years of age. 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32 33 34 EPSG:3857:7 63 65 67 69 EPSG:3857:8 126 130 134 138 EPSG:3857:9 252 261 268 276 EPSG:3857:10 505 523 536 553 EPSG:3857:11 1010 1046 1073 1106 EPSG:3857:12 2021 2093 2146 2213 EPSG:3857:13 4043 4186 4293 4426 EPSG:3857:14 8086 8372 8587 8853 EPSG:3857:15 16173 16744 17175 17706 EPSG:3857:16 32346 33489 34350 35412 EPSG:3857:17 64692 66979 68701 70825 EPSG:3857:18 129385 133959 137403 141650 EPSG:3857:19 258771 267918 274807 283300 EPSG:3857:20 517543 535836 549615 566600 EPSG:3857:21 1035086 1071672 1099230 1133201 EPSG:3857:22 2070172 2143345 2198461 2266402 EPSG:3857:23 4140344 4286691 4396923 4532804 EPSG:3857:24 8280689 8573382 8793846 9065609 EPSG:3857:25 16561379 17146764 17587693 18131219 EPSG:3857:26 33122759 34293529 35175387 36262439 EPSG:3857:27 66245519 68587058 70350774 72524879 EPSG:3857:28 132491038 137174116 140701548 145049759 EPSG:3857:29 264982076 274348233 281403096 290099518 EPSG:3857:30 529964152 548696467 562806193 580199037 Winter precipitations change (%) for the period 2020 - 2039 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_djf_NEARREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Combination Tsunami/Mangroves at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_man9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Climate risk based on Novel and Disappearing Climates 2050 SRES A2 Climate risk data are used to identify climate stability or scope for climate-adaptation focused interventions. The recent datasets from Tabor et al. 2018 which assess climate change exposure using downscaled climate projections with the SRES A2 emissions scenario was selected for ranking climate risk, combining two measures of radically changing climates. Tabor highlight (a) the threat status of the climate, assigning high values where the late 20th century climates will cease to exist anywhere in the world and therefore this climate space is very threatened as it may be disappearing from the world; and (b) the distance from current climates, with high values indicating areas with novel climates not currently experienced anywhere in the world, and where there is high uncertainty on future species communities. Climate risk values are grouped by deciles whereby landscapes with moderate climate risk are deemed most appropriate for selection, in that there are some adaptation challenges that the LWP intervention may be able to tackle. John W. Williams, Karyn Tabor. (2018). Novel and Disappearing Climates 2050 SRES A2 (Version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1559299 Support for this project was provided by Conservation International, the Land Tenure Center at the University of Wisconsin, the Center for Climatic Research at the University of Wisconsin, and the Environment Program at the University of Wisconsin–Madison. This research has been funded in part by the Walton Family Foundation, the Gordon and Betty Moore Foundation, and a gift from Betty and Gordon Moore. -180.0 -59.08371450000001 179.9996665 83.66628549999999 LWP:novel_disp_0to1_normalisedq_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 45 0 63 EPSG:3857:7 5 90 0 127 EPSG:3857:8 10 180 0 255 EPSG:3857:9 20 360 0 511 EPSG:3857:10 40 721 0 1023 EPSG:3857:11 80 1442 0 2047 EPSG:3857:12 161 2885 0 4095 EPSG:3857:13 322 5771 0 8191 EPSG:3857:14 644 11543 0 16383 EPSG:3857:15 1288 23087 0 32767 EPSG:3857:16 2577 46175 0 65535 EPSG:3857:17 5155 92350 0 131071 EPSG:3857:18 10310 184701 0 262143 EPSG:3857:19 20620 369402 0 524287 EPSG:3857:20 41241 738804 0 1048575 EPSG:3857:21 82483 1477609 0 2097150 EPSG:3857:22 164966 2955218 0 4194300 EPSG:3857:23 329932 5910436 0 8388600 EPSG:3857:24 659865 11820872 0 16777200 EPSG:3857:25 1319731 23641744 0 33554400 EPSG:3857:26 2639463 47283489 0 67108801 EPSG:3857:27 5278927 94566979 0 134217603 EPSG:3857:28 10557855 189133958 0 268435207 EPSG:3857:29 21115710 378267916 0 536870414 EPSG:3857:30 42231421 756535833 0 1073740829 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 9 212 0 511 EPSG:4326:9 18 424 0 1023 EPSG:4326:10 36 848 0 2047 EPSG:4326:11 72 1696 0 4095 EPSG:4326:12 144 3392 0 8191 EPSG:4326:13 288 6784 0 16383 EPSG:4326:14 576 13569 0 32767 EPSG:4326:15 1153 27139 0 65535 EPSG:4326:16 2306 54279 0 131071 EPSG:4326:17 4612 108559 0 262143 EPSG:4326:18 9224 217118 0 524287 EPSG:4326:19 18448 434237 0 1048575 EPSG:4326:20 36896 868475 0 2097150 EPSG:4326:21 73793 1736951 0 4194300 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 45 0 63 EPSG:3857:7 5 90 0 127 EPSG:3857:8 10 180 0 255 EPSG:3857:9 20 360 0 511 EPSG:3857:10 40 721 0 1023 EPSG:3857:11 80 1442 0 2047 EPSG:3857:12 161 2885 0 4095 EPSG:3857:13 322 5771 0 8191 EPSG:3857:14 644 11543 0 16383 EPSG:3857:15 1288 23087 0 32767 EPSG:3857:16 2577 46175 0 65535 EPSG:3857:17 5155 92350 0 131071 EPSG:3857:18 10310 184701 0 262143 EPSG:3857:19 20620 369402 0 524287 EPSG:3857:20 41241 738804 0 1048575 EPSG:3857:21 82483 1477609 0 2097150 EPSG:3857:22 164966 2955218 0 4194300 EPSG:3857:23 329932 5910436 0 8388600 EPSG:3857:24 659865 11820872 0 16777200 EPSG:3857:25 1319731 23641744 0 33554400 EPSG:3857:26 2639463 47283489 0 67108801 EPSG:3857:27 5278927 94566979 0 134217603 EPSG:3857:28 10557855 189133958 0 268435207 EPSG:3857:29 21115710 378267916 0 536870414 EPSG:3857:30 42231421 756535833 0 1073740829 Fire vulnerability recurrence map between 1995 and 2024 Vulnerability to forest fires in the Kédougou region was analyzed through three key indicators: cultivated areas, population density and wooded savannahs. These elements were selected for their ability to reflect the interactions between human activities, natural ecosystems and fire propagation mechanisms. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:burn_vulnerability image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 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3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 mafaru_2024 73.43606112249947 5.8013253113891965 73.51117370374618 5.859057400767437 sand:mafaru_2024 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 15 15 22 22 EPSG:3857:6 30 30 45 45 EPSG:3857:7 61 61 90 90 EPSG:3857:8 123 123 180 180 EPSG:3857:9 247 247 360 360 EPSG:3857:10 495 495 720 721 EPSG:3857:11 990 990 1441 1442 EPSG:3857:12 1981 1981 2883 2884 EPSG:3857:13 3962 3963 5767 5768 EPSG:3857:14 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184601 EPSG:3857:19 253596 253680 369093 369202 EPSG:3857:20 507192 507361 738186 738404 EPSG:3857:21 1014384 1014722 1476372 1476809 EPSG:3857:22 2028769 2029445 2952744 2953619 EPSG:3857:23 4057539 4058891 5905488 5907238 EPSG:3857:24 8115078 8117783 11810976 11814476 EPSG:3857:25 16230157 16235566 23621952 23628953 EPSG:3857:26 32460315 32471133 47243905 47257907 EPSG:3857:27 64920631 64942267 94487811 94515815 EPSG:3857:28 129841263 129884535 188975623 189031631 EPSG:3857:29 259682527 259769071 377951247 378063263 EPSG:3857:30 519365055 519538143 755902495 756126527 International Boundaries Polygons Level 0 - Natural Earth -180.0 -90.0 180.0 84.5022735595703 grid_data_core:ne_10m_admin_0_countries image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 7 255 0 511 EPSG:4326:9 15 511 0 1023 EPSG:4326:10 31 1023 0 2047 EPSG:4326:11 62 2047 0 4095 EPSG:4326:12 125 4095 0 8191 EPSG:4326:13 250 8191 0 16383 EPSG:4326:14 500 16383 0 32767 EPSG:4326:15 1000 32767 0 65535 EPSG:4326:16 2001 65535 0 131071 EPSG:4326:17 4003 131071 0 262143 EPSG:4326:18 8006 262143 0 524287 EPSG:4326:19 16013 524287 0 1048575 EPSG:4326:20 32026 1048575 0 2097151 EPSG:4326:21 64053 2097151 0 4194303 EPSG:900913 Self-calibrating Palmer Drought Severity Index (scPDSI) 2011-2020 (CRU) This layer shows the average values over the 2011 to 2020 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_11_20_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Yearly emissions of CH4 - 1970 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -88.79999999998984 179.99999999997954 90.0 wesr_climat:v60_CH4_1970_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 254 0 511 EPSG:4326:9 0 508 0 1023 EPSG:4326:10 0 1017 0 2047 EPSG:4326:11 0 2034 0 4095 EPSG:4326:12 0 4068 0 8191 EPSG:4326:13 0 8137 0 16383 EPSG:4326:14 0 16274 0 32767 EPSG:4326:15 0 32549 0 65535 EPSG:4326:16 0 65099 0 131071 EPSG:4326:17 0 130198 0 262143 EPSG:4326:18 0 260396 0 524287 EPSG:4326:19 0 520792 0 1048575 EPSG:4326:20 0 1041585 0 2097151 EPSG:4326:21 0 2083170 0 4194303 EPSG:900913 EPSG:3857_512 Human Footprint 1993 (Terrestrial) Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11. Available at: http://www.nature.com/doifinder/10.1038/ncomms12558 [Accessed October 18, 2016]. -179.99999995447251 -65.25013301721049 179.99661098079287 89.89762321520959 MapX_UNDP:hfp1993 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12147 0 16383 EPSG:3857:15 0 24294 0 32767 EPSG:3857:16 0 48589 0 65535 EPSG:3857:17 0 97178 0 131070 EPSG:3857:18 0 194356 0 262141 EPSG:3857:19 0 388713 0 524283 EPSG:3857:20 0 777426 0 1048566 EPSG:3857:21 0 1554852 0 2097132 EPSG:3857:22 -1 3109705 0 4194264 EPSG:3857:23 -1 6219410 0 8388529 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image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 9 EPSG:3857:5 13 15 17 19 EPSG:3857:6 27 30 35 38 EPSG:3857:7 55 60 71 77 EPSG:3857:8 111 121 143 155 EPSG:3857:9 222 243 286 311 EPSG:3857:10 444 487 572 622 EPSG:3857:11 888 974 1144 1244 EPSG:3857:12 1776 1949 2288 2489 EPSG:3857:13 3553 3899 4577 4978 EPSG:3857:14 7107 7799 9155 9956 EPSG:3857:15 14215 15599 18310 19913 EPSG:3857:16 28431 31199 36621 39827 EPSG:3857:17 56863 62399 73243 79654 EPSG:3857:18 113726 124798 146486 159308 EPSG:3857:19 227452 249597 292973 318617 EPSG:3857:20 454905 499195 585947 637235 EPSG:3857:21 909811 998390 1171894 1274471 EPSG:3857:22 1819622 1996781 2343788 2548943 EPSG:3857:23 3639245 3993562 4687577 5097887 EPSG:3857:24 7278490 7987125 9375154 10195774 EPSG:3857:25 14556981 15974250 18750308 20391549 EPSG:3857:26 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300004929 326264784 EPSG:3857:30 465823393 511176016 600009858 652529569 Mean temperatures 2020 - Central African Republic Mean observed temperatures in 2020 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2020_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 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2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Tropical cyclone surge hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:cs_phex image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Bhutan - Water Yield 2030 Layer received from TEEB partner in Bhutan Q2 2020 88.737534326 26.685110159 92.146924212 28.245314268 TEEB:BHU_Water_yield_2030 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 3 EPSG:3857:3 3 3 5 6 EPSG:3857:4 6 6 11 12 EPSG:3857:5 13 13 23 24 EPSG:3857:6 26 27 47 48 EPSG:3857:7 53 54 95 96 EPSG:3857:8 107 108 191 193 EPSG:3857:9 214 216 382 387 EPSG:3857:10 428 433 764 774 EPSG:3857:11 856 866 1528 1548 EPSG:3857:12 1712 1732 3057 3096 EPSG:3857:13 3425 3465 6115 6192 EPSG:3857:14 6851 6931 12230 12385 EPSG:3857:15 13702 13862 24461 24771 EPSG:3857:16 27404 27724 48922 49542 EPSG:3857:17 54808 55448 97844 99085 EPSG:3857:18 109616 110897 195688 198171 EPSG:3857:19 219233 221794 391377 396342 EPSG:3857:20 438467 443589 782754 792685 EPSG:3857:21 876934 887178 1565509 1585370 EPSG:3857:22 1753869 1774357 3131019 3170741 EPSG:3857:23 3507738 3548714 6262038 6341482 EPSG:3857:24 7015477 7097428 12524076 12682965 EPSG:3857:25 14030955 14194856 25048153 25365931 EPSG:3857:26 28061910 28389713 50096307 50731863 EPSG:3857:27 56123821 56779427 100192614 101463727 EPSG:3857:28 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south_africa_remote_site_screening_res50 16.447713889000067 -46.979109999999956 38.00071388900007 -22.126609999999957 mapx_chemobs:south_africa_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 5 4 4 EPSG:3857:4 9 10 8 9 EPSG:3857:5 18 20 17 19 EPSG:3857:6 36 41 34 38 EPSG:3857:7 72 82 69 77 EPSG:3857:8 144 165 139 155 EPSG:3857:9 288 331 279 310 EPSG:3857:10 576 663 558 620 EPSG:3857:11 1153 1327 1117 1240 EPSG:3857:12 2306 2654 2235 2480 EPSG:3857:13 4612 5309 4470 4960 EPSG:3857:14 9225 10619 8940 9921 EPSG:3857:15 18450 21239 17881 19842 EPSG:3857:16 36900 42479 35762 39685 EPSG:3857:17 73800 84959 71524 79371 EPSG:3857:18 147600 169918 143048 158743 EPSG:3857:19 295200 339837 286097 317486 EPSG:3857:20 590400 679675 572195 634973 EPSG:3857:21 1180801 1359350 1144390 1269946 EPSG:3857:22 2361603 2718700 2288781 2539892 EPSG:3857:23 4723206 5437400 4577563 5079784 EPSG:3857:24 9446412 10874801 9155127 10159569 EPSG:3857:25 18892825 21749603 18310254 20319139 EPSG:3857:26 37785651 43499207 36620508 40638278 EPSG:3857:27 75571302 86998415 73241016 81276557 EPSG:3857:28 151142605 173996831 146482032 162553114 EPSG:3857:29 302285210 347993663 292964064 325106228 EPSG:3857:30 604570421 695987326 585928129 650212456 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 3 4 4 EPSG:4326:3 4 6 8 9 EPSG:4326:4 9 12 17 19 EPSG:4326:5 19 24 34 38 EPSG:4326:6 39 48 69 77 EPSG:4326:7 79 97 139 155 EPSG:4326:8 159 194 279 310 EPSG:4326:9 318 389 558 620 EPSG:4326:10 637 779 1117 1240 EPSG:4326:11 1275 1558 2235 2480 EPSG:4326:12 2551 3117 4470 4960 EPSG:4326:13 5103 6234 8940 9921 EPSG:4326:14 10206 12468 17881 19842 EPSG:4326:15 20412 24936 35762 39685 EPSG:4326:16 40824 49872 71524 79371 EPSG:4326:17 81648 99745 143048 158743 EPSG:4326:18 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EPSG:3857:25 18892825 21749603 18310254 20319139 EPSG:3857:26 37785651 43499207 36620508 40638278 EPSG:3857:27 75571302 86998415 73241016 81276557 EPSG:3857:28 151142605 173996831 146482032 162553114 EPSG:3857:29 302285210 347993663 292964064 325106228 EPSG:3857:30 604570421 695987326 585928129 650212456 Flood vulnerability recurrence map between 1995 and 2024 In the Kédougou region, cultivated, urbanized, populated, and low-lying areas are more vulnerable to flooding for several interrelated reasons. On the one hand, soil sealing in urbanized areas and intensive agriculture significantly reduce water infiltration capacity, resulting in significant surface runoff during extreme rainfall events. On the other hand, high population density increases pressure on water resources and drainage infrastructure, which is often insufficient to channel the volume of water during heavy rains. -13.24387253466399 12.296396064761913 -11.335905049138686 13.472511381334042 risk_southeast_senegal:flood_vulnerability image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60584 61024 60714 61408 EPSG:3857:18 121169 122048 121428 122817 EPSG:3857:19 242339 244097 242856 245634 EPSG:3857:20 484679 488194 485712 491269 EPSG:3857:21 969359 976388 971424 982539 EPSG:3857:22 1938719 1952776 1942849 1965079 EPSG:3857:23 3877438 3905552 3885699 3930158 EPSG:3857:24 7754876 7811104 7771398 7860316 EPSG:3857:25 15509752 15622208 15542797 15720633 EPSG:3857:26 31019505 31244416 31085595 31441266 EPSG:3857:27 62039010 62488832 62171190 62882532 EPSG:3857:28 124078021 124977665 124342380 125765064 EPSG:3857:29 248156042 249955330 248684761 251530129 EPSG:3857:30 496312085 499910660 497369523 503060258 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 221 474 479 EPSG:4326:10 435 442 948 959 EPSG:4326:11 870 884 1897 1919 EPSG:4326:12 1741 1768 3794 3838 EPSG:4326:13 3482 3536 7589 7676 EPSG:4326:14 6965 7072 15178 15352 EPSG:4326:15 13931 14145 30357 30704 EPSG:4326:16 27862 28291 60714 61408 EPSG:4326:17 55725 56582 121428 122817 EPSG:4326:18 111451 113164 242856 245634 EPSG:4326:19 222902 226328 485712 491269 EPSG:4326:20 445804 452656 971424 982539 EPSG:4326:21 891609 905312 1942849 1965079 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60584 61024 60714 61408 EPSG:3857:18 121169 122048 121428 122817 EPSG:3857:19 242339 244097 242856 245634 EPSG:3857:20 484679 488194 485712 491269 EPSG:3857:21 969359 976388 971424 982539 EPSG:3857:22 1938719 1952776 1942849 1965079 EPSG:3857:23 3877438 3905552 3885699 3930158 EPSG:3857:24 7754876 7811104 7771398 7860316 EPSG:3857:25 15509752 15622208 15542797 15720633 EPSG:3857:26 31019505 31244416 31085595 31441266 EPSG:3857:27 62039010 62488832 62171190 62882532 EPSG:3857:28 124078021 124977665 124342380 125765064 EPSG:3857:29 248156042 249955330 248684761 251530129 EPSG:3857:30 496312085 499910660 497369523 503060258 Mean predicted temperatures 2023 - Reference - Central African Republic Mean predicted temperatures in 2023 in the Central African Republic. Reference layer. 14.373044546 2.1559566819999993 27.488447694 11.049277995 cc_and_health:mean_temp_predict_2023_ref_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Yearly emissions of CO2 (excluding short cycle organic Carbon) - 2010 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -85.59999999999002 179.99999999997954 90.0 wesr_climat:v60_CO2_excl_short-cycle_org_C_2010_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 62 0 127 EPSG:4326:7 0 124 0 255 EPSG:4326:8 0 249 0 511 EPSG:4326:9 0 499 0 1023 EPSG:4326:10 0 998 0 2047 EPSG:4326:11 0 1997 0 4095 EPSG:4326:12 0 3995 0 8191 EPSG:4326:13 0 7991 0 16383 EPSG:4326:14 0 15983 0 32767 EPSG:4326:15 0 31967 0 65535 EPSG:4326:16 0 63934 0 131071 EPSG:4326:17 0 127868 0 262143 EPSG:4326:18 0 255736 0 524287 EPSG:4326:19 0 511472 0 1048575 EPSG:4326:20 0 1022944 0 2097151 EPSG:4326:21 0 2045888 0 4194303 EPSG:900913 EPSG:3857_512 Crop Suitability 2071-2100 This dataset show general agricultural suitability at a spatial resolution of 30 arc-second (~1km), considering rainfed conditions and irrigation on currently irrigated areas. The agricultural suitability represents for each pixel the maximum suitability value of considered 16 plants, including: We show a subset of the data that covers three time periods (1981-2010, 2011-2040, 2071-2100), as well as changes in agricultural suitability over the same periods.<br><br>For futher details see: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107522">Zabel F., Putzenlechner B., Mauser W. (2014): Global agricultural land resources – a high resolution suitability evaluation and its perspectives until 2100 under climate change conditions</a><br/><br>Data can also be downloaded from <a href="http://geoportal-glues.ufz.de/stories/globalsuitability.html">here</a>.<br/> -180.0 -60.0 180.0 90.0 MapX_UNDP:overall_cropsuit_i_2071-2100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Annual Precipitation [mm/year] (2041-2060) RCP4.5 - CIMP5 Accumulated precipitation amount over 1 year [mm/year] for the period 2041-2060 based on RCP4.5. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_bio_mon_ACCESS1-0_rcp45_r1i1p1_g025.nc_12_2041-2060_V1.2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 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78231854 79134523 77179349 78091284 EPSG:3857:28 156463709 158269047 154358699 156182569 EPSG:3857:29 312927418 316538094 308717399 312365139 EPSG:3857:30 625854836 633076189 617434799 624730278 Spectral Acceleration 0.5 Sec 2475 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_05_s_2475_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average year precipitations anomalies (2011-2020) against 1901-1920 Average year precipitations anomalies in mm across the period 2011-2020 calculated over the average precipitations per year in the period 1901-1920 (as close as possible to the pre-industrial era). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_11_20_anom_1901_1920 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Satellite Mogadisho Urban Growth 2009 Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2009-03-14. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov. 45.195394649846214 1.955229029551538 45.47923060483454 2.141476613353127 MAPX:Mogadisho_Landsat7_20090314-531 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 10 10 EPSG:3857:5 15 15 20 20 EPSG:3857:6 31 31 40 40 EPSG:3857:7 63 63 80 80 EPSG:3857:8 126 126 160 160 EPSG:3857:9 252 253 320 320 EPSG:3857:10 505 506 640 641 EPSG:3857:11 1011 1012 1281 1282 EPSG:3857:12 2023 2025 2562 2565 EPSG:3857:13 4047 4051 5124 5130 EPSG:3857:14 8094 8102 10248 10261 EPSG:3857:15 16189 16205 20497 20523 EPSG:3857:16 32378 32411 40995 41047 EPSG:3857:17 64756 64823 81991 82094 EPSG:3857:18 129512 129647 163982 164188 EPSG:3857:19 259024 259295 327964 328377 EPSG:3857:20 518049 518591 655929 656755 EPSG:3857:21 1036098 1037183 1311858 1313511 EPSG:3857:22 2072196 2074367 2623716 2627023 EPSG:3857:23 4144392 4148735 5247433 5254046 EPSG:3857:24 8288784 8297470 10494866 10508093 EPSG:3857:25 16577569 16594940 20989732 21016187 EPSG:3857:26 33155138 33189880 41979464 42032375 EPSG:3857:27 66310277 66379760 83958928 84064750 EPSG:3857:28 132620555 132759520 167917856 168129500 EPSG:3857:29 265241110 265519041 335835713 336259000 EPSG:3857:30 530482221 531038082 671671427 672518000 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 10 10 EPSG:4326:4 7 7 20 20 EPSG:4326:5 15 15 40 40 EPSG:4326:6 31 31 80 80 EPSG:4326:7 62 62 160 160 EPSG:4326:8 124 125 320 320 EPSG:4326:9 249 250 640 641 EPSG:4326:10 499 500 1281 1282 EPSG:4326:11 999 1001 2562 2565 EPSG:4326:12 1999 2003 5124 5130 EPSG:4326:13 3998 4007 10248 10261 EPSG:4326:14 7997 8014 20497 20523 EPSG:4326:15 15994 16028 40995 41047 EPSG:4326:16 31988 32056 81991 82094 EPSG:4326:17 63976 64112 163982 164188 EPSG:4326:18 127953 128224 327964 328377 EPSG:4326:19 255906 256448 655929 656755 EPSG:4326:20 511812 512897 1311858 1313511 EPSG:4326:21 1023625 1025795 2623716 2627023 EPSG:900913 Peru_ACD Layer provided by Ministry of Environment of Peru. To create a map of aboveground carbon density (ACD) at one-hectare resolution, we integrated airborne Light Detection and Ranging (LiDAR) technology, a new field plot inventory network, freely available satellite imagery, and geostatistical scaling techniques. 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of the monthly mean temperatures [standard deviation] for the period 2041-2060 based on RCP4.5. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. 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79134739 77179459 78090766 EPSG:3857:28 156463917 158269478 154358919 156181533 EPSG:3857:29 312927834 316538957 308717838 312363066 EPSG:3857:30 625855668 633077915 617435676 624726132 Woodland total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:forestwlkm2a image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Self-calibrating Palmer Drought Severity Index (scPDSI) 2015 (CRU) This layer shows the average values for 2015 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_15_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 sen_wb_buffer_100m -17.528482082499128 12.295406935298832 -11.332683451847313 16.69730488090794 mapx_chemobs:sen_wb_buffer_100m image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 28 29 28 29 EPSG:3857:7 57 59 57 59 EPSG:3857:8 115 119 115 119 EPSG:3857:9 231 238 231 239 EPSG:3857:10 463 476 462 479 EPSG:3857:11 927 953 924 959 EPSG:3857:12 1855 1907 1848 1919 EPSG:3857:13 3710 3814 3697 3838 EPSG:3857:14 7421 7628 7394 7676 EPSG:3857:15 14842 15256 14788 15352 EPSG:3857:16 29684 30512 29577 30704 EPSG:3857:17 59368 61024 59154 61409 EPSG:3857:18 118737 122049 118308 122819 EPSG:3857:19 237475 244098 236616 245639 EPSG:3857:20 474950 488196 473232 491279 EPSG:3857:21 949900 976393 946465 982558 EPSG:3857:22 1899800 1952787 1892930 1965116 EPSG:3857:23 3799601 3905575 3785860 3930233 EPSG:3857:24 7599203 7811151 7571721 7860466 EPSG:3857:25 15198406 15622302 15143443 15720933 EPSG:3857:26 30396812 31244604 30286886 31441866 EPSG:3857:27 60793624 62489209 60573772 62883733 EPSG:3857:28 121587248 124978419 121147544 125767466 EPSG:3857:29 243174496 249956839 242295088 251534933 EPSG:3857:30 486348993 499913679 484590177 503069866 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 29 EPSG:4326:6 26 27 57 59 EPSG:4326:7 52 55 115 119 EPSG:4326:8 104 110 231 239 EPSG:4326:9 208 221 462 479 EPSG:4326:10 417 442 924 959 EPSG:4326:11 834 884 1848 1919 EPSG:4326:12 1668 1768 3697 3838 EPSG:4326:13 3336 3536 7394 7676 EPSG:4326:14 6672 7072 14788 15352 EPSG:4326:15 13344 14145 29577 30704 EPSG:4326:16 26688 28291 59154 61409 EPSG:4326:17 53377 56582 118308 122819 EPSG:4326:18 106754 113165 236616 245639 EPSG:4326:19 213509 226331 473232 491279 EPSG:4326:20 427019 452662 946465 982558 EPSG:4326:21 854038 905324 1892930 1965116 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 28 29 28 29 EPSG:3857:7 57 59 57 59 EPSG:3857:8 115 119 115 119 EPSG:3857:9 231 238 231 239 EPSG:3857:10 463 476 462 479 EPSG:3857:11 927 953 924 959 EPSG:3857:12 1855 1907 1848 1919 EPSG:3857:13 3710 3814 3697 3838 EPSG:3857:14 7421 7628 7394 7676 EPSG:3857:15 14842 15256 14788 15352 EPSG:3857:16 29684 30512 29577 30704 EPSG:3857:17 59368 61024 59154 61409 EPSG:3857:18 118737 122049 118308 122819 EPSG:3857:19 237475 244098 236616 245639 EPSG:3857:20 474950 488196 473232 491279 EPSG:3857:21 949900 976393 946465 982558 EPSG:3857:22 1899800 1952787 1892930 1965116 EPSG:3857:23 3799601 3905575 3785860 3930233 EPSG:3857:24 7599203 7811151 7571721 7860466 EPSG:3857:25 15198406 15622302 15143443 15720933 EPSG:3857:26 30396812 31244604 30286886 31441866 EPSG:3857:27 60793624 62489209 60573772 62883733 EPSG:3857:28 121587248 124978419 121147544 125767466 EPSG:3857:29 243174496 249956839 242295088 251534933 EPSG:3857:30 486348993 499913679 484590177 503069866 2011-2020 Average year temperature change since previous decade (2001-2100) Average year temperature anomalies in °C across the period 2011-2020 calculated over the average temperature per year in the period 2001-2010. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_11_20_anom_01_10 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 TZA_kilombero_sequest_fut_BAU 34.553167266769464 -10.038048450490551 37.239835341004294 -7.663994368030097 TEEB:sequest_fut_BAU_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 19 19 EPSG:4326:5 17 17 38 38 EPSG:4326:6 34 35 76 77 EPSG:4326:7 69 71 152 154 EPSG:4326:8 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69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 Dogondoutchi_Intensity_78_T250 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Intensity_78_T250 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 6 6 16 16 EPSG:4326:5 13 13 32 33 EPSG:4326:6 26 27 64 66 EPSG:4326:7 52 55 129 132 EPSG:4326:8 105 111 259 264 EPSG:4326:9 211 222 518 529 EPSG:4326:10 423 444 1037 1058 EPSG:4326:11 846 888 2075 2117 EPSG:4326:12 1693 1776 4151 4234 EPSG:4326:13 3387 3552 8302 8468 EPSG:4326:14 6774 7105 16605 16936 EPSG:4326:15 13549 14211 33210 33872 EPSG:4326:16 27099 28423 66421 67745 EPSG:4326:17 54199 56847 132842 135490 EPSG:4326:18 108399 113695 265685 270981 EPSG:4326:19 216798 227390 531371 541962 EPSG:4326:20 433596 454780 1062742 1083925 EPSG:4326:21 867193 909560 2125484 2167851 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 Annualy Actual Evapotranspiration 2005-2010 - Nile Basin Source: Bastiaanssen, W., Karimi, P., Rebelo, L.-M., Duan, Z., Senay, G., Muthuwatte, L., & et al. (6). (2014). Earth Observation Based Assessment of the Water Production and Water Consumption of Nile Basin Agro-Ecosystems. Remote Sensing, 6(11), 10306-10334. doi:10.3390/rs61110306 <br><br>The vast wetlands in Southern Sudan are characterised by huge evaporation rates from the Sudd, Bahr el Ghazal and the Sobat sub-basins (Mohamed, Bastiaanssen, & Savenije, 2004). About half of the flow into the White Nile is lost mainly to evaporation and transpiration in the wetlands of South Sudan (FAO, 2011) and approximately half of the Bahr el Jebel flow is lost to evaporation (NBI, 2016). In total, long-term evaporation is thought to account for water losses as high as 85 per cent of the total inflows into the Sudd wetlands (Senay, Velpur, Bohma, Demissie, & Gebremkhael, 2014). Analysis of the rate of water loss to evapotranspiration in the Sudd wetlands found that the central part of the Sudd (not counting the seasonally flooded pastures surrounding the wetlands) has evapotranspiration rates between 1,500 and 2,000 mm/yr. 23.550893783569364 -4.0330696105956605 39.804861615169365 31.60211402020434 MAPX_nd:Nile_ET_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 6 8 9 9 EPSG:3857:5 13 16 18 19 EPSG:3857:6 26 32 36 39 EPSG:3857:7 52 65 72 78 EPSG:3857:8 104 130 144 156 EPSG:3857:9 208 261 289 312 EPSG:3857:10 417 523 578 625 EPSG:3857:11 834 1046 1157 1250 EPSG:3857:12 1668 2093 2315 2500 EPSG:3857:13 3337 4187 4631 5001 EPSG:3857:14 6674 8375 9263 10003 EPSG:3857:15 13349 16751 18527 20007 EPSG:3857:16 26698 33502 37055 40014 EPSG:3857:17 53397 67005 74110 80028 EPSG:3857:18 106795 134011 148221 160057 EPSG:3857:19 213591 268022 296442 320114 EPSG:3857:20 427183 536044 592884 640228 EPSG:3857:21 854366 1072089 1185769 1280456 EPSG:3857:22 1708733 2144179 2371539 2560912 EPSG:3857:23 3417466 4288359 4743079 5121824 EPSG:3857:24 6834933 8576718 9486159 10243649 EPSG:3857:25 13669867 17153436 18972318 20487298 EPSG:3857:26 27339735 34306872 37944636 40974596 EPSG:3857:27 54679471 68613744 75889273 81949192 EPSG:3857:28 109358943 137227489 151778547 163898384 EPSG:3857:29 218717887 274454978 303557094 327796768 EPSG:3857:30 437435775 548909956 607114188 655593536 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 2 4 9 9 EPSG:4326:4 5 8 18 19 EPSG:4326:5 10 16 36 39 EPSG:4326:6 20 33 72 78 EPSG:4326:7 41 66 144 156 EPSG:4326:8 83 133 289 312 EPSG:4326:9 166 267 578 625 EPSG:4326:10 332 534 1157 1250 EPSG:4326:11 664 1069 2315 2500 EPSG:4326:12 1328 2139 4631 5001 EPSG:4326:13 2657 4279 9263 10003 EPSG:4326:14 5315 8559 18527 20007 EPSG:4326:15 10631 17118 37055 40014 EPSG:4326:16 21262 34236 74110 80028 EPSG:4326:17 42524 68472 148221 160057 EPSG:4326:18 85048 136945 296442 320114 EPSG:4326:19 170096 273891 592884 640228 EPSG:4326:20 340192 547782 1185769 1280456 EPSG:4326:21 680384 1095564 2371539 2560912 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 1 1 EPSG:900913:2 1 2 2 2 EPSG:900913:3 3 4 4 4 EPSG:900913:4 6 8 9 9 EPSG:900913:5 13 16 18 19 EPSG:900913:6 26 32 36 39 EPSG:900913:7 52 65 72 78 EPSG:900913:8 104 130 144 156 EPSG:900913:9 208 261 289 312 EPSG:900913:10 417 523 578 625 EPSG:900913:11 834 1046 1157 1250 EPSG:900913:12 1668 2093 2315 2500 EPSG:900913:13 3337 4187 4631 5001 EPSG:900913:14 6674 8375 9263 10003 EPSG:900913:15 13349 16751 18527 20007 EPSG:900913:16 26698 33502 37055 40014 EPSG:900913:17 53397 67005 74110 80028 EPSG:900913:18 106795 134011 148221 160057 EPSG:900913:19 213591 268022 296442 320114 EPSG:900913:20 427183 536044 592884 640228 EPSG:900913:21 854366 1072089 1185769 1280456 EPSG:900913:22 1708733 2144179 2371539 2560912 EPSG:900913:23 3417466 4288359 4743079 5121824 EPSG:900913:24 6834933 8576718 9486159 10243649 EPSG:900913:25 13669867 17153436 18972318 20487298 EPSG:900913:26 27339735 34306872 37944636 40974596 EPSG:900913:27 54679471 68613744 75889273 81949192 EPSG:900913:28 109358943 137227489 151778547 163898384 EPSG:900913:29 218717887 274454978 303557094 327796768 EPSG:900913:30 437435775 548909956 607114188 655593536 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 6 8 9 9 EPSG:3857:5 13 16 18 19 EPSG:3857:6 26 32 36 39 EPSG:3857:7 52 65 72 78 EPSG:3857:8 104 130 144 156 EPSG:3857:9 208 261 289 312 EPSG:3857:10 417 523 578 625 EPSG:3857:11 834 1046 1157 1250 EPSG:3857:12 1668 2093 2315 2500 EPSG:3857:13 3337 4187 4631 5001 EPSG:3857:14 6674 8375 9263 10003 EPSG:3857:15 13349 16751 18527 20007 EPSG:3857:16 26698 33502 37055 40014 EPSG:3857:17 53397 67005 74110 80028 EPSG:3857:18 106795 134011 148221 160057 EPSG:3857:19 213591 268022 296442 320114 EPSG:3857:20 427183 536044 592884 640228 EPSG:3857:21 854366 1072089 1185769 1280456 EPSG:3857:22 1708733 2144179 2371539 2560912 EPSG:3857:23 3417466 4288359 4743079 5121824 EPSG:3857:24 6834933 8576718 9486159 10243649 EPSG:3857:25 13669867 17153436 18972318 20487298 EPSG:3857:26 27339735 34306872 37944636 40974596 EPSG:3857:27 54679471 68613744 75889273 81949192 EPSG:3857:28 109358943 137227489 151778547 163898384 EPSG:3857:29 218717887 274454978 303557094 327796768 EPSG:3857:30 437435775 548909956 607114188 655593536 Bhutan - Water Yield 2010 Layer received from TEEB partner in Bhutan in Q2 2020. 88.737534326 26.685110159 92.146924212 28.245314268 TEEB:BHU_Water_yield_2010 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 3 EPSG:3857:3 3 3 5 6 EPSG:3857:4 6 6 11 12 EPSG:3857:5 13 13 23 24 EPSG:3857:6 26 27 47 48 EPSG:3857:7 53 54 95 96 EPSG:3857:8 107 108 191 193 EPSG:3857:9 214 216 382 387 EPSG:3857:10 428 433 764 774 EPSG:3857:11 856 866 1528 1548 EPSG:3857:12 1712 1732 3057 3096 EPSG:3857:13 3425 3465 6115 6192 EPSG:3857:14 6851 6931 12230 12385 EPSG:3857:15 13702 13862 24461 24771 EPSG:3857:16 27404 27724 48922 49542 EPSG:3857:17 54808 55448 97844 99085 EPSG:3857:18 109616 110897 195688 198171 EPSG:3857:19 219233 221794 391377 396342 EPSG:3857:20 438467 443589 782754 792685 EPSG:3857:21 876934 887178 1565509 1585370 EPSG:3857:22 1753869 1774357 3131019 3170741 EPSG:3857:23 3507738 3548714 6262038 6341482 EPSG:3857:24 7015477 7097428 12524076 12682965 EPSG:3857:25 14030955 14194856 25048153 25365931 EPSG:3857:26 28061910 28389713 50096307 50731863 EPSG:3857:27 56123821 56779427 100192614 101463727 EPSG:3857:28 112247642 113558855 200385229 202927454 EPSG:3857:29 224495284 227117710 400770458 405854909 EPSG:3857:30 448990568 454235421 801540917 811709818 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 3 EPSG:4326:2 1 1 5 6 EPSG:4326:3 2 2 11 12 EPSG:4326:4 5 5 23 24 EPSG:4326:5 10 11 47 48 EPSG:4326:6 21 22 95 96 EPSG:4326:7 43 45 191 193 EPSG:4326:8 87 90 382 387 EPSG:4326:9 175 180 764 774 EPSG:4326:10 351 360 1528 1548 EPSG:4326:11 702 720 3057 3096 EPSG:4326:12 1405 1440 6115 6192 EPSG:4326:13 2810 2881 12230 12385 EPSG:4326:14 5621 5763 24461 24771 EPSG:4326:15 11242 11526 48922 49542 EPSG:4326:16 22484 23052 97844 99085 EPSG:4326:17 44968 46104 195688 198171 EPSG:4326:18 89936 92208 391377 396342 EPSG:4326:19 179873 184417 782754 792685 EPSG:4326:20 359747 368835 1565509 1585370 EPSG:4326:21 719494 737671 3131019 3170741 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 3 EPSG:3857:3 3 3 5 6 EPSG:3857:4 6 6 11 12 EPSG:3857:5 13 13 23 24 EPSG:3857:6 26 27 47 48 EPSG:3857:7 53 54 95 96 EPSG:3857:8 107 108 191 193 EPSG:3857:9 214 216 382 387 EPSG:3857:10 428 433 764 774 EPSG:3857:11 856 866 1528 1548 EPSG:3857:12 1712 1732 3057 3096 EPSG:3857:13 3425 3465 6115 6192 EPSG:3857:14 6851 6931 12230 12385 EPSG:3857:15 13702 13862 24461 24771 EPSG:3857:16 27404 27724 48922 49542 EPSG:3857:17 54808 55448 97844 99085 EPSG:3857:18 109616 110897 195688 198171 EPSG:3857:19 219233 221794 391377 396342 EPSG:3857:20 438467 443589 782754 792685 EPSG:3857:21 876934 887178 1565509 1585370 EPSG:3857:22 1753869 1774357 3131019 3170741 EPSG:3857:23 3507738 3548714 6262038 6341482 EPSG:3857:24 7015477 7097428 12524076 12682965 EPSG:3857:25 14030955 14194856 25048153 25365931 EPSG:3857:26 28061910 28389713 50096307 50731863 EPSG:3857:27 56123821 56779427 100192614 101463727 EPSG:3857:28 112247642 113558855 200385229 202927454 EPSG:3857:29 224495284 227117710 400770458 405854909 EPSG:3857:30 448990568 454235421 801540917 811709818 Satellite Mogadisho Urban Growth 2001 Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2001-06-28. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov. 45.195394649846214 1.955229029551538 45.47923060483453 2.14147661335313 MAPX:Mogadisho_Landsat7_20010628-531 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 10 10 EPSG:3857:5 15 15 20 20 EPSG:3857:6 31 31 40 40 EPSG:3857:7 63 63 80 80 EPSG:3857:8 126 126 160 160 EPSG:3857:9 252 253 320 320 EPSG:3857:10 505 506 640 641 EPSG:3857:11 1011 1012 1281 1282 EPSG:3857:12 2023 2025 2562 2565 EPSG:3857:13 4047 4051 5124 5130 EPSG:3857:14 8094 8102 10248 10261 EPSG:3857:15 16189 16205 20497 20523 EPSG:3857:16 32378 32411 40995 41047 EPSG:3857:17 64756 64823 81991 82094 EPSG:3857:18 129512 129647 163982 164188 EPSG:3857:19 259024 259295 327964 328377 EPSG:3857:20 518049 518591 655929 656755 EPSG:3857:21 1036098 1037183 1311858 1313511 EPSG:3857:22 2072196 2074367 2623716 2627023 EPSG:3857:23 4144392 4148735 5247433 5254046 EPSG:3857:24 8288784 8297470 10494866 10508093 EPSG:3857:25 16577569 16594940 20989732 21016187 EPSG:3857:26 33155138 33189880 41979464 42032375 EPSG:3857:27 66310277 66379760 83958928 84064750 EPSG:3857:28 132620555 132759520 167917856 168129500 EPSG:3857:29 265241110 265519041 335835713 336259000 EPSG:3857:30 530482221 531038082 671671427 672518000 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 10 10 EPSG:4326:4 7 7 20 20 EPSG:4326:5 15 15 40 40 EPSG:4326:6 31 31 80 80 EPSG:4326:7 62 62 160 160 EPSG:4326:8 124 125 320 320 EPSG:4326:9 249 250 640 641 EPSG:4326:10 499 500 1281 1282 EPSG:4326:11 999 1001 2562 2565 EPSG:4326:12 1999 2003 5124 5130 EPSG:4326:13 3998 4007 10248 10261 EPSG:4326:14 7997 8014 20497 20523 EPSG:4326:15 15994 16028 40995 41047 EPSG:4326:16 31988 32056 81991 82094 EPSG:4326:17 63976 64112 163982 164188 EPSG:4326:18 127953 128224 327964 328377 EPSG:4326:19 255906 256448 655929 656755 EPSG:4326:20 511812 512897 1311858 1313511 EPSG:4326:21 1023625 1025795 2623716 2627023 EPSG:900913 site_0028_visual 103.74690500699275 10.653176807974434 105.74039483165863 12.48209622646687 hotspots:site_0028_visual image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 3 3 EPSG:3857:3 3 3 6 6 EPSG:3857:4 7 7 12 12 EPSG:3857:5 14 15 25 25 EPSG:3857:6 29 30 50 50 EPSG:3857:7 59 60 100 101 EPSG:3857:8 119 120 201 203 EPSG:3857:9 238 240 403 406 EPSG:3857:10 476 481 807 812 EPSG:3857:11 952 963 1614 1625 EPSG:3857:12 1904 1926 3228 3251 EPSG:3857:13 3809 3852 6456 6502 EPSG:3857:14 7619 7704 12913 13004 EPSG:3857:15 15238 15408 25827 26008 EPSG:3857:16 30477 30817 51654 52017 EPSG:3857:17 60955 61634 103309 104034 EPSG:3857:18 121910 123269 206618 208069 EPSG:3857:19 243820 246539 413236 416139 EPSG:3857:20 487640 493078 826472 832279 EPSG:3857:21 975280 986156 1652945 1664558 EPSG:3857:22 1950560 1972312 3305891 3329116 EPSG:3857:23 3901121 3944624 6611782 6658233 EPSG:3857:24 7802243 7889248 13223564 13316467 EPSG:3857:25 15604486 15778496 26447128 26632935 EPSG:3857:26 31208973 31556993 52894256 53265870 EPSG:3857:27 62417947 63113987 105788513 106531740 EPSG:3857:28 124835895 126227974 211577027 213063481 EPSG:3857:29 249671790 252455948 423154054 426126962 EPSG:3857:30 499343581 504911897 846308109 852253924 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 3 3 EPSG:4326:2 1 1 6 6 EPSG:4326:3 3 3 12 12 EPSG:4326:4 6 7 25 25 EPSG:4326:5 13 14 50 50 EPSG:4326:6 27 28 100 101 EPSG:4326:7 55 56 201 203 EPSG:4326:8 110 112 403 406 EPSG:4326:9 220 225 807 812 EPSG:4326:10 440 451 1614 1625 EPSG:4326:11 881 902 3228 3251 EPSG:4326:12 1763 1805 6456 6502 EPSG:4326:13 3527 3611 12913 13004 EPSG:4326:14 7055 7222 25827 26008 EPSG:4326:15 14111 14444 51654 52017 EPSG:4326:16 28223 28889 103309 104034 EPSG:4326:17 56446 57778 206618 208069 EPSG:4326:18 112893 115557 413236 416139 EPSG:4326:19 225787 231114 826472 832279 EPSG:4326:20 451574 462228 1652945 1664558 EPSG:4326:21 903149 924457 3305891 3329116 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 3 3 EPSG:3857:3 3 3 6 6 EPSG:3857:4 7 7 12 12 EPSG:3857:5 14 15 25 25 EPSG:3857:6 29 30 50 50 EPSG:3857:7 59 60 100 101 EPSG:3857:8 119 120 201 203 EPSG:3857:9 238 240 403 406 EPSG:3857:10 476 481 807 812 EPSG:3857:11 952 963 1614 1625 EPSG:3857:12 1904 1926 3228 3251 EPSG:3857:13 3809 3852 6456 6502 EPSG:3857:14 7619 7704 12913 13004 EPSG:3857:15 15238 15408 25827 26008 EPSG:3857:16 30477 30817 51654 52017 EPSG:3857:17 60955 61634 103309 104034 EPSG:3857:18 121910 123269 206618 208069 EPSG:3857:19 243820 246539 413236 416139 EPSG:3857:20 487640 493078 826472 832279 EPSG:3857:21 975280 986156 1652945 1664558 EPSG:3857:22 1950560 1972312 3305891 3329116 EPSG:3857:23 3901121 3944624 6611782 6658233 EPSG:3857:24 7802243 7889248 13223564 13316467 EPSG:3857:25 15604486 15778496 26447128 26632935 EPSG:3857:26 31208973 31556993 52894256 53265870 EPSG:3857:27 62417947 63113987 105788513 106531740 EPSG:3857:28 124835895 126227974 211577027 213063481 EPSG:3857:29 249671790 252455948 423154054 426126962 EPSG:3857:30 499343581 504911897 846308109 852253924 Soil Adjusted Vegetation Index in Keur Massar Senegal (2025) This layer shows the distribution of vegetation in Keur Massar (Dakar, Senegal) derived from Sentinel-2 imagery at 10 m spatial resolution. The satellite images were collected from Copernicus Browser (open access) on the 16th of April 2025. The Soil Adjusted Vegetation Index (SAVI) was calculated using the red and near-infrared bands of Sentinel-2, applying a soil brightness correction factor (L = 0.5). Vegetation appears on the map starting from SAVI values of 0.26, representing low vegetation cover, and gradually increases up to 0.95, representing dense vegetation (dark green). This layer serves as an input for the project, providing baseline information on vegetation cover to support the susceptibility assessment of illegal dumping sites. -17.382029187007333 14.733719739640827 -17.2719124771499 14.84106039798925 dakar_waste:SAVI image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7508 7513 7400 7405 EPSG:3857:15 15017 15027 14801 14811 EPSG:3857:16 30035 30055 29603 29623 EPSG:3857:17 60071 60111 59207 59247 EPSG:3857:18 120142 120222 118414 118494 EPSG:3857:19 240284 240445 236829 236989 EPSG:3857:20 480568 480891 473659 473979 EPSG:3857:21 961137 961783 947318 947959 EPSG:3857:22 1922274 1923567 1894636 1895919 EPSG:3857:23 3844548 3847135 3789273 3791839 EPSG:3857:24 7689097 7694271 7578546 7583678 EPSG:3857:25 15378195 15388543 15157093 15167357 EPSG:3857:26 30756391 30777086 30314186 30334714 EPSG:3857:27 61512783 61554173 60628373 60669428 EPSG:3857:28 123025567 123108347 121256747 121338856 EPSG:3857:29 246051134 246216695 242513495 242677713 EPSG:3857:30 492102268 492433390 485026990 485355426 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 462 EPSG:4326:10 427 428 925 925 EPSG:4326:11 855 856 1850 1851 EPSG:4326:12 1710 1712 3700 3702 EPSG:4326:13 3420 3425 7400 7405 EPSG:4326:14 6841 6850 14801 14811 EPSG:4326:15 13682 13701 29603 29623 EPSG:4326:16 27364 27403 59207 59247 EPSG:4326:17 54729 54807 118414 118494 EPSG:4326:18 109458 109614 236829 236989 EPSG:4326:19 218916 219228 473659 473979 EPSG:4326:20 437832 438457 947318 947959 EPSG:4326:21 875665 876915 1894636 1895919 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7508 7513 7400 7405 EPSG:3857:15 15017 15027 14801 14811 EPSG:3857:16 30035 30055 29603 29623 EPSG:3857:17 60071 60111 59207 59247 EPSG:3857:18 120142 120222 118414 118494 EPSG:3857:19 240284 240445 236829 236989 EPSG:3857:20 480568 480891 473659 473979 EPSG:3857:21 961137 961783 947318 947959 EPSG:3857:22 1922274 1923567 1894636 1895919 EPSG:3857:23 3844548 3847135 3789273 3791839 EPSG:3857:24 7689097 7694271 7578546 7583678 EPSG:3857:25 15378195 15388543 15157093 15167357 EPSG:3857:26 30756391 30777086 30314186 30334714 EPSG:3857:27 61512783 61554173 60628373 60669428 EPSG:3857:28 123025567 123108347 121256747 121338856 EPSG:3857:29 246051134 246216695 242513495 242677713 EPSG:3857:30 492102268 492433390 485026990 485355426 Self-calibrating Palmer Drought Severity Index (scPDSI) 1990-1999 (CRU) This layer shows the average values over the 1990 to 1999 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that covers the time interval from 1901 to 2018. Original data were subset and processed using QGIS at UNEP/GRID-Geneva. <br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> The dataset has been updated each year using newer versions of CRU TS input data, currently to the end of 2018 using a preliminary version of CRU TS 4.03 (0.5° resolution). <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 UN_Sahel:scPDSI.cru_ts403_1990-1999 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tanzania_remote_site_screening_res50 29.340830109000006 -11.761432042999948 40.44333010900001 -0.9844320429999465 mapx_chemobs:tanzania_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 17 18 19 EPSG:3857:6 32 34 37 39 EPSG:3857:7 64 68 74 78 EPSG:3857:8 128 136 148 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9 9 EPSG:4326:4 8 9 18 19 EPSG:4326:5 16 18 37 39 EPSG:4326:6 32 36 74 78 EPSG:4326:7 64 72 148 156 EPSG:4326:8 129 144 297 313 EPSG:4326:9 258 289 595 627 EPSG:4326:10 517 578 1190 1254 EPSG:4326:11 1035 1157 2381 2508 EPSG:4326:12 2070 2315 4763 5016 EPSG:4326:13 4140 4631 9527 10032 EPSG:4326:14 8281 9262 19054 20065 EPSG:4326:15 16563 18525 38109 40130 EPSG:4326:16 33126 37050 76218 80260 EPSG:4326:17 66252 74100 152437 160521 EPSG:4326:18 132505 148200 304874 321043 EPSG:4326:19 265011 296401 609749 642087 EPSG:4326:20 530022 592803 1219498 1284175 EPSG:4326:21 1060045 1185606 2438997 2568350 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 17 18 19 EPSG:3857:6 32 34 37 39 EPSG:3857:7 64 68 74 78 EPSG:3857:8 128 136 148 156 EPSG:3857:9 257 272 297 313 EPSG:3857:10 514 545 595 627 EPSG:3857:11 1029 1091 1190 1254 EPSG:3857:12 2059 2182 2381 2508 EPSG:3857:13 4118 4365 4763 5016 EPSG:3857:14 8236 8731 9527 10032 EPSG:3857:15 16473 17462 19054 20065 EPSG:3857:16 32947 34924 38109 40130 EPSG:3857:17 65894 69848 76218 80260 EPSG:3857:18 131788 139697 152437 160521 EPSG:3857:19 263577 279394 304874 321043 EPSG:3857:20 527155 558788 609749 642087 EPSG:3857:21 1054311 1117577 1219498 1284175 EPSG:3857:22 2108622 2235155 2438997 2568350 EPSG:3857:23 4217244 4470310 4877994 5136701 EPSG:3857:24 8434488 8940620 9755989 10273403 EPSG:3857:25 16868976 17881241 19511979 20546807 EPSG:3857:26 33737952 35762483 39023959 41093615 EPSG:3857:27 67475904 71524967 78047918 82187230 EPSG:3857:28 134951809 143049935 156095836 164374460 EPSG:3857:29 269903619 286099871 312191673 328748921 EPSG:3857:30 539807239 572199743 624383346 657497842 T56HKH_20190927_843_QG 149.73701209968527 -34.41180718585441 150.95410135717458 -33.39707945018877 wesr_swipe:T56HKH_20190927_843_QG image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 153 154 234 235 EPSG:3857:9 306 308 468 470 EPSG:3857:10 612 616 937 941 EPSG:3857:11 1225 1232 1875 1882 EPSG:3857:12 2451 2465 3751 3765 EPSG:3857:13 4903 4930 7503 7531 EPSG:3857:14 9806 9861 15006 15062 EPSG:3857:15 19612 19723 30013 30124 EPSG:3857:16 39224 39447 60026 60248 EPSG:3857:17 78449 78894 120053 120496 EPSG:3857:18 156898 157788 240107 240993 EPSG:3857:19 313796 315576 480214 481986 EPSG:3857:20 627592 631153 960428 963973 EPSG:3857:21 1255184 1262306 1920857 1927947 EPSG:3857:22 2510368 2524613 3841714 3855894 EPSG:3857:23 5020736 5049226 7683429 7711789 EPSG:3857:24 10041473 10098452 15366858 15423579 EPSG:3857:25 20082947 20196905 30733717 30847158 EPSG:3857:26 40165894 40393810 61467434 61694316 EPSG:3857:27 80331788 80787621 122934868 123388632 EPSG:3857:28 160663576 161575242 245869736 246777264 EPSG:3857:29 321327152 323150484 491739473 493554528 EPSG:3857:30 642654304 646300969 983478946 987109056 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 3 3 EPSG:4326:2 2 2 7 7 EPSG:4326:3 5 5 14 14 EPSG:4326:4 10 11 29 29 EPSG:4326:5 21 22 58 58 EPSG:4326:6 43 44 117 117 EPSG:4326:7 87 88 234 235 EPSG:4326:8 175 176 468 470 EPSG:4326:9 350 353 937 941 EPSG:4326:10 701 707 1875 1882 EPSG:4326:11 1403 1415 3751 3765 EPSG:4326:12 2807 2831 7503 7531 EPSG:4326:13 5615 5662 15006 15062 EPSG:4326:14 11231 11324 30013 30124 EPSG:4326:15 22463 22648 60026 60248 EPSG:4326:16 44927 45296 120053 120496 EPSG:4326:17 89855 90593 240107 240993 EPSG:4326:18 179710 181187 480214 481986 EPSG:4326:19 359420 362375 960428 963973 EPSG:4326:20 718840 724751 1920857 1927947 EPSG:4326:21 1437680 1449502 3841714 3855894 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 153 154 234 235 EPSG:3857:9 306 308 468 470 EPSG:3857:10 612 616 937 941 EPSG:3857:11 1225 1232 1875 1882 EPSG:3857:12 2451 2465 3751 3765 EPSG:3857:13 4903 4930 7503 7531 EPSG:3857:14 9806 9861 15006 15062 EPSG:3857:15 19612 19723 30013 30124 EPSG:3857:16 39224 39447 60026 60248 EPSG:3857:17 78449 78894 120053 120496 EPSG:3857:18 156898 157788 240107 240993 EPSG:3857:19 313796 315576 480214 481986 EPSG:3857:20 627592 631153 960428 963973 EPSG:3857:21 1255184 1262306 1920857 1927947 EPSG:3857:22 2510368 2524613 3841714 3855894 EPSG:3857:23 5020736 5049226 7683429 7711789 EPSG:3857:24 10041473 10098452 15366858 15423579 EPSG:3857:25 20082947 20196905 30733717 30847158 EPSG:3857:26 40165894 40393810 61467434 61694316 EPSG:3857:27 80331788 80787621 122934868 123388632 EPSG:3857:28 160663576 161575242 245869736 246777264 EPSG:3857:29 321327152 323150484 491739473 493554528 EPSG:3857:30 642654304 646300969 983478946 987109056 Combination Landslide/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_lds_for6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_mambo_bado_20200922 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20200922 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 Combination Tropical cyclone surge/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_for6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Areas of Global Significance for Biodiversity Conservation and Carbon Storage <style> .p1 { overflow: auto; font-style: oblique; font-size: .9em; padding: 10px; margin: 0; text-align: justify; -moz-hyphens: auto; -webkit-hyphens: auto; -ms-hypens: auto; -ms-hyphens: auto; hyphens: auto; max-height: 220px; overflow-x: auto; overflow-y: hidden; columns: 160px; column-rule: 1px solid #ccc; grid-column-gap: 10px; column-gap: 10px; } </style> <div class="p1"> <p> This map is the result of a global joint optimization of valuable biodiversity and carbon storage. This analysis collated distribution data for over 180000 terrestrial vertebrate and plant species globally, removing unsuitable areas using information on species' habitat preferences and species' known altitudinal limits or, where unknown, by removing anthropogenically modified land. </p> <p> Given existing biases in taxonomic coverage for plant species, we calculated 10 representative sets of species, containing approximately 10% of species of each taxonomic group. For carbon we used the combined amount of above-ground and below-ground biomass carbon density and vulnerable soil organic carbon density. We then determined those areas globally that jointly contributed the most to biodiversity and carbon conservation if up to 10%, 20%, or 100% of the Earth were to be protected. <p> <u>References:</u> </p> <dl> <dt> Jung, M., et al. (2020). Areas of global importance for terrestrial biodiversity, carbon, and water. BioRxiv. <a href="https://www.biorxiv.org/content/10.1101/2020.04.16.021444v1" target="_blank">biorxiv.org/content/10.1101/2020.04.16.021444v1</a>. </dt> </dl> </div> -179.995201157628 -84.69466806618583 179.8859620772232 85.91771612300938 MapX_UNDP:conservation_biodiversity_carbon_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 126 0 127 EPSG:3857:8 0 253 0 255 EPSG:3857:9 0 506 0 511 EPSG:3857:10 0 1012 0 1023 EPSG:3857:11 0 2025 0 2047 EPSG:3857:12 0 4050 0 4094 EPSG:3857:13 0 8101 0 8189 EPSG:3857:14 0 16202 0 16378 EPSG:3857:15 0 32404 0 32757 EPSG:3857:16 0 64809 0 65515 EPSG:3857:17 0 129619 1 131030 EPSG:3857:18 0 259238 3 262060 EPSG:3857:19 0 518476 6 524121 EPSG:3857:20 0 1036953 13 1048243 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provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -90.0 180.0 90.0 wesr_climat:v60_N2O_2018_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Precipitation Anomalies Apr-May-Jun_2017_(mm) - CHIRPS -19.125063083055668 -35.37238257858172 52.6296893492118 38.256795423617206 MAPX:CHIRPS_Anomaly_3-Monthly_Apr-May-Jun_2017_(mm) image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 1 2 3 5 EPSG:4326:3 2 5 7 10 EPSG:4326:4 4 11 14 20 EPSG:4326:5 9 22 28 41 EPSG:4326:6 18 44 57 82 EPSG:4326:7 36 89 114 165 EPSG:4326:8 73 178 228 330 EPSG:4326:9 147 356 457 661 EPSG:4326:10 294 713 915 1323 EPSG:4326:11 588 1426 1830 2646 EPSG:4326:12 1177 2852 3660 5293 EPSG:4326:13 2354 5705 7321 10587 EPSG:4326:14 4709 11411 14643 21174 EPSG:4326:15 9419 22823 29286 42348 EPSG:4326:16 18839 45646 58572 84697 EPSG:4326:17 37678 91293 117145 169395 EPSG:4326:18 75356 182586 234291 338791 EPSG:4326:19 150713 365173 468582 677583 EPSG:4326:20 301426 730347 937164 1355166 EPSG:4326:21 602852 1460694 1874328 2710332 EPSG:900913 Rarity-weighted richness <span style="font-size:0.95em"><span style="font-size:1.1em"><b>Description</b></span> Rarity weighted richness is a measure that combines endemism and species richness of amphibians, birds, mammals, reptiles and a representative set of plant taxa in each 10 km cell. This index lowers the contribution of wide ranging species to overall species richness and highlights the areas that have a relatively high proportion of narrow‐range species. Species ranges were rasterised at 1 km resolution from polygon maps from the IUCN Red List (IUCN Red List of Threatened Species (2019) Version 2019.2. http://www.iucnredlist.org), the Global Assessment of Reptile Distributions (GARD) (Roll et al. (2017), Version 1.5, https://datadryad.org/stash/dataset/doi:10.5061/dryad.83s7k) and the Botanical Information and Ecology Network (BIEN) database (Enquist et al. 2019 and Maitner et al. 2017, version 4.1. http://bien.nceas.ucsb.edu/bien/biendata/). Additional vascular plant species ranges were created from point data from the IUCN Red List (IUCN Red List of Threatened Species (2019) Version 2019.2. http://www.iucnredlist.org), Botanic Gardens Conservation International (BGCI) (https://www.bgci.org/) and the Global Biodiversity Information Facility (GBIF) (https://www.gbif.org/). Species range maps were refined, when possible, by removing unsuitable areas using information on species’ habitat preferences and species' known altitudinal limits. Habitats distributions were obtained from the global map of terrestrial habitat types (Jung et al. in prep), while altitudinal data was obtained from the Global Multi-resolution Terrain Elevation Data (GMTED2010) (USGS). This refinement process produced Areas of Habitat (AOH) maps for each species (Brooks et al. 2019).<br><br>Each grid cell of the species’ AOH was then scored for range-size rarity (the proportion of the species’ AOH the cell represents; i.e. size of grid cell/AOH). The total score for each cell was calculated by summing scores across all the species whose AOH intersected with it. Higher values occur in cells with more species that have smaller ranges (i.e. both the number of species and the degree to which their ranges are restricted contribute to the range rarity score).<br><br>NatureMap is currently soliciting feedback on the validity of this map at the national and sub-national levels. Please submit any comments via the <a href="https://explorer.naturemap.earth/" target="_blank">Nature Map Explorer</a>.<br><br><b>References</b><br></<span>Brooks, T. M. et al. (2019). Measuring Terrestrial Area of Habitat (AOH) and Its Utility for the IUCN Red List. Trends in Ecology & Evolution 34:977–986. <a href="https://doi.org/10.1016/j.tree.2019.06.009" target="_blank">doi.org/10.1016/j.tree.2019.06.009</a>.<br><br>BGCI (2019). ThreatSearch online database. <a href="www.bgci.org/threat_search.php" target="_blank">www.bgci.org/threat_search.php</a>.<br><br>Enquist, B.J. et al. (in prep.). Botanical big data shows that plant diversity in the New World is driven by climatic-linked differences in evolutionary rates and biotic exclusion.<br><br>Jung, M. et al. (in prep). A global map of species terrestrial habitat types.<br><br>Maitner, B.S. et al. (2017). The BIEN R package: A tool to access the Botanical Information and Ecology Network (BIEN) database. Methods in Ecology and Evolution; 9:373–379. <a href="https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.12861" target="_blank">doi/10.1111/2041-210X.12861</a>.<br><br>Roll, U. et al. (2017), The global distribution of tetrapods reveals a need for targeted reptile conservation, Nature Ecology & Evolution, 1: 1677–1682, <a href="https://doi.org/10.1038/s41559-017-0332-2" target="_blank">doi.org/10.1038/s41559-017-0332-2</a>.</span> -179.995201157628 -84.69466806618583 179.8859620772232 85.91771612300938 MapX_UNDP:rarity_weighted_richness_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 126 0 127 EPSG:3857:8 0 253 0 255 EPSG:3857:9 0 506 0 511 EPSG:3857:10 0 1012 0 1023 EPSG:3857:11 0 2025 0 2047 EPSG:3857:12 0 4050 0 4094 EPSG:3857:13 0 8101 0 8189 EPSG:3857:14 0 16202 0 16378 EPSG:3857:15 0 32404 0 32757 EPSG:3857:16 0 64809 0 65515 EPSG:3857:17 0 129619 1 131030 EPSG:3857:18 0 259238 3 262060 EPSG:3857:19 0 518476 6 524121 EPSG:3857:20 0 1036953 13 1048243 EPSG:3857:21 0 2073906 27 2096487 EPSG:3857:22 -1 4147812 55 4192975 EPSG:3857:23 -1 8295624 111 8385950 EPSG:3857:24 0 16591249 223 16771901 EPSG:3857:25 0 33182499 447 33543802 EPSG:3857:26 0 66364998 894 67087605 EPSG:3857:27 0 132729997 1789 134175211 EPSG:3857:28 -1 265459994 3578 268350423 EPSG:3857:29 0 530919989 7156 536700846 EPSG:3857:30 0 1061839978 14313 1073401692 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 62 0 127 EPSG:4326:7 2 124 0 255 EPSG:4326:8 5 248 0 511 EPSG:4326:9 11 496 0 1023 EPSG:4326:10 23 993 0 2047 EPSG:4326:11 46 1987 0 4094 EPSG:4326:12 92 3975 0 8189 EPSG:4326:13 185 7950 0 16378 EPSG:4326:14 371 15901 0 32757 EPSG:4326:15 743 31802 0 65515 EPSG:4326:16 1486 63604 1 131030 EPSG:4326:17 2972 127208 3 262060 EPSG:4326:18 5945 254417 6 524121 EPSG:4326:19 11890 508835 13 1048243 EPSG:4326:20 23781 1017670 27 2096487 EPSG:4326:21 47562 2035340 55 4192975 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 126 0 127 EPSG:3857:8 0 253 0 255 EPSG:3857:9 0 506 0 511 EPSG:3857:10 0 1012 0 1023 EPSG:3857:11 0 2025 0 2047 EPSG:3857:12 0 4050 0 4094 EPSG:3857:13 0 8101 0 8189 EPSG:3857:14 0 16202 0 16378 EPSG:3857:15 0 32404 0 32757 EPSG:3857:16 0 64809 0 65515 EPSG:3857:17 0 129619 1 131030 EPSG:3857:18 0 259238 3 262060 EPSG:3857:19 0 518476 6 524121 EPSG:3857:20 0 1036953 13 1048243 EPSG:3857:21 -1 2073906 27 2096487 EPSG:3857:22 -1 4147812 55 4192975 EPSG:3857:23 0 8295624 111 8385950 EPSG:3857:24 0 16591249 223 16771901 EPSG:3857:25 0 33182499 447 33543802 EPSG:3857:26 0 66364998 894 67087605 EPSG:3857:27 -1 132729997 1789 134175211 EPSG:3857:28 0 265459994 3578 268350423 EPSG:3857:29 0 530919989 7156 536700846 EPSG:3857:30 -1 1061839978 14313 1073401692 Combination Flood/Forest at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_flo_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Self-calibrating Palmer Drought Severity Index (scPDSI) 2022 (CRU) This layer shows the average values for 2022 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_22_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 c181125_mantapala 28.847679478 -9.533699678 28.918080924 -9.487133772 MAPX:c181125_mantapala image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 33 33 37 37 EPSG:3857:7 67 67 74 74 EPSG:3857:8 134 134 148 148 EPSG:3857:9 269 269 297 297 EPSG:3857:10 539 539 594 594 EPSG:3857:11 1078 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EPSG:4326:7 70 70 148 148 EPSG:4326:8 141 141 297 297 EPSG:4326:9 282 283 594 594 EPSG:4326:10 565 566 1188 1188 EPSG:4326:11 1131 1132 2376 2377 EPSG:4326:12 2263 2264 4752 4754 EPSG:4326:13 4527 4529 9504 9508 EPSG:4326:14 9055 9059 19009 19016 EPSG:4326:15 18111 18119 38019 38032 EPSG:4326:16 36222 36239 76039 76064 EPSG:4326:17 72444 72478 152078 152129 EPSG:4326:18 144888 144956 304156 304259 EPSG:4326:19 289777 289912 608312 608518 EPSG:4326:20 579554 579825 1216625 1217036 EPSG:4326:21 1159109 1159651 2433251 2434072 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 33 33 37 37 EPSG:3857:7 67 67 74 74 EPSG:3857:8 134 134 148 148 EPSG:3857:9 269 269 297 297 EPSG:3857:10 539 539 594 594 EPSG:3857:11 1078 1078 1188 1188 EPSG:3857:12 2156 2156 2376 2377 EPSG:3857:13 4312 4313 4752 4754 EPSG:3857:14 8625 8627 9504 9508 EPSG:3857:15 17251 17255 19009 19016 EPSG:3857:16 34503 34511 38019 38032 EPSG:3857:17 69006 69023 76039 76064 EPSG:3857:18 138012 138046 152078 152129 EPSG:3857:19 276024 276092 304156 304259 EPSG:3857:20 552048 552185 608312 608518 EPSG:3857:21 1104096 1104371 1216625 1217036 EPSG:3857:22 2208193 2208743 2433251 2434072 EPSG:3857:23 4416387 4417487 4866503 4868144 EPSG:3857:24 8832774 8834975 9733007 9736288 EPSG:3857:25 17665549 17669950 19466014 19472576 EPSG:3857:26 35331099 35339900 38932029 38945153 EPSG:3857:27 70662198 70679801 77864058 77890306 EPSG:3857:28 141324396 141359602 155728116 155780612 EPSG:3857:29 282648793 282719205 311456233 311561224 EPSG:3857:30 565297586 565438410 622912467 623122448 Dogondoutchi_Duration_78_T25 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Duration_78_T25 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 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132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 Hydrography - Natural Polygons 14.278348129129038 2.1686254796591595 26.929306202145593 10.991564938682107 cc_and_health:vNaturalPolygons image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 294 EPSG:3857:10 480 505 552 588 EPSG:3857:11 961 1011 1105 1177 EPSG:3857:12 1922 2023 2210 2354 EPSG:3857:13 3844 4046 4420 4708 EPSG:3857:14 7688 8093 8841 9417 EPSG:3857:15 15377 16186 17683 18835 EPSG:3857:16 30754 32373 35367 37670 EPSG:3857:17 61509 64746 70734 75340 EPSG:3857:18 123018 129492 141469 150681 EPSG:3857:19 246037 258984 282938 301362 EPSG:3857:20 492074 517969 565876 602725 EPSG:3857:21 984149 1035939 1131753 1205450 EPSG:3857:22 1968298 2071879 2263506 2410901 EPSG:3857:23 3936596 4143759 4527013 4821802 EPSG:3857:24 7873192 8287518 9054027 9643604 EPSG:3857:25 15746385 16575037 18108054 19287209 EPSG:3857:26 31492771 33150074 36216109 38574418 EPSG:3857:27 62985542 66300148 72432218 77148837 EPSG:3857:28 125971084 132600297 144864436 154297674 EPSG:3857:29 251942168 265200594 289728872 308595348 EPSG:3857:30 503884337 530401189 579457744 617190696 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 294 EPSG:4326:9 224 249 552 588 EPSG:4326:10 449 499 1105 1177 EPSG:4326:11 898 999 2210 2354 EPSG:4326:12 1797 1998 4420 4708 EPSG:4326:13 3595 3997 8841 9417 EPSG:4326:14 7191 7994 17683 18835 EPSG:4326:15 14383 15989 35367 37670 EPSG:4326:16 28766 31978 70734 75340 EPSG:4326:17 57532 63956 141469 150681 EPSG:4326:18 115064 127913 282938 301362 EPSG:4326:19 230128 255827 565876 602725 EPSG:4326:20 460257 511654 1131753 1205450 EPSG:4326:21 920514 1023309 2263506 2410901 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 294 EPSG:3857:10 480 505 552 588 EPSG:3857:11 961 1011 1105 1177 EPSG:3857:12 1922 2023 2210 2354 EPSG:3857:13 3844 4046 4420 4708 EPSG:3857:14 7688 8093 8841 9417 EPSG:3857:15 15377 16186 17683 18835 EPSG:3857:16 30754 32373 35367 37670 EPSG:3857:17 61509 64746 70734 75340 EPSG:3857:18 123018 129492 141469 150681 EPSG:3857:19 246037 258984 282938 301362 EPSG:3857:20 492074 517969 565876 602725 EPSG:3857:21 984149 1035939 1131753 1205450 EPSG:3857:22 1968298 2071879 2263506 2410901 EPSG:3857:23 3936596 4143759 4527013 4821802 EPSG:3857:24 7873192 8287518 9054027 9643604 EPSG:3857:25 15746385 16575037 18108054 19287209 EPSG:3857:26 31492771 33150074 36216109 38574418 EPSG:3857:27 62985542 66300148 72432218 77148837 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Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_jja_ENDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 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19514 19924 30006 30126 EPSG:3857:16 39029 39849 60013 60252 EPSG:3857:17 78058 79698 120026 120504 EPSG:3857:18 156116 159396 240053 241008 EPSG:3857:19 312233 318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 EPSG:3857:22 2497869 2550351 3840862 3856135 EPSG:3857:23 4995738 5100703 7681724 7712271 EPSG:3857:24 9991476 10201407 15363449 15424542 EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 hfp2013_meris_wgs Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11 -179.99997804642848 -65.24741434935741 180.0 89.8976232152096 MapX_UNDP_nd:hfp2013_meris_wgs image/png image/vnd.jpeg-png image/jpeg image/png8 EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12146 0 16383 EPSG:3857:15 0 24293 0 32767 EPSG:3857:16 0 48587 0 65535 EPSG:3857:17 0 97175 0 131071 EPSG:3857:18 0 194351 0 262143 EPSG:3857:19 0 388703 0 524287 EPSG:3857:20 0 777407 0 1048575 EPSG:3857:21 0 1554814 0 2097151 EPSG:3857:22 -1 3109629 0 4194304 EPSG:3857:23 -1 6219258 0 8388608 EPSG:3857:24 0 12438517 1 16777215 EPSG:3857:25 0 24877035 2 33554431 EPSG:3857:26 0 49754070 4 67108863 EPSG:3857:27 0 99508140 8 134217727 EPSG:3857:28 -1 199016280 16 268435456 EPSG:3857:29 0 398032561 32 536870911 EPSG:3857:30 0 796065123 65 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 55 0 127 EPSG:4326:7 0 110 0 255 EPSG:4326:8 0 220 0 511 EPSG:4326:9 0 441 0 1023 EPSG:4326:10 0 883 0 2047 EPSG:4326:11 1 1766 0 4095 EPSG:4326:12 2 3532 0 8191 EPSG:4326:13 4 7065 0 16383 EPSG:4326:14 9 14130 0 32767 EPSG:4326:15 18 28261 0 65535 EPSG:4326:16 37 56523 0 131071 EPSG:4326:17 74 113047 0 262143 EPSG:4326:18 149 226095 0 524287 EPSG:4326:19 298 452190 0 1048575 EPSG:4326:20 596 904381 0 2097151 EPSG:4326:21 1192 1808763 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 23 0 31 EPSG:900913:6 0 47 0 63 EPSG:900913:7 0 94 0 127 EPSG:900913:8 0 189 0 255 EPSG:900913:9 0 379 0 511 EPSG:900913:10 0 759 0 1023 EPSG:900913:11 0 1518 0 2047 EPSG:900913:12 0 3036 0 4095 EPSG:900913:13 0 6073 0 8191 EPSG:900913:14 0 12146 0 16383 EPSG:900913:15 0 24293 0 32767 EPSG:900913:16 0 48587 0 65535 EPSG:900913:17 0 97175 0 131071 EPSG:900913:18 0 194351 0 262143 EPSG:900913:19 0 388703 0 524287 EPSG:900913:20 0 777407 0 1048575 EPSG:900913:21 0 1554814 0 2097151 EPSG:900913:22 0 3109629 0 4194303 EPSG:900913:23 0 6219258 0 8388607 EPSG:900913:24 0 12438517 1 16777215 EPSG:900913:25 0 24877035 2 33554431 EPSG:900913:26 0 49754070 4 67108863 EPSG:900913:27 0 99508140 8 134217727 EPSG:900913:28 0 199016280 16 268435455 EPSG:900913:29 0 398032561 32 536870911 EPSG:900913:30 0 796065123 65 1073741823 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from CSIRO Atmospheric Research, Australia, Mk3.0 Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_csiro_mk3_0_5km_2041-2060_debiasedmean_tas_av_12month_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Flood Hazard 10 Years - SSP5 RCP8.5 - CAF This layer shows the height (in cm) reached by the water in consequence of a flooding event with 10 years return period based on a Upper Boundary climate scenario (RCP8.5). The hydrological model used is the Continuum model (Silvestro et al. 2013 and 2015). It is a continuous, distributed and physically based hydrological model able to reproduce the spatial-temporal evolution of soil moisture, energy fluxes, surface soil temperature, evapotranspiration and discharge. Climate dataset used for the simulation of basin response are the W5E5 Global Meteorological dataset for present climate, and the ISIMIP3b Global Meteorological reanalysis dataset for the futurE climate. In order to generate flood hazard maps, resulting discharge estimates are input to an hydraulic model based on the Manning equation that compute channel uniform flow depth. This simplified approach fits to determine flood maps on large areas. 14.420833333 2.2241666670000004 27.463333333 11.0075 cc_and_health:global_rcp85_h10glob_CentreAfrique_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4720 EPSG:3857:14 7687 8090 8848 9441 EPSG:3857:15 15375 16181 17696 18883 EPSG:3857:16 30751 32363 35393 37767 EPSG:3857:17 61503 64726 70786 75535 EPSG:3857:18 123006 129452 141572 151070 EPSG:3857:19 246013 258904 283145 302140 EPSG:3857:20 492027 517808 566291 604280 EPSG:3857:21 984054 1035616 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Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_jja_NEARREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 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62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Flood hazard frequency -180.0 -90.0 180.0 90.0 ECO-DRR:fl_freq_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 GIRI_Pop_count_2022 -180.0 -59.999999994239985 180.0 84.00833333903576 ECO-DRR:HRSL_wGHSL_pop_count image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 45 0 63 EPSG:3857:7 3 90 0 127 EPSG:3857:8 7 181 0 255 EPSG:3857:9 15 363 0 511 EPSG:3857:10 31 726 0 1023 EPSG:3857:11 62 1453 0 2047 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226879 244988 262387 285446 EPSG:900913:20 453758 489977 524775 570893 EPSG:900913:21 907517 979954 1049551 1141787 EPSG:900913:22 1815034 1959909 2099103 2283575 EPSG:900913:23 3630068 3919818 4198207 4567150 EPSG:900913:24 7260136 7839637 8396414 9134300 EPSG:900913:25 14520272 15679275 16792828 18268601 EPSG:900913:26 29040545 31358551 33585656 36537203 EPSG:900913:27 58081090 62717103 67171312 73074407 EPSG:900913:28 116162180 125434207 134342625 146148814 EPSG:900913:29 232324360 250868415 268685250 292297628 EPSG:900913:30 464648721 501736831 537370500 584595256 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 Combination Tropical cyclone surge/ Sea grasses at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_sea9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Kerala Flood 100 Years RP - Historical Kerala State flood hazard map - Historical. 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EPSG:3857:25 1342190 23102976 0 33553703 EPSG:3857:26 2684381 46205952 0 67107407 EPSG:3857:27 5368763 92411905 1 134214814 EPSG:3857:28 10737526 184823811 2 268429629 EPSG:3857:29 21475052 369647623 4 536859258 EPSG:3857:30 42950105 739295247 9 1073718516 frac_cats_2017_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_2017_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 2019-12_albedo -180.0 -59.995535714 179.995535715 80.004464286 wesr_mountains:2019-12_albedo image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 3 53 0 127 EPSG:4326:7 7 106 0 255 EPSG:4326:8 14 213 0 511 EPSG:4326:9 28 426 0 1023 EPSG:4326:10 56 853 0 2047 EPSG:4326:11 113 1706 0 4095 EPSG:4326:12 227 3413 0 8191 EPSG:4326:13 454 6826 0 16383 EPSG:4326:14 909 13652 0 32767 EPSG:4326:15 1819 27305 0 65535 EPSG:4326:16 3639 54611 0 131070 EPSG:4326:17 7278 109223 0 262140 EPSG:4326:18 14557 218446 0 524281 EPSG:4326:19 29114 436893 0 1048562 EPSG:4326:20 58228 873787 0 2097125 EPSG:4326:21 116456 1747574 0 4194251 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 Areas exposed to extreme heat in Kedougou between 1995 and 2004 Extreme heat is studied by calculating the Land Surface Temperature (LST), defined as the temperature felt when the earth's surface is touched with the hands, or the temperature of the skin on the ground. This temperature estimate is influenced by several parameters, including vegetation and surface emissivity. LST was estimated in relation to Normalized Difference Vegetation Index (NDVI) values determined from red and near-infrared bands. Land surface emissivity (LSE) is recovered directly from thermal infrared bands. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:heat_1995_2004 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 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15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 site_0060_Landsat -10.858176899138206 8.079534492312552 -10.189521743955197 8.79879002262406 test_antonio_mosaics:site_0060_Landsat image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 30 30 EPSG:4326:6 28 29 60 60 EPSG:4326:7 57 58 120 120 EPSG:4326:8 115 116 240 241 EPSG:4326:9 230 233 481 483 EPSG:4326:10 461 466 962 966 EPSG:4326:11 923 932 1924 1932 EPSG:4326:12 1847 1864 3848 3864 EPSG:4326:13 3695 3728 7697 7728 EPSG:4326:14 7391 7456 15395 15456 EPSG:4326:15 14782 14913 30791 30913 EPSG:4326:16 29564 29826 61582 61826 EPSG:4326:17 59128 59652 123165 123652 EPSG:4326:18 118257 119305 246330 247304 EPSG:4326:19 236515 238610 492661 494608 EPSG:4326:20 473031 477221 985322 989217 EPSG:4326:21 946062 954442 1970645 1978435 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 site_0336_19860908_visual_gauss 21.804453393351142 2.163950346428799 22.972377367092143 3.360478793316272 hotspots:site_0336_19860908_visual_gauss image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 15 15 35 36 EPSG:4326:6 30 31 71 72 EPSG:4326:7 61 62 143 144 EPSG:4326:8 123 124 287 288 EPSG:4326:9 246 249 574 577 EPSG:4326:10 492 499 1148 1154 EPSG:4326:11 985 999 2296 2309 EPSG:4326:12 1971 1998 4592 4618 EPSG:4326:13 3943 3997 9184 9237 EPSG:4326:14 7886 7995 18368 18474 EPSG:4326:15 15772 15990 36737 36949 EPSG:4326:16 31544 31980 73474 73899 EPSG:4326:17 63088 63960 146949 147799 EPSG:4326:18 126177 127920 293899 295599 EPSG:4326:19 252355 255841 587798 591199 EPSG:4326:20 504711 511682 1175596 1182399 EPSG:4326:21 1009423 1023364 2351192 2364799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 Combination Flood/Forest at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_flo_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Automn precipitations change (%) for the period 2020 - 2039 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_son_NEARREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Combination Tsunami/Coral reefs at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_cor9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 ken_slope 33.88974434855757 -4.739402006732216 41.937083228471195 5.081234702368131 mapx_chemobs:ken_slope image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 9 9 EPSG:3857:5 15 16 19 19 EPSG:3857:6 31 32 38 39 EPSG:3857:7 62 65 76 78 EPSG:3857:8 124 131 152 157 EPSG:3857:9 248 262 304 315 EPSG:3857:10 497 525 608 631 EPSG:3857:11 995 1050 1216 1262 EPSG:3857:12 1990 2101 2433 2525 EPSG:3857:13 3980 4203 4867 5050 EPSG:3857:14 7960 8407 9734 10100 EPSG:3857:15 15920 16815 19468 20201 EPSG:3857:16 31841 33631 38937 40402 EPSG:3857:17 63683 67263 77874 80804 EPSG:3857:18 127367 134527 155749 161609 EPSG:3857:19 254734 269054 311499 323219 EPSG:3857:20 509468 538108 622999 646438 EPSG:3857:21 1018936 1076216 1245998 1292877 EPSG:3857:22 2037873 2152433 2491996 2585754 EPSG:3857:23 4075747 4304866 4983992 5171508 EPSG:3857:24 8151494 8609732 9967984 10343017 EPSG:3857:25 16302988 17219464 19935969 20686035 EPSG:3857:26 32605977 34438929 39871938 41372070 EPSG:3857:27 65211954 68877859 79743876 82744141 EPSG:3857:28 130423908 137755719 159487752 165488283 EPSG:3857:29 260847817 275511438 318975505 330976567 EPSG:3857:30 521695634 551022876 637951011 661953134 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 9 9 EPSG:4326:4 7 8 19 19 EPSG:4326:5 15 16 38 39 EPSG:4326:6 30 33 76 78 EPSG:4326:7 60 67 152 157 EPSG:4326:8 120 134 304 315 EPSG:4326:9 241 269 608 631 EPSG:4326:10 483 538 1216 1262 EPSG:4326:11 966 1077 2433 2525 EPSG:4326:12 1932 2155 4867 5050 EPSG:4326:13 3864 4311 9734 10100 EPSG:4326:14 7729 8623 19468 20201 EPSG:4326:15 15458 17246 38937 40402 EPSG:4326:16 30917 34493 77874 80804 EPSG:4326:17 61835 68987 155749 161609 EPSG:4326:18 123671 137974 311499 323219 EPSG:4326:19 247343 275948 622999 646438 EPSG:4326:20 494687 551897 1245998 1292877 EPSG:4326:21 989375 1103794 2491996 2585754 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 9 9 EPSG:3857:5 15 16 19 19 EPSG:3857:6 31 32 38 39 EPSG:3857:7 62 65 76 78 EPSG:3857:8 124 131 152 157 EPSG:3857:9 248 262 304 315 EPSG:3857:10 497 525 608 631 EPSG:3857:11 995 1050 1216 1262 EPSG:3857:12 1990 2101 2433 2525 EPSG:3857:13 3980 4203 4867 5050 EPSG:3857:14 7960 8407 9734 10100 EPSG:3857:15 15920 16815 19468 20201 EPSG:3857:16 31841 33631 38937 40402 EPSG:3857:17 63683 67263 77874 80804 EPSG:3857:18 127367 134527 155749 161609 EPSG:3857:19 254734 269054 311499 323219 EPSG:3857:20 509468 538108 622999 646438 EPSG:3857:21 1018936 1076216 1245998 1292877 EPSG:3857:22 2037873 2152433 2491996 2585754 EPSG:3857:23 4075747 4304866 4983992 5171508 EPSG:3857:24 8151494 8609732 9967984 10343017 EPSG:3857:25 16302988 17219464 19935969 20686035 EPSG:3857:26 32605977 34438929 39871938 41372070 EPSG:3857:27 65211954 68877859 79743876 82744141 EPSG:3857:28 130423908 137755719 159487752 165488283 EPSG:3857:29 260847817 275511438 318975505 330976567 EPSG:3857:30 521695634 551022876 637951011 661953134 Eq_phex -180.0 -90.0 180.0 90.0 wesr_risk:Eq_physexp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Marine Range Rarity (Aquamaps) See: <a href="www.aquamaps.org">Kaschner, K., K. Kesner-Reyes, C. Garilao, J. Rius-Barile, T. Rees, and R. Froese. 2016. AquaMaps: Predicted range maps for aquatic species. World wide web electronic publication, www.aquamaps.org, Version 08/2016.</a><br/><br>Under terms of the licence <a href="https://creativecommons.org/licenses/by-nc/3.0/">Aquamaps cannot be used for commercial purposes</a> -180.0 -90.0 180.0 90.0 MapX_UNDP:rrarity image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262143 EPSG:3857:19 0 524287 0 524287 EPSG:3857:20 0 1048575 0 1048575 EPSG:3857:21 0 2097151 0 2097151 EPSG:3857:22 -1 4194303 0 4194304 EPSG:3857:23 -1 8388607 0 8388608 EPSG:3857:24 0 16777215 0 16777215 EPSG:3857:25 0 33554431 0 33554431 EPSG:3857:26 0 67108863 0 67108863 EPSG:3857:27 0 134217727 1 134217727 EPSG:3857:28 -1 268435455 3 268435456 EPSG:3857:29 0 536870911 7 536870911 EPSG:3857:30 0 1073741823 14 1073741823 EPSG:4326 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262143 EPSG:3857:19 0 524287 0 524287 EPSG:3857:20 0 1048575 0 1048575 EPSG:3857:21 -1 2097151 0 2097152 EPSG:3857:22 -1 4194303 0 4194304 EPSG:3857:23 0 8388607 0 8388607 EPSG:3857:24 0 16777215 0 16777215 EPSG:3857:25 0 33554431 0 33554431 EPSG:3857:26 0 67108863 0 67108863 EPSG:3857:27 -1 134217727 1 134217728 EPSG:3857:28 0 268435455 3 268435455 EPSG:3857:29 0 536870911 7 536870911 EPSG:3857:30 -1 1073741823 14 1073741824 Areas exposed to extreme heat in Kedougou between 2015 and 2024 Extreme heat is studied by calculating the Land Surface Temperature (LST), defined as the temperature felt when the earth's surface is touched with the hands, or the temperature of the skin on the ground. This temperature estimate is influenced by several parameters, including vegetation and surface emissivity. LST was estimated in relation to Normalized Difference Vegetation Index (NDVI) values determined from red and near-infrared bands. Land surface emissivity (LSE) is recovered directly from thermal infrared bands. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:heat_2015_2024 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491251 EPSG:4326:20 445870 452589 971450 982502 EPSG:4326:21 891741 905179 1942901 1965005 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 Self-calibrating Palmer Drought Severity Index (scPDSI) 2000-2009 (CRU) This layer shows the average values over the 2000 to 2010 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901 to 2018. Original data were subset and processed using QGIS at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> The dataset has been updated each year using newer versions of CRU TS input data, currently to the end of 2018 using a preliminary version of CRU TS 4.03 (0.5° resolution). <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 UN_Sahel:scPDSI.cru_ts403_2000-2009 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Summer temperature change (°C) for the period 2040 - 2059 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_jja_MIDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from National Center for Atmospheric Research, PCM1 Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_ncar_pcm1_5km_2041-2060_debiasedmean_tas_av12_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 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cc_and_health:mean_temp_2001_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 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29650 16131 16339 EPSG:3857:17 58850 59301 32263 32678 EPSG:3857:18 117701 118602 64527 65356 EPSG:3857:19 235403 237205 129054 130712 EPSG:3857:20 470806 474410 258109 261425 EPSG:3857:21 941612 948821 516219 522850 EPSG:3857:22 1883224 1897643 1032439 1045701 EPSG:3857:23 3766449 3795286 2064879 2091402 EPSG:3857:24 7532899 7590573 4129759 4182805 EPSG:3857:25 15065799 15181146 8259518 8365611 EPSG:3857:26 30131598 30362292 16519037 16731222 EPSG:3857:27 60263197 60724584 33038074 33462444 EPSG:3857:28 120526394 121449168 66076148 66924889 EPSG:3857:29 241052788 242898337 132152297 133849779 EPSG:3857:30 482105577 485796674 264304595 267699559 K3-ELU-LF -180.0 -56.00013888888891 179.99999999999926 83.62486111111086 wesr_mountains:K3-ELU-LF image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 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131071 EPSG:3857:18 10582 180514 0 262143 EPSG:3857:19 21165 361028 0 524287 EPSG:3857:20 42331 722057 0 1048575 EPSG:3857:21 84663 1444114 0 2097152 EPSG:3857:22 169327 2888228 0 4194304 EPSG:3857:23 338654 5776457 0 8388607 EPSG:3857:24 677308 11552914 0 16777215 EPSG:3857:25 1354617 23105829 0 33554431 EPSG:3857:26 2709234 46211658 0 67108863 EPSG:3857:27 5418468 92423316 0 134217728 EPSG:3857:28 10836937 184846632 0 268435455 EPSG:3857:29 21673875 369693264 0 536870911 EPSG:3857:30 43347750 739386528 0 1073741824 Winter temperature change (°C) for the period 2080 - 2099 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_djf_ENDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 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62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Hydrography - Water Lines river only 14.311495526534399 2.0622926391050047 27.534422769575563 11.020842231641868 cc_and_health:vWaterLines_river_only image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 253 276 295 EPSG:3857:10 480 506 552 590 EPSG:3857:11 960 1012 1105 1180 EPSG:3857:12 1921 2024 2210 2361 EPSG:3857:13 3843 4049 4421 4722 EPSG:3857:14 7687 8098 8843 9445 EPSG:3857:15 15374 16196 17686 18890 EPSG:3857:16 30749 32392 35373 37780 EPSG:3857:17 61498 64784 70746 75560 EPSG:3857:18 122996 129569 141493 151121 EPSG:3857:19 245993 259139 282986 302243 EPSG:3857:20 491987 518279 565973 604487 EPSG:3857:21 983975 1036559 1131946 1208975 EPSG:3857:22 1967950 2073119 2263893 2417951 EPSG:3857:23 3935901 4146238 4527786 4835902 EPSG:3857:24 7871802 8292477 9055572 9671805 EPSG:3857:25 15743605 16584954 18111144 19343610 EPSG:3857:26 31487211 33169909 36222288 38687220 EPSG:3857:27 62974422 66339819 72444576 77374440 EPSG:3857:28 125948844 132679639 144889152 154748881 EPSG:3857:29 251897689 265359278 289778305 309497763 EPSG:3857:30 503795378 530718556 579556610 618995526 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 125 276 295 EPSG:4326:9 224 250 552 590 EPSG:4326:10 449 500 1105 1180 EPSG:4326:11 898 1000 2210 2361 EPSG:4326:12 1797 2001 4421 4722 EPSG:4326:13 3594 4002 8843 9445 EPSG:4326:14 7188 8004 17686 18890 EPSG:4326:15 14377 16008 35373 37780 EPSG:4326:16 28755 32017 70746 75560 EPSG:4326:17 57510 64034 141493 151121 EPSG:4326:18 115021 128068 282986 302243 EPSG:4326:19 230043 256137 565973 604487 EPSG:4326:20 460086 512274 1131946 1208975 EPSG:4326:21 920173 1024548 2263893 2417951 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 253 276 295 EPSG:3857:10 480 506 552 590 EPSG:3857:11 960 1012 1105 1180 EPSG:3857:12 1921 2024 2210 2361 EPSG:3857:13 3843 4049 4421 4722 EPSG:3857:14 7687 8098 8843 9445 EPSG:3857:15 15374 16196 17686 18890 EPSG:3857:16 30749 32392 35373 37780 EPSG:3857:17 61498 64784 70746 75560 EPSG:3857:18 122996 129569 141493 151121 EPSG:3857:19 245993 259139 282986 302243 EPSG:3857:20 491987 518279 565973 604487 EPSG:3857:21 983975 1036559 1131946 1208975 EPSG:3857:22 1967950 2073119 2263893 2417951 EPSG:3857:23 3935901 4146238 4527786 4835902 EPSG:3857:24 7871802 8292477 9055572 9671805 EPSG:3857:25 15743605 16584954 18111144 19343610 EPSG:3857:26 31487211 33169909 36222288 38687220 EPSG:3857:27 62974422 66339819 72444576 77374440 EPSG:3857:28 125948844 132679639 144889152 154748881 EPSG:3857:29 251897689 265359278 289778305 309497763 EPSG:3857:30 503795378 530718556 579556610 618995526 h1000ic 0.1675000015994978 11.697500041616369 16.000833334932196 23.52416670828256 risk_niger_undp:h1000ic image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 3 8 8 EPSG:4326:4 5 6 16 17 EPSG:4326:5 11 13 32 34 EPSG:4326:6 23 27 64 69 EPSG:4326:7 47 55 128 139 EPSG:4326:8 94 111 256 278 EPSG:4326:9 189 222 512 557 EPSG:4326:10 378 445 1024 1115 EPSG:4326:11 756 890 2049 2230 EPSG:4326:12 1512 1781 4099 4460 EPSG:4326:13 3025 3563 8199 8920 EPSG:4326:14 6050 7127 16399 17840 EPSG:4326:15 12101 14254 32798 35680 EPSG:4326:16 24203 28509 65596 71361 EPSG:4326:17 48406 57018 131193 142723 EPSG:4326:18 96812 114036 262387 285446 EPSG:4326:19 193624 228072 524775 570893 EPSG:4326:20 387249 456145 1049551 1141787 EPSG:4326:21 774499 912290 2099103 2283575 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 3 3 4 4 EPSG:900913:4 6 7 8 8 EPSG:900913:5 13 14 16 17 EPSG:900913:6 27 29 32 34 EPSG:900913:7 55 59 64 69 EPSG:900913:8 110 119 128 139 EPSG:900913:9 221 239 256 278 EPSG:900913:10 443 478 512 557 EPSG:900913:11 886 956 1024 1115 EPSG:900913:12 1772 1913 2049 2230 EPSG:900913:13 3544 3827 4099 4460 EPSG:900913:14 7089 7655 8199 8920 EPSG:900913:15 14179 15311 16399 17840 EPSG:900913:16 28359 30623 32798 35680 EPSG:900913:17 56719 61247 65596 71361 EPSG:900913:18 113439 122494 131193 142723 EPSG:900913:19 226879 244988 262387 285446 EPSG:900913:20 453758 489977 524775 570893 EPSG:900913:21 907517 979954 1049551 1141787 EPSG:900913:22 1815034 1959909 2099103 2283575 EPSG:900913:23 3630068 3919818 4198207 4567150 EPSG:900913:24 7260136 7839637 8396414 9134300 EPSG:900913:25 14520272 15679275 16792828 18268601 EPSG:900913:26 29040545 31358551 33585656 36537203 EPSG:900913:27 58081090 62717103 67171312 73074407 EPSG:900913:28 116162180 125434207 134342625 146148814 EPSG:900913:29 232324360 250868415 268685250 292297628 EPSG:900913:30 464648721 501736831 537370500 584595256 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 Spring precipitations change (%) for the period 2020 - 2039 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_mam_NEARREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 land_degradation_global_GeoEssential This dataset has been generated using the Trends.Earth model to asses Land Degradation according to the UN Metadata Guideline for SDG. <br> More information on <a href= "http://trends.earth/docs/en/" target="_blank">Trends.Earth</a>. <br> More information on <a href="https://knowledge.unccd.int/topics/sustainable-development-goals-sdgs/sdg-indicator-1531" target= "_blank">Land Degradation</a>. <br> More information on <a href="https://unstats.un.org/sdgs/metadata/files/Metadata-15-03-01.pdf" target="_blank">SDG15.3.1</a>. <br> <br> Generated using the GEOEssential VLab -180.0 -55.920126210999996 180.0 83.63539874 wesr_sdg:land_degradation_global_GeoEssential image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 176 0 255 EPSG:3857:9 20 352 0 511 EPSG:3857:10 41 704 0 1023 EPSG:3857:11 82 1409 0 2047 EPSG:3857:12 164 2818 0 4095 EPSG:3857:13 328 5637 0 8191 EPSG:3857:14 657 11275 0 16383 EPSG:3857:15 1314 22551 0 32767 EPSG:3857:16 2628 45102 0 65535 EPSG:3857:17 5256 90205 0 131071 EPSG:3857:18 10513 180410 0 262143 EPSG:3857:19 21027 360820 0 524287 EPSG:3857:20 42055 721640 0 1048575 EPSG:3857:21 84110 1443281 0 2097151 EPSG:3857:22 168220 2886563 0 4194304 EPSG:3857:23 336441 5773126 0 8388608 EPSG:3857:24 672882 11546253 0 16777215 EPSG:3857:25 1345764 23092506 0 33554431 EPSG:3857:26 2691528 46185012 0 67108863 EPSG:3857:27 5383057 92370024 0 134217727 EPSG:3857:28 10766115 184740049 0 268435456 EPSG:3857:29 21532231 369480098 0 536870911 EPSG:3857:30 43064462 738960197 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 4 103 0 255 EPSG:4326:8 9 207 0 511 EPSG:4326:9 18 415 0 1023 EPSG:4326:10 36 830 0 2047 EPSG:4326:11 72 1660 0 4095 EPSG:4326:12 144 3320 0 8191 EPSG:4326:13 289 6640 0 16383 EPSG:4326:14 579 13281 0 32767 EPSG:4326:15 1158 26563 0 65535 EPSG:4326:16 2317 53127 0 131071 EPSG:4326:17 4634 106255 0 262143 EPSG:4326:18 9269 212511 0 524287 EPSG:4326:19 18538 425023 0 1048575 EPSG:4326:20 37076 850046 0 2097151 EPSG:4326:21 74152 1700092 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 176 0 255 EPSG:3857:9 20 352 0 511 EPSG:3857:10 41 704 0 1023 EPSG:3857:11 82 1409 0 2047 EPSG:3857:12 164 2818 0 4095 EPSG:3857:13 328 5637 0 8191 EPSG:3857:14 657 11275 0 16383 EPSG:3857:15 1314 22551 0 32767 EPSG:3857:16 2628 45102 0 65535 EPSG:3857:17 5256 90205 0 131071 EPSG:3857:18 10513 180410 0 262143 EPSG:3857:19 21027 360820 0 524287 EPSG:3857:20 42055 721640 0 1048575 EPSG:3857:21 84110 1443281 0 2097152 EPSG:3857:22 168220 2886563 0 4194304 EPSG:3857:23 336441 5773126 0 8388607 EPSG:3857:24 672882 11546253 0 16777215 EPSG:3857:25 1345764 23092506 0 33554431 EPSG:3857:26 2691528 46185012 0 67108863 EPSG:3857:27 5383057 92370024 0 134217728 EPSG:3857:28 10766115 184740049 0 268435455 EPSG:3857:29 21532231 369480098 0 536870911 EPSG:3857:30 43064462 738960197 0 1073741824 Combination Tropical cyclone/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcw_for6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mammals of the World (Jenkins, Pimm & Joppa - 2013) Maps of mammal diversity include the total species richness, major taxonomic Orders (Cetartiodactyla, Carnivora, Primates, Eulipotyphla, Chiroptera, Rodentia), marsupials, threatened species, and small-ranged species. Species considered small-ranged are those with a geographic range size smaller than the global median (i.e., the 50% of species with the smallest ranges). Maps are based on data from the IUCN, July 2013 update. All maps were generated at a spatial resolution of 10×10 km and use the Eckert IV equal-area projection. Maps represent native, extant species only. Tables of the mammal species included are available for download here: http://biodiversitymapping.org/wordpress/index.php/mammals/ Direct Link to download:http://biodiversitymapping.org/wordpress/index.php/download/ -179.50889388818507 -85.69633751266441 179.53549311992452 83.78813167493983 MAPX_nd:wld_richness_mammals_10km image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 4 127 0 127 EPSG:3857:8 9 255 0 255 EPSG:3857:9 18 511 0 511 EPSG:3857:10 37 1023 1 1022 EPSG:3857:11 74 2047 2 2045 EPSG:3857:12 148 4095 5 4090 EPSG:3857:13 296 8191 11 8181 EPSG:3857:14 593 16383 22 16362 EPSG:3857:15 1187 32767 44 32725 EPSG:3857:16 2374 65535 89 65451 EPSG:3857:17 4749 131071 178 130902 EPSG:3857:18 9498 262143 357 261805 EPSG:3857:19 18996 524287 715 523611 EPSG:3857:20 37993 1048575 1430 1047223 EPSG:3857:21 75986 2097151 2860 2094446 EPSG:3857:22 151973 4194303 5721 4188892 EPSG:3857:23 303946 8388607 11443 8377784 EPSG:3857:24 607893 16777215 22887 16755568 EPSG:3857:25 1215787 33554431 45774 33511136 EPSG:3857:26 2431574 67108863 91548 67022273 EPSG:3857:27 4863148 134217727 183097 134044547 EPSG:3857:28 9726297 268435455 366195 268089094 EPSG:3857:29 19452594 536870911 732390 536178189 EPSG:3857:30 38905189 1073741823 1464780 1072356378 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 62 0 127 EPSG:4326:7 4 124 0 255 EPSG:4326:8 8 249 0 511 EPSG:4326:9 17 499 1 1022 EPSG:4326:10 35 999 2 2045 EPSG:4326:11 70 1999 5 4090 EPSG:4326:12 141 3998 11 8181 EPSG:4326:13 282 7996 22 16362 EPSG:4326:14 565 15992 44 32725 EPSG:4326:15 1130 31984 89 65451 EPSG:4326:16 2261 63969 178 130902 EPSG:4326:17 4523 127938 357 261805 EPSG:4326:18 9046 255876 715 523611 EPSG:4326:19 18093 511752 1430 1047223 EPSG:4326:20 36186 1023505 2860 2094446 EPSG:4326:21 72373 2047010 5721 4188892 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 1 31 0 31 EPSG:900913:6 2 63 0 63 EPSG:900913:7 4 127 0 127 EPSG:900913:8 9 255 0 255 EPSG:900913:9 18 511 0 511 EPSG:900913:10 37 1023 1 1022 EPSG:900913:11 74 2047 2 2045 EPSG:900913:12 148 4095 5 4090 EPSG:900913:13 296 8191 11 8181 EPSG:900913:14 593 16383 22 16362 EPSG:900913:15 1187 32767 44 32725 EPSG:900913:16 2374 65535 89 65451 EPSG:900913:17 4749 131071 178 130902 EPSG:900913:18 9498 262143 357 261805 EPSG:900913:19 18996 524287 715 523611 EPSG:900913:20 37993 1048575 1430 1047223 EPSG:900913:21 75986 2097151 2860 2094446 EPSG:900913:22 151973 4194303 5721 4188892 EPSG:900913:23 303946 8388607 11443 8377784 EPSG:900913:24 607893 16777215 22887 16755568 EPSG:900913:25 1215787 33554431 45774 33511136 EPSG:900913:26 2431574 67108863 91548 67022273 EPSG:900913:27 4863148 134217727 183097 134044547 EPSG:900913:28 9726297 268435455 366195 268089094 EPSG:900913:29 19452594 536870911 732390 536178189 EPSG:900913:30 38905189 1073741823 1464780 1072356378 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 4 127 0 127 EPSG:3857:8 9 255 0 255 EPSG:3857:9 18 511 0 511 EPSG:3857:10 37 1023 1 1022 EPSG:3857:11 74 2047 2 2045 EPSG:3857:12 148 4095 5 4090 EPSG:3857:13 296 8191 11 8181 EPSG:3857:14 593 16383 22 16362 EPSG:3857:15 1187 32767 44 32725 EPSG:3857:16 2374 65535 89 65451 EPSG:3857:17 4749 131071 178 130902 EPSG:3857:18 9498 262143 357 261805 EPSG:3857:19 18996 524287 715 523611 EPSG:3857:20 37993 1048575 1430 1047223 EPSG:3857:21 75986 2097151 2860 2094446 EPSG:3857:22 151973 4194303 5721 4188892 EPSG:3857:23 303946 8388607 11443 8377784 EPSG:3857:24 607893 16777215 22887 16755568 EPSG:3857:25 1215787 33554431 45774 33511136 EPSG:3857:26 2431574 67108863 91548 67022273 EPSG:3857:27 4863148 134217727 183097 134044547 EPSG:3857:28 9726297 268435455 366195 268089094 EPSG:3857:29 19452594 536870911 732390 536178189 EPSG:3857:30 38905189 1073741823 1464780 1072356378 Forest Structual Condition Index (SCI) - Africa The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> 4.291832979587211 -7.903071018846623 35.40579740803463 6.8343008700661745 MapX_UNDP:africaSCI image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 16 19 EPSG:3857:6 30 33 32 38 EPSG:3857:7 61 66 65 76 EPSG:3857:8 123 133 131 153 EPSG:3857:9 246 267 262 306 EPSG:3857:10 492 534 524 612 EPSG:3857:11 985 1069 1048 1225 EPSG:3857:12 1970 2138 2096 2450 EPSG:3857:13 3940 4276 4193 4901 EPSG:3857:14 7880 8552 8387 9803 EPSG:3857:15 15760 17105 16774 19606 EPSG:3857:16 31520 34211 33549 39213 EPSG:3857:17 63041 68422 67098 78426 EPSG:3857:18 126083 136845 134197 156853 EPSG:3857:19 252167 273690 268394 313707 EPSG:3857:20 504334 547380 536788 627414 EPSG:3857:21 1008668 1094761 1073577 1254829 EPSG:3857:22 2017337 2189522 2147155 2509659 EPSG:3857:23 4034674 4379045 4294310 5019318 EPSG:3857:24 8069348 8758091 8588621 10038637 EPSG:3857:25 16138697 17516182 17177243 20077275 EPSG:3857:26 32277394 35032365 34354487 40154551 EPSG:3857:27 64554788 70064730 68708975 80309102 EPSG:3857:28 129109576 140129460 137417950 160618204 EPSG:3857:29 258219152 280258921 274835901 321236408 EPSG:3857:30 516438305 560517843 549671802 642472816 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 8 16 19 EPSG:4326:5 14 17 32 38 EPSG:4326:6 29 34 65 76 EPSG:4326:7 59 69 131 153 EPSG:4326:8 118 139 262 306 EPSG:4326:9 236 278 524 612 EPSG:4326:10 473 556 1048 1225 EPSG:4326:11 946 1113 2096 2450 EPSG:4326:12 1892 2227 4193 4901 EPSG:4326:13 3784 4455 8387 9803 EPSG:4326:14 7569 8911 16774 19606 EPSG:4326:15 15139 17822 33549 39213 EPSG:4326:16 30279 35645 67098 78426 EPSG:4326:17 60559 71290 134197 156853 EPSG:4326:18 121118 142581 268394 313707 EPSG:4326:19 242237 285163 536788 627414 EPSG:4326:20 484475 570326 1073577 1254829 EPSG:4326:21 968950 1140653 2147155 2509659 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 16 19 EPSG:3857:6 30 33 32 38 EPSG:3857:7 61 66 65 76 EPSG:3857:8 123 133 131 153 EPSG:3857:9 246 267 262 306 EPSG:3857:10 492 534 524 612 EPSG:3857:11 985 1069 1048 1225 EPSG:3857:12 1970 2138 2096 2450 EPSG:3857:13 3940 4276 4193 4901 EPSG:3857:14 7880 8552 8387 9803 EPSG:3857:15 15760 17105 16774 19606 EPSG:3857:16 31520 34211 33549 39213 EPSG:3857:17 63041 68422 67098 78426 EPSG:3857:18 126083 136845 134197 156853 EPSG:3857:19 252167 273690 268394 313707 EPSG:3857:20 504334 547380 536788 627414 EPSG:3857:21 1008668 1094761 1073577 1254829 EPSG:3857:22 2017337 2189522 2147155 2509659 EPSG:3857:23 4034674 4379045 4294310 5019318 EPSG:3857:24 8069348 8758091 8588621 10038637 EPSG:3857:25 16138697 17516182 17177243 20077275 EPSG:3857:26 32277394 35032365 34354487 40154551 EPSG:3857:27 64554788 70064730 68708975 80309102 EPSG:3857:28 129109576 140129460 137417950 160618204 EPSG:3857:29 258219152 280258921 274835901 321236408 EPSG:3857:30 516438305 560517843 549671802 642472816 Crops yield 2010 (FAO) The production yield for the main crops for the year 2010 is derived from the sub-theme 'Area, Yield and Production' of the theme 5: 'Actual Yields and Production' of GAEZ v4 of the FAO. The sub-theme presents maps of the spatial distribution of harvested areas (1000 ha), production (1000 tons) and yield (t/ha) for 26 major crops/crop groups for 3-year averages of 1999-2001 (representing year 2000) and 2009–2011 (representing 2010). Together, these 26 crop commodities account for all recorded crop production of each delineated spatial allocation unit (i.e., a country) for which crop statistics were assembled. Yield and production are provided in fresh/harvested weight. -180.0 -90.0 180.0 90.0 unccd:all_2010_yld_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mean temperatures 2000 - Central African Republic Mean observed temperatures in 2000 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2000_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 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EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Spectral Acceleration 1.0 Sec 475 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_10_s_475_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 POP_SANGHA_2019_finale_Worlpop_opt 13.12388346995083 0.0357446152097114 16.999434297770676 2.722915245020809 AccessMod:POP_SANGHA_2019_finale_Worlpop_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 15 15 17 17 EPSG:3857:6 31 31 34 35 EPSG:3857:7 63 63 68 70 EPSG:3857:8 126 127 137 140 EPSG:3857:9 252 255 274 280 EPSG:3857:10 504 511 549 560 EPSG:3857:11 1008 1023 1098 1120 EPSG:3857:12 2017 2047 2197 2241 EPSG:3857:13 4034 4095 4394 4482 EPSG:3857:14 8068 8190 8789 8965 EPSG:3857:15 16136 16380 17578 17931 EPSG:3857:16 32272 32761 35157 35862 EPSG:3857:17 64544 65522 70314 71725 EPSG:3857:18 129088 131045 140628 143450 EPSG:3857:19 258176 262091 281257 286901 EPSG:3857:20 516353 524183 562514 573802 EPSG:3857:21 1032707 1048367 1125028 1147604 EPSG:3857:22 2065415 2096735 2250056 2295209 EPSG:3857:23 4130831 4193471 4500112 4590419 EPSG:3857:24 8261663 8386942 9000225 9180839 EPSG:3857:25 16523326 16773884 18000450 18361678 EPSG:3857:26 33046652 33547768 36000901 36723356 EPSG:3857:27 66093305 67095537 72001802 73446712 EPSG:3857:28 132186610 134191074 144003604 146893424 EPSG:3857:29 264373221 268382149 288007209 293786849 EPSG:3857:30 528746442 536764299 576014419 587573699 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 7 7 17 17 EPSG:4326:5 15 15 34 35 EPSG:4326:6 31 31 68 70 EPSG:4326:7 62 63 137 140 EPSG:4326:8 124 127 274 280 EPSG:4326:9 248 255 549 560 EPSG:4326:10 496 511 1098 1120 EPSG:4326:11 993 1023 2197 2241 EPSG:4326:12 1986 2047 4394 4482 EPSG:4326:13 3972 4094 8789 8965 EPSG:4326:14 7944 8188 17578 17931 EPSG:4326:15 15888 16377 35157 35862 EPSG:4326:16 31776 32754 70314 71725 EPSG:4326:17 63553 65509 140628 143450 EPSG:4326:18 127106 131019 281257 286901 EPSG:4326:19 254212 262039 562514 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33547768 36000901 36723356 EPSG:3857:27 66093305 67095537 72001802 73446712 EPSG:3857:28 132186610 134191074 144003604 146893424 EPSG:3857:29 264373221 268382149 288007209 293786849 EPSG:3857:30 528746442 536764299 576014419 587573699 Threatened species richness This raster layer represents the number of threatened species of mammals, amphibians and birds potentially occurring in each ~1km grid cell. Species range data were rasterised at 30 arc-seconds (approximately 1km at the equator) from IUCN Red List polygons (IUCN 2020) for those with a Red List status of Critically Endangered, Endangered or Vulnerable. Raster layers for each species were summed together with equal weighting into a single richness layer.<br><br>The species included are used as a proxy to represent threatened terrestrial biodiversity and are based on taxonomic groups that have been comprehensively assessed by IUCN Red List. Thus users should be aware of the taxonomic bias and that marine values are based only on marine species of mammals and birds.<br/><br>Source: IUCN 2020. The IUCN Red List of Threatened Species. Version 2020-4 <a href="http://www.iucnredlist.org" target="_blank">IUCNRedList</a>.<br><br>Terms of Use: <a href="http://www.iucnredlist.org/info/terms-of-use" target="_blank">Commercial use is not permitted</a><br/> -179.995201157628 -84.69466806618583 179.8859620772232 85.91771612300938 MapX_UNDP:threatened_species_richness_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 126 0 127 EPSG:3857:8 0 253 0 255 EPSG:3857:9 0 506 0 511 EPSG:3857:10 0 1012 0 1023 EPSG:3857:11 0 2025 0 2047 EPSG:3857:12 0 4050 0 4094 EPSG:3857:13 0 8101 0 8189 EPSG:3857:14 0 16202 0 16378 EPSG:3857:15 0 32404 0 32757 EPSG:3857:16 0 64809 0 65515 EPSG:3857:17 0 129619 1 131030 EPSG:3857:18 0 259238 3 262060 EPSG:3857:19 0 518476 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1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Combination Tsunami/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_for6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Flood recurrence map between 1995 and 2024 The northeastern part of the Kédougou region is the most affected, particularly the Saraya department. This situation is largely due to the overflowing of the Falémé River and several backwaters. These rivers, the main tributaries of the Senegal River, leave their banks after intense rains, causing flooding, as evidenced by the events of 2024. Flooding in Saraya is also aggravated by water erosion, as demonstrated by the mechanisms described in the study by Boissy et al. (2022). Intense and prolonged rainfall leads to erosion of soils already weakened by a low-permeability geological substrate and rugged terrain. In addition, human activities (agriculture, gold mining) disrupt soil stability. These factors, coupled with steep slopes (up to 61.57%), concentrate the flow towards low-lying areas, creating conditions conducive to flooding. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:flood image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491251 EPSG:4326:20 445870 452589 971450 982502 EPSG:4326:21 891741 905179 1942901 1965005 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 Automn temperature change (°C) for the period 2040 - 2059 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_son_MIDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Ocean acidification Changes in CO2 concentration alter the aragonite saturation state (ASS) of the ocean, among other chemical properties of seawater, and as ASS levels drop the ability of calcifying species such as corals and shelled invertebrates to create calcium carbonate structures declines (S22). The global distribution of ASS values has been modeled at 1- degree resolution for pre-industrial (circa 1870) and modern times (2000-2009) (S23). KNB used the difference between these values as an estimate of the human-derived driver of changes in ocean acidification. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS." -180.0 -90.0 180.0 90.0 unea_pollution:13_ocean_acidification image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:900913 Average year temperature anomalies (2021-2022) over 1991-2020 climatology Average year temperature anomalies in °Celsius across the period 2021-2022 calculated over the average temperatures per year in the period 1991-2020 (climatology). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_21_22_anom9120 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 vulnerable_soil_organic_carbon_density_opt -179.9999463166003 -81.81909663334687 179.9999737471548 81.81933800928408 MapX_UNDP:vulnerable_soil_organic_carbon_density_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 1 14 0 15 EPSG:3857:5 2 29 0 31 EPSG:3857:6 5 58 0 63 EPSG:3857:7 10 117 0 127 EPSG:3857:8 20 235 0 255 EPSG:3857:9 41 470 0 511 EPSG:3857:10 82 941 0 1023 EPSG:3857:11 164 1883 0 2047 EPSG:3857:12 328 3767 0 4095 EPSG:3857:13 656 7535 0 8191 EPSG:3857:14 1313 15070 0 16383 EPSG:3857:15 2626 30140 0 32767 EPSG:3857:16 5253 60281 0 65535 EPSG:3857:17 10507 120563 0 131071 EPSG:3857:18 21014 241127 0 262143 EPSG:3857:19 42029 482255 0 524287 EPSG:3857:20 84059 964511 0 1048575 EPSG:3857:21 168118 1929023 0 2097151 EPSG:3857:22 336236 3858047 0 4194303 EPSG:3857:23 672473 7716094 1 8388607 EPSG:3857:24 1344947 15432189 2 16777214 EPSG:3857:25 2689895 30864378 5 33554429 EPSG:3857:26 5379791 61728756 10 67108859 EPSG:3857:27 10759583 123457512 20 134217718 EPSG:3857:28 21519166 246915024 40 268435436 EPSG:3857:29 43038332 493830049 80 536870872 EPSG:3857:30 86076665 987660099 160 1073741745 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 30 0 63 EPSG:4326:6 2 61 0 127 EPSG:4326:7 5 122 0 255 EPSG:4326:8 11 244 0 511 EPSG:4326:9 23 488 0 1023 EPSG:4326:10 46 977 0 2047 EPSG:4326:11 93 1954 0 4095 EPSG:4326:12 186 3909 0 8191 EPSG:4326:13 372 7819 0 16383 EPSG:4326:14 744 15639 0 32767 EPSG:4326:15 1489 31278 0 65535 EPSG:4326:16 2978 62557 0 131071 EPSG:4326:17 5956 125114 0 262143 EPSG:4326:18 11913 250229 0 524287 EPSG:4326:19 23827 500459 0 1048575 EPSG:4326:20 47655 1000918 0 2097151 EPSG:4326:21 95311 2001837 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 1 14 0 15 EPSG:3857:5 2 29 0 31 EPSG:3857:6 5 58 0 63 EPSG:3857:7 10 117 0 127 EPSG:3857:8 20 235 0 255 EPSG:3857:9 41 470 0 511 EPSG:3857:10 82 941 0 1023 EPSG:3857:11 164 1883 0 2047 EPSG:3857:12 328 3767 0 4095 EPSG:3857:13 656 7535 0 8191 EPSG:3857:14 1313 15070 0 16383 EPSG:3857:15 2626 30140 0 32767 EPSG:3857:16 5253 60281 0 65535 EPSG:3857:17 10507 120563 0 131071 EPSG:3857:18 21014 241127 0 262143 EPSG:3857:19 42029 482255 0 524287 EPSG:3857:20 84059 964511 0 1048575 EPSG:3857:21 168118 1929023 0 2097151 EPSG:3857:22 336236 3858047 0 4194303 EPSG:3857:23 672473 7716094 1 8388607 EPSG:3857:24 1344947 15432189 2 16777214 EPSG:3857:25 2689895 30864378 5 33554429 EPSG:3857:26 5379791 61728756 10 67108859 EPSG:3857:27 10759583 123457512 20 134217718 EPSG:3857:28 21519166 246915024 40 268435436 EPSG:3857:29 43038332 493830049 80 536870872 EPSG:3857:30 86076665 987660099 160 1073741745 2001-2010 Average year temperature change since previous decade (1991-2000) Average year temperature anomalies in °C across the period 2001-2010 calculated over the average temperature per year in the period 1991-2000. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_01_10_anom_91_00 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Phospate (summer) - WOA13 World Ocean Atlas 2013 (WOA13) is a long-term set of objectively analyzed climatologies of temperature, salinity, oxygen, phosphate, silicate, and nitrate for annual, seasonal, and monthly periods for the World Ocean. Data (at surface) are expressed in µmol/l -180.0 -78.0 180.0 90.0 unea_pollution:ph_summ image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 0 119 0 255 EPSG:4326:8 0 238 0 511 EPSG:4326:9 0 477 0 1023 EPSG:4326:10 0 955 0 2047 EPSG:4326:11 0 1911 0 4095 EPSG:4326:12 0 3822 0 8191 EPSG:4326:13 0 7645 0 16383 EPSG:4326:14 0 15291 0 32767 EPSG:4326:15 0 30583 0 65535 EPSG:4326:16 0 61166 0 131071 EPSG:4326:17 0 122333 0 262143 EPSG:4326:18 0 244667 0 524287 EPSG:4326:19 0 489335 0 1048575 EPSG:4326:20 0 978670 0 2097151 EPSG:4326:21 0 1957341 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 13 0 15 EPSG:900913:5 0 27 0 31 EPSG:900913:6 0 54 0 63 EPSG:900913:7 0 109 0 127 EPSG:900913:8 0 219 0 255 EPSG:900913:9 0 439 0 511 EPSG:900913:10 0 879 0 1023 EPSG:900913:11 0 1758 0 2047 EPSG:900913:12 0 3516 0 4095 EPSG:900913:13 0 7033 0 8191 EPSG:900913:14 0 14066 0 16383 EPSG:900913:15 0 28132 0 32767 EPSG:900913:16 0 56265 0 65535 EPSG:900913:17 0 112531 0 131071 EPSG:900913:18 0 225062 0 262143 EPSG:900913:19 0 450124 0 524287 EPSG:900913:20 0 900249 0 1048575 EPSG:900913:21 0 1800498 0 2097151 EPSG:900913:22 0 3600997 0 4194303 EPSG:900913:23 0 7201994 0 8388607 EPSG:900913:24 0 14403989 0 16777215 EPSG:900913:25 0 28807979 0 33554431 EPSG:900913:26 0 57615958 0 67108863 EPSG:900913:27 0 115231917 0 134217727 EPSG:900913:28 0 230463834 0 268435455 EPSG:900913:29 0 460927668 0 536870911 EPSG:900913:30 0 921855337 0 1073741823 Summer precipitations change (%) for the period 2020 - 2039 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_jja_NEARREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Landslide hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:ls_phex_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Flood hazard frequency 60.879999999999995 23.709999999999994 75.38 36.9 UNDAC-PAK:fl_freq_P3_pak_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 10 11 EPSG:3857:5 12 13 21 22 EPSG:3857:6 24 27 42 45 EPSG:3857:7 49 55 85 90 EPSG:3857:8 99 110 171 181 EPSG:3857:9 199 221 342 363 EPSG:3857:10 398 442 685 726 EPSG:3857:11 797 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190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 7 11 EPSG:4326:4 3 8 14 22 EPSG:4326:5 7 16 28 45 EPSG:4326:6 15 32 57 90 EPSG:4326:7 31 65 115 181 EPSG:4326:8 63 130 230 362 EPSG:4326:9 127 260 460 725 EPSG:4326:10 255 520 921 1450 EPSG:4326:11 511 1041 1843 2901 EPSG:4326:12 1023 2082 3686 5802 EPSG:4326:13 2047 4164 7372 11605 EPSG:4326:14 4095 8328 14745 23210 EPSG:4326:15 8191 16657 29491 46421 EPSG:4326:16 16383 33314 58982 92842 EPSG:4326:17 32767 66628 117964 185685 EPSG:4326:18 65535 133256 235929 371370 EPSG:4326:19 131071 266513 471859 742741 EPSG:4326:20 262143 533026 943718 1485482 EPSG:4326:21 524287 1066052 1887436 2970965 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 230 362 EPSG:3857:10 368 516 460 725 EPSG:3857:11 736 1032 921 1450 EPSG:3857:12 1473 2065 1843 2901 EPSG:3857:13 2946 4130 3686 5802 EPSG:3857:14 5893 8260 7372 11605 EPSG:3857:15 11787 16520 14745 23210 EPSG:3857:16 23574 33041 29491 46421 EPSG:3857:17 47149 66082 58982 92842 EPSG:3857:18 94299 132164 117964 185685 EPSG:3857:19 188599 264328 235929 371370 EPSG:3857:20 377199 528657 471859 742741 EPSG:3857:21 754398 1057315 943718 1485482 EPSG:3857:22 1508796 2114630 1887436 2970965 EPSG:3857:23 3017592 4229260 3774873 5941930 EPSG:3857:24 6035184 8458521 7549747 11883861 EPSG:3857:25 12070369 16917042 15099494 23767722 EPSG:3857:26 24140738 33834084 30198988 47535445 EPSG:3857:27 48281477 67668168 60397977 95070890 EPSG:3857:28 96562954 135336336 120795955 190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 Oil Spill Deepwater On April 20, 2010, an explosion on the Deepwater Horizon Macondo oil well drilling platform tragically killed 11 workers, and started the largest marine oil spill in U.S. history, releasing millions of barrels of oil into the Gulf of Mexico. NOAA was on the scene from the earliest moments of the crisis, bringing more than 25 years of experience protecting and restoring our coasts from oil spills. -96.4439 23.45089999999986 -81.18219999999984 36.9407 unea_pollution_nd:oil20100325 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 0 1 EPSG:4326:2 1 1 1 2 EPSG:4326:3 2 2 3 4 EPSG:4326:4 4 5 7 8 EPSG:4326:5 9 11 14 17 EPSG:4326:6 18 23 29 35 EPSG:4326:7 37 47 59 70 EPSG:4326:8 75 94 118 140 EPSG:4326:9 150 189 237 281 EPSG:4326:10 301 378 475 562 EPSG:4326:11 603 757 950 1124 EPSG:4326:12 1207 1514 1901 2248 EPSG:4326:13 2414 3028 3802 4497 EPSG:4326:14 4829 6057 7605 8994 EPSG:4326:15 9659 12114 15210 17989 EPSG:4326:16 19318 24229 30421 35978 EPSG:4326:17 38636 48459 60843 71956 EPSG:4326:18 77273 96919 121687 143913 EPSG:4326:19 154546 193838 243374 287827 EPSG:4326:20 309092 387676 486749 575655 EPSG:4326:21 618185 775353 973499 1151310 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 0 0 EPSG:900913:2 1 1 0 1 EPSG:900913:3 3 3 1 2 EPSG:900913:4 6 6 3 4 EPSG:900913:5 12 13 7 8 EPSG:900913:6 24 27 14 17 EPSG:900913:7 49 55 29 35 EPSG:900913:8 99 110 59 70 EPSG:900913:9 199 221 118 140 EPSG:900913:10 398 443 237 281 EPSG:900913:11 797 886 475 562 EPSG:900913:12 1595 1773 950 1124 EPSG:900913:13 3190 3546 1901 2248 EPSG:900913:14 6380 7093 3802 4497 EPSG:900913:15 12761 14187 7605 8994 EPSG:900913:16 25522 28374 15210 17989 EPSG:900913:17 51044 56748 30421 35978 EPSG:900913:18 102088 113497 60843 71956 EPSG:900913:19 204176 226995 121687 143913 EPSG:900913:20 408353 453991 243374 287827 EPSG:900913:21 816706 907982 486749 575655 EPSG:900913:22 1633413 1815964 973499 1151310 EPSG:900913:23 3266827 3631929 1946998 2302621 EPSG:900913:24 6533655 7263859 3893996 4605243 EPSG:900913:25 13067311 14527718 7787992 9210486 EPSG:900913:26 26134623 29055436 15575985 18420973 EPSG:900913:27 52269247 58110873 31151971 36841946 EPSG:900913:28 104538495 116221747 62303943 73683892 EPSG:900913:29 209076991 232443494 124607887 147367784 EPSG:900913:30 418153983 464886989 249215775 294735568 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from NOAA Geophysical Fluid Dynamics Laboratory, CM2.0 Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_gfdl_cm2_0_5km_2041-2060_debiasedmean_tas_av_12mon_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Projected timing of annual severe bleaching (annual exceedance of 8 Degree Heating Weeks of thermal stress in reef areas) under SSPP2-4.5 using CMIP6 models. The data and complementary report have two purposes, and are intended for use by the global coral reef scientific and management community, which had these 2 objectives. Objective 1. To present projections of coral bleaching conditions (i.e., exposure to the primary climate threat to coral reefs) and potential adaptation at a spatial scale that enables use of the data in management and conservation planning and in support of other decisions influencing coral reefs and reef use. Objective 2. To evaluate the implications of the Paris Agreement as well as failure to achieve its goal, by comparing the projected timing of annual severe bleaching between Shared Socioeconomic Pathways SSP5-8.5 and SSP2-4.5. Data source used: Intergovernmental Panel on Climate Change (IPCC) Coupled Model Interpolation Project Phase 6 (CMIP6) model outputs for sea surface temperature (https://www.ipcc-data.org/), combined with United States National Oceanic and Atmospheric Administration (NOAA) CoralTemp data from NOAA Coral Reef Watch (https://www.coralreefwatch.noaa.gov/product/5km/index_5km_sst.php). -180.0 -90.0 180.0 90.0 wesr_climat:asb_year_0_ssp245 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Gridded Livestock of the World – Cattle This updated layer of The Gridded Livestock of the World (GLW)database provided modelled livestock densities of the world, adjusted to match official (FAOSTAT)national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 565 km at the equator).Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analyticalprocedure has been revised and extended to include a more systematic assessment of model accuracy and therepresentation of uncertainties associated with the predictions.<br><br>For further details on mapping methods see: Robinson, T.P., Wint, G.R.W., Conchedda, G., Van Boeckel, T.P., Ercoli, V., Palamara, E., Cinardi, G., D’Aietti, L., Hay, S.I., Gilbert, M., 2014. Mapping the Global Distribution of Livestock. PLoS ONE 9, e96084. <a href=\"https://doi.org/10.1371/journal.pone.0096084\"target=_blank>https://doi.org/10.1371/journal.pone.0096084</a><br/><br>These digital layers are made publically available via the Livestock Geo-Wiki (<a href=\"http://www.livestock.geo-wiki.org\"target=_blank>livestock.geo-wiki.org</a><br/> -180.0 -90.0 180.0 90.0 MapX_UNDP:Glb_Cattle_CC2006_AD image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Year precipitations 2019 - Central African Republic Total precipitations observed in 2019 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2019_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Self-calibrating Palmer Drought Severity Index (scPDSI) 1991-2000 (CRU) This layer shows the average values over the 1991 to 2000 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_91_00_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_mambo_bado_20190220 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20190220 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 Travel_time_final_Senegal2_opt -17.55393284087355 12.29686893595293 -11.27780942134996 16.693373854449966 AccessMod:Travel_time_final_Senegal2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 28 29 28 29 EPSG:3857:7 57 59 57 59 EPSG:3857:8 115 119 115 119 EPSG:3857:9 231 238 231 239 EPSG:3857:10 463 476 462 479 EPSG:3857:11 927 953 924 959 EPSG:3857:12 1855 1907 1848 1919 EPSG:3857:13 3710 3814 3696 3839 EPSG:3857:14 7421 7628 7393 7678 EPSG:3857:15 14842 15256 14786 15357 EPSG:3857:16 29685 30512 29572 30714 EPSG:3857:17 59370 61024 59144 61429 EPSG:3857:18 118740 122048 118289 122859 EPSG:3857:19 237481 244096 236579 245719 EPSG:3857:20 474962 488192 473158 491438 EPSG:3857:21 949924 976385 946316 982877 EPSG:3857:22 1899848 1952770 1892633 1965755 EPSG:3857:23 3799697 3905540 3785267 3931511 EPSG:3857:24 7599394 7811081 7570535 7863023 EPSG:3857:25 15198788 15622163 15141070 15726047 EPSG:3857:26 30397577 31244326 30282141 31452095 EPSG:3857:27 60795154 62488652 60564283 62904191 EPSG:3857:28 121590308 124977304 121128566 125808383 EPSG:3857:29 243180617 249954608 242257133 251616767 EPSG:3857:30 486361234 499909216 484514267 503233535 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 29 EPSG:4326:6 26 27 57 59 EPSG:4326:7 52 55 115 119 EPSG:4326:8 104 110 231 239 EPSG:4326:9 208 221 462 479 EPSG:4326:10 417 442 924 959 EPSG:4326:11 834 884 1848 1919 EPSG:4326:12 1668 1768 3696 3839 EPSG:4326:13 3336 3536 7393 7678 EPSG:4326:14 6672 7072 14786 15357 EPSG:4326:15 13345 14145 29572 30714 EPSG:4326:16 26690 28290 59144 61429 EPSG:4326:17 53380 56581 118289 122859 EPSG:4326:18 106760 113163 236579 245719 EPSG:4326:19 213521 226326 473158 491438 EPSG:4326:20 427042 452653 946316 982877 EPSG:4326:21 854084 905307 1892633 1965755 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 28 29 28 29 EPSG:3857:7 57 59 57 59 EPSG:3857:8 115 119 115 119 EPSG:3857:9 231 238 231 239 EPSG:3857:10 463 476 462 479 EPSG:3857:11 927 953 924 959 EPSG:3857:12 1855 1907 1848 1919 EPSG:3857:13 3710 3814 3696 3839 EPSG:3857:14 7421 7628 7393 7678 EPSG:3857:15 14842 15256 14786 15357 EPSG:3857:16 29685 30512 29572 30714 EPSG:3857:17 59370 61024 59144 61429 EPSG:3857:18 118740 122048 118289 122859 EPSG:3857:19 237481 244096 236579 245719 EPSG:3857:20 474962 488192 473158 491438 EPSG:3857:21 949924 976385 946316 982877 EPSG:3857:22 1899848 1952770 1892633 1965755 EPSG:3857:23 3799697 3905540 3785267 3931511 EPSG:3857:24 7599394 7811081 7570535 7863023 EPSG:3857:25 15198788 15622163 15141070 15726047 EPSG:3857:26 30397577 31244326 30282141 31452095 EPSG:3857:27 60795154 62488652 60564283 62904191 EPSG:3857:28 121590308 124977304 121128566 125808383 EPSG:3857:29 243180617 249954608 242257133 251616767 EPSG:3857:30 486361234 499909216 484514267 503233535 Coastal Vulnerability Index (only environmental variables) The Coastal Vulnerability Index (only environmental variables) shows the susceptibility of coastal areas to extreme climate impacts and their capacity to recover, survive, and adapt depending on their geo-morphological and ecological conditions. Combination of climate related / environmental variables: - Elevation; - Coastal slope; - Land roughness; - Distance from the shoreline; - Ecosystem health. Area: Morocco Child Project: SCCF Source: GEF-MedProgramme -6.243055555556 34.513854833210004 -3.8041666647160004 35.922465945448 medprogramme:MOR_cvi_only_env_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 6 6 7 7 EPSG:3857:5 12 12 15 15 EPSG:3857:6 25 25 30 31 EPSG:3857:7 50 50 61 62 EPSG:3857:8 100 101 123 125 EPSG:3857:9 201 203 247 250 EPSG:3857:10 402 407 494 501 EPSG:3857:11 804 814 988 1002 EPSG:3857:12 1609 1629 1976 2004 EPSG:3857:13 3219 3258 3953 4009 EPSG:3857:14 6438 6516 7907 8018 EPSG:3857:15 12876 13033 15815 16037 EPSG:3857:16 25752 26066 31631 32075 EPSG:3857:17 51504 52132 63262 64150 EPSG:3857:18 103009 104265 126525 128301 EPSG:3857:19 206019 208531 253051 256603 EPSG:3857:20 412039 417062 506103 513207 EPSG:3857:21 824079 834124 1012207 1026415 EPSG:3857:22 1648159 1668248 2024415 2052830 EPSG:3857:23 3296318 3336497 4048830 4105660 EPSG:3857:24 6592637 6672995 8097660 8211320 EPSG:3857:25 13185274 13345990 16195321 16422641 EPSG:3857:26 26370549 26691980 32390642 32845283 EPSG:3857:27 52741099 53383961 64781284 65690567 EPSG:3857:28 105482198 106767923 129562568 131381135 EPSG:3857:29 210964396 213535847 259125136 262762271 EPSG:3857:30 421928792 427071695 518250273 525524542 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 2 2 7 7 EPSG:4326:4 4 4 15 15 EPSG:4326:5 9 9 30 31 EPSG:4326:6 19 19 61 62 EPSG:4326:7 38 39 123 125 EPSG:4326:8 76 78 247 250 EPSG:4326:9 153 157 494 501 EPSG:4326:10 307 315 988 1002 EPSG:4326:11 615 631 1976 2004 EPSG:4326:12 1230 1262 3953 4009 EPSG:4326:13 2461 2525 7907 8018 EPSG:4326:14 4922 5050 15815 16037 EPSG:4326:15 9844 10100 31631 32075 EPSG:4326:16 19689 20201 63262 64150 EPSG:4326:17 39378 40403 126525 128301 EPSG:4326:18 78756 80807 253051 256603 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EPSG:3857:26 26370549 26691980 32390642 32845283 EPSG:3857:27 52741099 53383961 64781284 65690567 EPSG:3857:28 105482198 106767923 129562568 131381135 EPSG:3857:29 210964396 213535847 259125136 262762271 EPSG:3857:30 421928792 427071695 518250273 525524542 dredging_points20122024vf_pg -176.72401428222656 -54.81700134277344 178.04800415039062 79.69800567626953 sand:dredging_points20122024vf_pg image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 10 0 15 EPSG:3857:5 3 21 0 31 EPSG:3857:6 7 43 0 63 EPSG:3857:7 14 87 1 127 EPSG:3857:8 29 174 2 254 EPSG:3857:9 59 349 4 509 EPSG:3857:10 119 699 9 1018 EPSG:3857:11 239 1398 18 2036 EPSG:3857:12 479 2796 37 4073 EPSG:3857:13 958 5593 74 8147 EPSG:3857:14 1917 11187 149 16295 EPSG:3857:15 3834 22374 298 32590 EPSG:3857:16 7668 44749 596 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298 32590 EPSG:4326:15 1875 26363 596 65180 EPSG:4326:16 3750 52726 1192 130361 EPSG:4326:17 7501 105452 2385 260722 EPSG:4326:18 15003 210905 4771 521445 EPSG:4326:19 30006 421810 9542 1042890 EPSG:4326:20 60013 843620 19084 2085780 EPSG:4326:21 120026 1687240 38168 4171561 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 10 0 15 EPSG:3857:5 3 21 0 31 EPSG:3857:6 7 43 0 63 EPSG:3857:7 14 87 1 127 EPSG:3857:8 29 174 2 254 EPSG:3857:9 59 349 4 509 EPSG:3857:10 119 699 9 1018 EPSG:3857:11 239 1398 18 2036 EPSG:3857:12 479 2796 37 4073 EPSG:3857:13 958 5593 74 8147 EPSG:3857:14 1917 11187 149 16295 EPSG:3857:15 3834 22374 298 32590 EPSG:3857:16 7668 44749 596 65180 EPSG:3857:17 15337 89498 1192 130361 EPSG:3857:18 30675 178996 2385 260722 EPSG:3857:19 61351 357993 4770 521445 EPSG:3857:20 122703 715986 9541 1042890 EPSG:3857:21 245407 1431972 19083 2085780 EPSG:3857:22 490815 2863945 38167 4171561 EPSG:3857:23 981630 5727891 76335 8343123 EPSG:3857:24 1963261 11455783 152671 16686246 EPSG:3857:25 3926522 22911566 305343 33372492 EPSG:3857:26 7853045 45823133 610687 66744985 EPSG:3857:27 15706091 91646267 1221375 133489971 EPSG:3857:28 31412183 183292535 2442751 266979942 EPSG:3857:29 62824366 366585070 4885503 533959884 EPSG:3857:30 125648733 733170140 9771007 1067919769 Areas of Global Significance for Biodiversity Conservation, Carbon Storage, and Water Provision <span style="font-size:1em"> This map is the result of a global joint optimization of valuable biodiversity, carbon storage and water regulation. This analysis collated distribution data for over 180000 terrestrial vertebrate and plant species globally, removing unsuitable areas using information on species' habitat preferences and species' known altitudinal limits or, where unknown, by removing anthropogenically modified land. <br /> <br /> Given existing biases in taxonomic coverage for plant species, we calculated 10 representative sets of species, containing approximately 10% of species of each taxonomic group. For carbon we used the combined amount of above-ground and below-ground biomass carbon density and vulnerable soil organic carbon density. For water we took potential water regulation outputs from the WaterWorld model normalized by water basin. We then determined those areas globally that jointly contributed the most to biodiversity, carbon and water conservation if up to 10%, 20%, or 100% of the Earth were to be protected. <br> <br> <u>References:</u> <ul> <li> Jung, M., et al. (2020). Areas of global importance for terrestrial biodiversity, carbon, and water. BioRxiv. <a href="https://www.biorxiv.org/content/10.1101/2020.04.16.021444v1" target="_blank">biorxiv.org/content/10.1101/2020.04.16.021444v1</a>. </li> </ul> </span> -179.995201157628 -84.69466806618583 179.8859620772232 85.91771612300938 MapX_UNDP:conservation_biodiversity_carbon_water_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 126 0 127 EPSG:3857:8 0 253 0 255 EPSG:3857:9 0 506 0 511 EPSG:3857:10 0 1012 0 1023 EPSG:3857:11 0 2025 0 2047 EPSG:3857:12 0 4050 0 4094 EPSG:3857:13 0 8101 0 8189 EPSG:3857:14 0 16202 0 16378 EPSG:3857:15 0 32404 0 32757 EPSG:3857:16 0 64809 0 65515 EPSG:3857:17 0 129619 1 131030 EPSG:3857:18 0 259238 3 262060 EPSG:3857:19 0 518476 6 524121 EPSG:3857:20 0 1036953 13 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-3.075687270143314 28.181206954060514 -3.0642747063483102 rs_for_asgm:mosaic_2019_kamituga_west image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 520 592 592 EPSG:3857:11 1041 1041 1184 1184 EPSG:3857:12 2082 2083 2368 2368 EPSG:3857:13 4165 4166 4736 4737 EPSG:3857:14 8331 8332 9473 9474 EPSG:3857:15 16663 16664 18947 18949 EPSG:3857:16 33326 33328 37895 37898 EPSG:3857:17 66652 66656 75791 75796 EPSG:3857:18 133304 133312 151582 151592 EPSG:3857:19 266608 266625 303165 303185 EPSG:3857:20 533217 533250 606330 606371 EPSG:3857:21 1066435 1066501 1212660 1212743 EPSG:3857:22 2132870 2133003 2425321 2425486 EPSG:3857:23 4265740 4266007 4850642 4850973 EPSG:3857:24 8531481 8532014 9701284 9701947 EPSG:3857:25 17062963 17064028 19402568 19403894 EPSG:3857:26 34125926 34128057 38805137 38807789 EPSG:3857:27 68251853 68256114 77610274 77615579 EPSG:3857:28 136503706 136512228 155220549 155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 264 592 592 EPSG:4326:10 529 529 1184 1184 EPSG:4326:11 1058 1058 2368 2368 EPSG:4326:12 2117 2117 4736 4737 EPSG:4326:13 4235 4235 9473 9474 EPSG:4326:14 8470 8471 18947 18949 EPSG:4326:15 16941 16943 37895 37898 EPSG:4326:16 33883 33887 75791 75796 EPSG:4326:17 67767 67775 151582 151592 EPSG:4326:18 135534 135551 303165 303185 EPSG:4326:19 271069 271102 606330 606371 EPSG:4326:20 542138 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EPSG:3857:27 68251853 68256114 77610274 77615579 EPSG:3857:28 136503706 136512228 155220549 155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 Automn precipitations change (%) for the period 2080 - 2099 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_son_ENDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Marine Proportional Range Rarity (Aquamaps) See: <a href="www.aquamaps.org">Kaschner, K., K. Kesner-Reyes, C. Garilao, J. Rius-Barile, T. Rees, and R. Froese. 2016. AquaMaps: Predicted range maps for aquatic species. World wide web electronic publication, www.aquamaps.org, Version 08/2016.</a><br/><br>Under terms of the licence <a href="https://creativecommons.org/licenses/by-nc/3.0/">Aquamaps cannot be used for commercial purposes</a> -180.0 -90.0 180.0 90.0 MapX_UNDP:prrarity image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262143 EPSG:3857:19 0 524287 0 524287 EPSG:3857:20 0 1048575 0 1048575 EPSG:3857:21 0 2097151 0 2097151 EPSG:3857:22 -1 4194303 0 4194304 EPSG:3857:23 -1 8388607 0 8388608 EPSG:3857:24 0 16777215 0 16777215 EPSG:3857:25 0 33554431 0 33554431 EPSG:3857:26 0 67108863 0 67108863 EPSG:3857:27 0 134217727 1 134217727 EPSG:3857:28 -1 268435455 3 268435456 EPSG:3857:29 0 536870911 7 536870911 EPSG:3857:30 0 1073741823 14 1073741823 EPSG:4326 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262143 EPSG:3857:19 0 524287 0 524287 EPSG:3857:20 0 1048575 0 1048575 EPSG:3857:21 -1 2097151 0 2097152 EPSG:3857:22 -1 4194303 0 4194304 EPSG:3857:23 0 8388607 0 8388607 EPSG:3857:24 0 16777215 0 16777215 EPSG:3857:25 0 33554431 0 33554431 EPSG:3857:26 0 67108863 0 67108863 EPSG:3857:27 -1 134217727 1 134217728 EPSG:3857:28 0 268435455 3 268435455 EPSG:3857:29 0 536870911 7 536870911 EPSG:3857:30 -1 1073741823 14 1073741824 International Boundaries Polygons Level 0 - ESRI -180.0 -90.0 180.0 84.533821105957 grid_data_core:esri_boundaries2015 image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 7 255 0 511 EPSG:4326:9 15 511 0 1023 EPSG:4326:10 31 1023 0 2047 EPSG:4326:11 62 2047 0 4095 EPSG:4326:12 124 4095 0 8191 EPSG:4326:13 248 8191 0 16383 EPSG:4326:14 497 16383 0 32767 EPSG:4326:15 995 32767 0 65535 EPSG:4326:16 1990 65535 0 131071 EPSG:4326:17 3980 131071 0 262143 EPSG:4326:18 7960 262143 0 524287 EPSG:4326:19 15921 524287 0 1048575 EPSG:4326:20 31842 1048575 0 2097151 EPSG:4326:21 63685 2097151 0 4194303 EPSG:900913 Cities with more than 1'000 inhabitants -180.0 -38.1779518127441 180.0 71.8351974487305 grid_data_core:city1k_gis image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 2 0 7 EPSG:4326:3 0 5 0 15 EPSG:4326:4 1 11 0 31 EPSG:4326:5 3 22 0 63 EPSG:4326:6 6 45 0 127 EPSG:4326:7 12 91 0 255 EPSG:4326:8 25 182 0 511 EPSG:4326:9 51 364 0 1023 EPSG:4326:10 103 729 0 2047 EPSG:4326:11 206 1458 0 4095 EPSG:4326:12 413 2916 0 8191 EPSG:4326:13 826 5833 0 16383 EPSG:4326:14 1653 11667 0 32767 EPSG:4326:15 3306 23334 0 65535 EPSG:4326:16 6613 46668 0 131071 EPSG:4326:17 13227 93336 0 262143 EPSG:4326:18 26454 186672 0 524287 EPSG:4326:19 52908 373345 0 1048575 EPSG:4326:20 105817 746690 0 2097151 EPSG:4326:21 211635 1493381 0 4194303 EPSG:900913 Central Congo Basin non-peat-forming forest probability (2022) Metadata for files in the zip archive: Crezee_2022_Central_Congo_Peat_Probability_Layers.zip This folder contains 5 probability layers, the output of 1000 classification runs using a random 2/3 subset of training data, that was used to produce the peatland extent estimates and probability map (Figure 1b) in: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This folder contains 5 layers: - Probability_2022_HardwoodDominatedPeatSwamp.tif - Probability_2022_PalmDominatedPeatSwamp.tif - Probability_2022_NonPeatFormingForest.tif - Probability_2022_Savanna.tif - Probability_2022_Water.tif Each layer has pixel values from 0-1000, representing the number of times that class was given as the most likely class for that pixel in 1000 Maximum Likelihood classifications using a random 2/3 subset of the training data. For example, a value of 995 in the Probability_2022_Water.tif file means that in 995 of the 1000 runs this pixel was mapped as 'water'. Conversely, a value of 4 in the Probability_2022_Savanna.tif would mean that that pixel was only mapped as savanna 4 times in the 1000 runs. As an approximation, dividing these values by 1000 gives the probability that that pixel contains a majority of vegetation of that class. Total peat swamp forest probability is obtained by summing the probabilities of the hardwood and palm-dominated peat swamp forest files. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 15.0 -4.999916949999999 25.72744828 3.30533333 peatlands:Crezee_2022_Probability_NonPeatFormingForest image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 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9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 Dogondoutchi_Severity_78_T25 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Severity_78_T25 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 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239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 Global habitats <style> .p1 { overflow: auto; font-style: italic; font-size: .9em; padding: 10px; margin: 0; text-align: justify; -moz-hyphens: auto; -webkit-hyphens: auto; -ms-hypens: auto; -ms-hyphens: auto; hyphens: auto; max-height: 230px; overflow-x: auto; overflow-y: hidden; columns: 180px; column-rule: 1px solid #ccc; grid-column-gap: 10px; column-gap: 10px; } ul { list-style-type: none; padding: 0; } ul li { margin-bottom: 5px; } </style> <div class="p1"><p>This map provides area-based estimates of at least 75 habitat types at ~100m resolution, placing it among some of the most comprehensive global maps of habitats that can be used for biodiversity assessments.The map follows the thematic legend of habitat classes as defined by the IUCN habitat classification system and maps as many terrestrial, freshwater and marine habitats as possible at global scale.</p><p>To create the habitat type map we used land-cover data from the Copernicus land-cover product as well as the most recent data for the world's climatic zones based on the global Köppen-geiger climate classification system and the distribution of biomes. We relied on ancillary datasets describing the global distribution of mountains, wetlands, intertidal zones or mangroves as well as currently best available global datasets on human pressures.</p><p><u>See:</u><ul><li>Jung, M., Dahal, P.R., Butchart, S.H.M., Donald, P.F., De Lamo, X., Lesiv, M., Kapos, V., Rondinini, C., Visconti, P., (2020). A global map of terrestrial habitat types. Sci. Data 7, 256. <a href="https://www.nature.com/articles/s41597-020-00599-8" target="_blank">www.nature.com/articles/s41597-020-00599-8.</a></li></ul></p></div> -179.99917662946004 -81.81826968418555 179.9994217980732 81.81855607761675 MapX_UNDP:global_habitat_v004_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 1 14 0 15 EPSG:3857:5 2 29 0 31 EPSG:3857:6 5 58 0 63 EPSG:3857:7 10 117 0 127 EPSG:3857:8 20 235 0 255 EPSG:3857:9 41 470 0 511 EPSG:3857:10 82 941 0 1023 EPSG:3857:11 164 1883 0 2047 EPSG:3857:12 328 3767 0 4095 EPSG:3857:13 656 7535 0 8191 EPSG:3857:14 1313 15070 0 16383 EPSG:3857:15 2627 30140 0 32767 EPSG:3857:16 5254 60280 0 65535 EPSG:3857:17 10509 120561 0 131071 EPSG:3857:18 21018 241123 0 262143 EPSG:3857:19 42037 482247 1 524287 EPSG:3857:20 84075 964494 2 1048574 EPSG:3857:21 168150 1928989 4 2097148 EPSG:3857:22 336300 3857979 9 4194297 EPSG:3857:23 672601 7715959 19 8388594 EPSG:3857:24 1345203 15431918 38 16777189 EPSG:3857:25 2690407 30863836 76 33554378 EPSG:3857:26 5380815 61727672 153 67108756 EPSG:3857:27 10761631 123455345 306 134217512 EPSG:3857:28 21523263 246910691 613 268435024 EPSG:3857:29 43046527 493821383 1227 536870049 EPSG:3857:30 86093054 987642767 2455 1073740099 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 30 0 63 EPSG:4326:6 2 61 0 127 EPSG:4326:7 5 122 0 255 EPSG:4326:8 11 244 0 511 EPSG:4326:9 23 488 0 1023 EPSG:4326:10 46 977 0 2047 EPSG:4326:11 93 1954 0 4095 EPSG:4326:12 186 3909 0 8191 EPSG:4326:13 372 7819 0 16383 EPSG:4326:14 744 15639 0 32767 EPSG:4326:15 1489 31278 0 65535 EPSG:4326:16 2978 62557 0 131071 EPSG:4326:17 5957 125114 0 262143 EPSG:4326:18 11915 250228 1 524287 EPSG:4326:19 23830 500456 2 1048574 EPSG:4326:20 47660 1000913 4 2097148 EPSG:4326:21 95320 2001827 9 4194297 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 1 14 0 15 EPSG:3857:5 2 29 0 31 EPSG:3857:6 5 58 0 63 EPSG:3857:7 10 117 0 127 EPSG:3857:8 20 235 0 255 EPSG:3857:9 41 470 0 511 EPSG:3857:10 82 941 0 1023 EPSG:3857:11 164 1883 0 2047 EPSG:3857:12 328 3767 0 4095 EPSG:3857:13 656 7535 0 8191 EPSG:3857:14 1313 15070 0 16383 EPSG:3857:15 2627 30140 0 32767 EPSG:3857:16 5254 60280 0 65535 EPSG:3857:17 10509 120561 0 131071 EPSG:3857:18 21018 241123 0 262143 EPSG:3857:19 42037 482247 1 524287 EPSG:3857:20 84075 964494 2 1048574 EPSG:3857:21 168150 1928989 4 2097148 EPSG:3857:22 336300 3857979 9 4194297 EPSG:3857:23 672601 7715959 19 8388594 EPSG:3857:24 1345203 15431918 38 16777189 EPSG:3857:25 2690407 30863836 76 33554378 EPSG:3857:26 5380815 61727672 153 67108756 EPSG:3857:27 10761631 123455345 306 134217512 EPSG:3857:28 21523263 246910691 613 268435024 EPSG:3857:29 43046527 493821383 1227 536870049 EPSG:3857:30 86093054 987642767 2455 1073740099 Average year temperature anomalies (2001-2010) against 1901-1920 Average year temperature anomalies in °Celsius across the period 2001-2010 calculated over the average temperatures per year in the period 1901-1920 (as close as possible to the pre-industrial era). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_01_10_anom_1901_1920 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Tropical Cyclone Sum of Wind -180.0 -90.0 179.99599307699998 83.99199665399996 wesr_risk:cy_sumwinds image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 63 2047 0 2047 EPSG:3857:12 126 4095 0 4095 EPSG:3857:13 253 8191 0 8191 EPSG:3857:14 506 16383 0 16383 EPSG:3857:15 1012 32767 0 32767 EPSG:3857:16 2025 65535 0 65535 EPSG:3857:17 4051 131071 0 131070 EPSG:3857:18 8103 262143 0 262141 EPSG:3857:19 16206 524287 0 524282 EPSG:3857:20 32413 1048575 0 1048564 EPSG:3857:21 64827 2097151 0 2097128 EPSG:3857:22 129655 4194303 0 4194257 EPSG:3857:23 259311 8388607 0 8388514 EPSG:3857:24 518622 16777215 0 16777029 EPSG:3857:25 1037245 33554431 0 33554058 EPSG:3857:26 2074490 67108863 0 67108117 EPSG:3857:27 4148981 134217727 0 134216234 EPSG:3857:28 8297963 268435455 0 268432468 EPSG:3857:29 16595927 536870911 0 536864936 EPSG:3857:30 33191854 1073741823 0 1073729872 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1093 32767 0 65535 EPSG:4326:16 2187 65535 0 131070 EPSG:4326:17 4374 131071 0 262141 EPSG:4326:18 8749 262143 0 524282 EPSG:4326:19 17499 524287 0 1048564 EPSG:4326:20 34999 1048575 0 2097128 EPSG:4326:21 69998 2097151 0 4194257 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 63 2047 0 2047 EPSG:3857:12 126 4095 0 4095 EPSG:3857:13 253 8191 0 8191 EPSG:3857:14 506 16383 0 16383 EPSG:3857:15 1012 32767 0 32767 EPSG:3857:16 2025 65535 0 65535 EPSG:3857:17 4051 131071 0 131070 EPSG:3857:18 8103 262143 0 262141 EPSG:3857:19 16206 524287 0 524282 EPSG:3857:20 32413 1048575 0 1048564 EPSG:3857:21 64827 2097151 0 2097128 EPSG:3857:22 129655 4194303 0 4194257 EPSG:3857:23 259311 8388607 0 8388514 EPSG:3857:24 518622 16777215 0 16777029 EPSG:3857:25 1037245 33554431 0 33554058 EPSG:3857:26 2074490 67108863 0 67108117 EPSG:3857:27 4148981 134217727 0 134216234 EPSG:3857:28 8297963 268435455 0 268432468 EPSG:3857:29 16595927 536870911 0 536864936 EPSG:3857:30 33191854 1073741823 0 1073729872 Peak Ground Acceleration PGA 475 Years (cm/s2) For the GAR Atlas, a fully probabilistic seismic hazard analysis at global level was developed by CIMNE and INGENIAR Ltda. This hazard model is a continuation and improvement of the one developed in the framework of GAR13 where a set of tectonic provinces were identified and characterized by means of a set of parameters that describe the future seismic activity on each of them based on historical records together with relationships to obtain hazard intensities as a function of magnitude and distance. The hazard analysis was performed using the program CRISIS2014, a state-of-the-art tool for these kinds of tasks and widely known and acknowledged by experts in the field across the world. The chosen hazard intensity measure for this case was spectral acceleration and to guarantee a good connection between the hazard and the exposure characteristics, results for several ordinates beteween 0.0 and 2.3 seconds were computed. More details about the probabilistic seismic hazard analysis can be found in Cardona et al. (2015). -180.0 -90.0 180.0 90.0 wesr_risk:pga_475_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 TZA_Kilombero_LULC2014 34.553167266769464 -10.038048450490551 37.239835341004294 -7.663994368030097 TEEB:Kilombero_LULC2014_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 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EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 mozambique_remote_site_screening_res50 30.217320000000004 -26.86869848999992 40.84082000000001 -10.472198489999924 mapx_chemobs:mozambique_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 9 9 9 EPSG:3857:5 16 18 18 19 EPSG:3857:6 33 36 37 39 EPSG:3857:7 67 73 74 78 EPSG:3857:8 135 147 149 157 EPSG:3857:9 270 295 298 314 EPSG:3857:10 541 591 597 628 EPSG:3857:11 1083 1182 1195 1256 EPSG:3857:12 2167 2365 2391 2512 EPSG:3857:13 4335 4731 4783 5025 EPSG:3857:14 8671 9462 9567 10050 EPSG:3857:15 17342 18924 19134 20101 EPSG:3857:16 34685 37849 38268 40202 EPSG:3857:17 69370 75698 76537 80405 EPSG:3857:18 138740 151396 153075 160811 EPSG:3857:19 277480 302792 306151 321622 EPSG:3857:20 554961 605585 612302 643245 EPSG:3857:21 1109923 1211171 1224604 1286491 EPSG:3857:22 2219847 2422342 2449209 2572982 EPSG:3857:23 4439694 4844685 4898418 5145964 EPSG:3857:24 8879388 9689371 9796837 10291928 EPSG:3857:25 17758776 19378742 19593674 20583856 EPSG:3857:26 35517552 38757484 39187348 41167712 EPSG:3857:27 71035104 77514968 78374697 82335425 EPSG:3857:28 142070208 155029936 156749394 164670850 EPSG:3857:29 284140416 310059873 313498789 329341701 EPSG:3857:30 568280833 620119746 626997579 658683402 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 5 9 9 EPSG:4326:4 8 10 18 19 EPSG:4326:5 17 20 37 39 EPSG:4326:6 35 41 74 78 EPSG:4326:7 71 83 149 157 EPSG:4326:8 142 166 298 314 EPSG:4326:9 285 332 597 628 EPSG:4326:10 571 664 1195 1256 EPSG:4326:11 1143 1329 2391 2512 EPSG:4326:12 2286 2659 4783 5025 EPSG:4326:13 4572 5318 9567 10050 EPSG:4326:14 9145 10637 19134 20101 EPSG:4326:15 18290 21275 38268 40202 EPSG:4326:16 36580 42550 76537 80405 EPSG:4326:17 73161 85101 153075 160811 EPSG:4326:18 146323 170202 306151 321622 EPSG:4326:19 292646 340404 612302 643245 EPSG:4326:20 585292 680809 1224604 1286491 EPSG:4326:21 1170585 1361619 2449209 2572982 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 9 9 9 EPSG:3857:5 16 18 18 19 EPSG:3857:6 33 36 37 39 EPSG:3857:7 67 73 74 78 EPSG:3857:8 135 147 149 157 EPSG:3857:9 270 295 298 314 EPSG:3857:10 541 591 597 628 EPSG:3857:11 1083 1182 1195 1256 EPSG:3857:12 2167 2365 2391 2512 EPSG:3857:13 4335 4731 4783 5025 EPSG:3857:14 8671 9462 9567 10050 EPSG:3857:15 17342 18924 19134 20101 EPSG:3857:16 34685 37849 38268 40202 EPSG:3857:17 69370 75698 76537 80405 EPSG:3857:18 138740 151396 153075 160811 EPSG:3857:19 277480 302792 306151 321622 EPSG:3857:20 554961 605585 612302 643245 EPSG:3857:21 1109923 1211171 1224604 1286491 EPSG:3857:22 2219847 2422342 2449209 2572982 EPSG:3857:23 4439694 4844685 4898418 5145964 EPSG:3857:24 8879388 9689371 9796837 10291928 EPSG:3857:25 17758776 19378742 19593674 20583856 EPSG:3857:26 35517552 38757484 39187348 41167712 EPSG:3857:27 71035104 77514968 78374697 82335425 EPSG:3857:28 142070208 155029936 156749394 164670850 EPSG:3857:29 284140416 310059873 313498789 329341701 EPSG:3857:30 568280833 620119746 626997579 658683402 Peak Ground Acceleration PGA 975 Years (cm/s2) For the GAR Atlas, a fully probabilistic seismic hazard analysis at global level was developed by CIMNE and INGENIAR Ltda. This hazard model is a continuation and improvement of the one developed in the framework of GAR13 where a set of tectonic provinces were identified and characterized by means of a set of parameters that describe the future seismic activity on each of them based on historical records together with relationships to obtain hazard intensities as a function of magnitude and distance. The hazard analysis was performed using the program CRISIS2014, a state-of-the-art tool for these kinds of tasks and widely known and acknowledged by experts in the field across the world. The chosen hazard intensity measure for this case was spectral acceleration and to guarantee a good connection between the hazard and the exposure characteristics, results for several ordinates beteween 0.0 and 2.3 seconds were computed. More details about the probabilistic seismic hazard analysis can be found in Cardona et al. (2015). -180.0 -90.0 180.0 90.0 wesr_risk:pga_975_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Short Vegetation Change 1982 - 2016 This analysis of 35 years’ worth of satellite data (at approximately 25 square kilometer resolution at the equator) provides a comprehensive record of global land-change dynamics during the period 1982–2016. Contrary to the prevailing view that forest area has declined globally — tree cover has increased by 2.24 million km2 (+7.1% relative to the 1982 level), largely the result of a net loss in the tropics being outweighed by a net gain in the extratropics. Global bare ground cover has decreased by 1.16 million km2 (−3.1%), most notably in agricultural regions in Asia. Of all land changes, 60% are associated with direct human activities and 40% with indirect drivers such as climate change. Land-use change exhibits regional dominance, including tropical deforestation and agricultural expansion, temperate reforestation or afforestation, cropland intensification and urbanization. Consistently across all climate domains, montane systems have gained tree cover and many arid and semi-arid ecosystems have lost vegetation cover.<br><br>For full details see: <a href="https://doi.org/10.1038/s41586-018-0411-9">Song, X.-P., Hansen, M.C., Stehman, S.V., Potapov, P.V., Tyukavina, A., Vermote, E.F., Townshend, J.R., 2018. Global land change from 1982 to 2016. Nature 1</a><br/>. -180.0 -90.0 180.0 90.0 MapX_UNDP:Short_vegetation_change_1982-2016 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Digital elevation model at 90m resolution This digitial elevation model (DEM) is derived from CGIAR-CSI SRTM v4.1 and ASTER GDEM v2 data products, and has been processed and mergedm inculding void-filling and smoothing of irregularities, to provide continuous coverage of ~91% of the globe.<br><br>For full processing and merging methodology see: <a href="https://www.sciencedirect.com/science/article/abs/pii/S0924271613002360"target="_blank">Robinson et al. (2014)</a>.<br/><br>Data can also be downloaded from <a href="http://www.earthenv.org/DEM"target="_blank">EarthEnv</a>.<br/><br>This data available under a <a href="https://creativecommons.org/licenses/by/4.0/"target="_blank">Creative Commons Attribution 4.0 International License</a> and is provided without any warranty of any kind whatsoever, either express or implied, including warranties of merchantability and fitness for a particular purpose. The creators of the product shall not be liable for incidental, consequential, or special damages arising out of the use of any data.<br/> -179.99999999999966 -59.999999999948244 179.99999999986994 82.99999999999997 MapX_UNDP:dem90 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 3 45 0 63 EPSG:3857:7 7 90 0 127 EPSG:3857:8 14 181 0 255 EPSG:3857:9 28 363 0 511 EPSG:3857:10 56 726 0 1023 EPSG:3857:11 113 1453 0 2047 EPSG:3857:12 226 2906 0 4095 EPSG:3857:13 452 5813 0 8191 EPSG:3857:14 905 11626 0 16383 EPSG:3857:15 1811 23252 0 32767 EPSG:3857:16 3623 46504 0 65535 EPSG:3857:17 7246 93008 0 131071 EPSG:3857:18 14492 186017 0 262143 EPSG:3857:19 28985 372034 0 524287 EPSG:3857:20 57971 744069 0 1048575 EPSG:3857:21 115943 1488139 0 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EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 3 45 0 63 EPSG:3857:7 7 90 0 127 EPSG:3857:8 14 181 0 255 EPSG:3857:9 28 363 0 511 EPSG:3857:10 56 726 0 1023 EPSG:3857:11 113 1453 0 2047 EPSG:3857:12 226 2906 0 4095 EPSG:3857:13 452 5813 0 8191 EPSG:3857:14 905 11626 0 16383 EPSG:3857:15 1811 23252 0 32767 EPSG:3857:16 3623 46504 0 65535 EPSG:3857:17 7246 93008 0 131071 EPSG:3857:18 14492 186017 0 262143 EPSG:3857:19 28985 372034 0 524287 EPSG:3857:20 57971 744069 0 1048575 EPSG:3857:21 115943 1488139 0 2097152 EPSG:3857:22 231887 2976279 0 4194304 EPSG:3857:23 463774 5952559 0 8388607 EPSG:3857:24 927548 11905118 0 16777215 EPSG:3857:25 1855097 23810236 0 33554431 EPSG:3857:26 3710195 47620473 0 67108863 EPSG:3857:27 7420391 95240947 0 134217728 EPSG:3857:28 14840782 190481895 0 268435455 EPSG:3857:29 29681565 380963791 0 536870911 EPSG:3857:30 59363131 761927583 0 1073741824 Travel_time_final_Guinee2_opt -15.12552847903117 7.153551977476363 -7.622479365710555 12.71750787814737 AccessMod:Travel_time_final_Guinee2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 15 14 15 EPSG:3857:6 29 30 29 30 EPSG:3857:7 59 61 58 61 EPSG:3857:8 118 122 117 122 EPSG:3857:9 237 245 234 245 EPSG:3857:10 475 491 468 490 EPSG:3857:11 951 983 937 980 EPSG:3857:12 1902 1966 1875 1961 EPSG:3857:13 3804 3932 3751 3922 EPSG:3857:14 7608 7865 7503 7845 EPSG:3857:15 15216 15731 15007 15690 EPSG:3857:16 30433 31462 30014 31380 EPSG:3857:17 60867 62924 60028 62760 EPSG:3857:18 121734 125849 120057 125521 EPSG:3857:19 243468 251698 240115 251042 EPSG:3857:20 486937 503397 480231 502085 EPSG:3857:21 973875 1006794 960463 1004171 EPSG:3857:22 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31164006 32217435 30734829 32133498 EPSG:3857:27 62328013 64434870 61469658 64266997 EPSG:3857:28 124656027 128869740 122939316 128533995 EPSG:3857:29 249312055 257739481 245878633 257067990 EPSG:3857:30 498624111 515478962 491757266 514135981 Forest Integrity Index (Montana State University) The forest integrrity index is derived by overlaying the human footprint (Venter et al. 2016) on the forest structural condition. The name is consistent with the concept of ecological integrity. Ecological integrity has been defined as, “the system’s capacity to maintain structure and ecosystem functions using processes and elements characteristic for its ecoregion.” (Parks Canada 2008). This capacity is a result of the climate, soil, topography, biota and other biophysical properties of the ecoregion and the extent to which these properties are not altered by modern human pressures. Consistent with this definition, the forest integrity index is based on on the structural complexity of a stand relative to the natural potential of the ecoregion and level of human pressure. Thus, forest of high integrity are relatively tall, high in canopy cover, older, and with relatively low human pressure. An increasing number of studies have shown that human pressure in various forms can have negative effects on native species. Thus, high integrity forests may be uniquely important for conservation because they support species and processes that are require well-developed forests and are sensitive to human activities. Such forests often also have high economic value and have likely been preferentially converted to more intense human land uses. Thus, identifying remaining areas of high forest integrity is important for conservation planning.<br><br>Data is provided by Montana State University.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> -81.007003784197 -9.999861112471002 141.016129418236 23.384477504501 wesr_biodiversity:forint100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 16 8 28 EPSG:3857:6 27 33 17 57 EPSG:3857:7 55 67 35 114 EPSG:3857:8 110 135 70 228 EPSG:3857:9 221 270 140 456 EPSG:3857:10 443 540 281 913 EPSG:3857:11 887 1081 563 1826 EPSG:3857:12 1774 2162 1126 3652 EPSG:3857:13 3548 4324 2252 7304 EPSG:3857:14 7096 8649 4505 14609 EPSG:3857:15 14193 17298 9010 29219 EPSG:3857:16 28387 34597 18021 58439 EPSG:3857:17 56775 69195 36042 116878 EPSG:3857:18 113550 138390 72084 233756 EPSG:3857:19 227101 276781 144168 467513 EPSG:3857:20 454202 553563 288337 935027 EPSG:3857:21 908404 1107127 576675 1870054 EPSG:3857:22 1816808 2214254 1153351 3740108 EPSG:3857:23 3633616 4428509 2306703 7480217 EPSG:3857:24 7267232 8857019 4613407 14960435 EPSG:3857:25 14534465 17714038 9226815 29920871 EPSG:3857:26 29068930 35428077 18453631 59841743 EPSG:3857:27 58137860 70856155 36907263 119683487 EPSG:3857:28 116275721 141712310 73814527 239366975 EPSG:3857:29 232551442 283424621 147629055 478733950 EPSG:3857:30 465102885 566849242 295258111 957467900 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 8 8 28 EPSG:4326:5 11 17 17 57 EPSG:4326:6 23 35 35 114 EPSG:4326:7 47 71 70 228 EPSG:4326:8 94 142 140 456 EPSG:4326:9 189 284 281 913 EPSG:4326:10 378 568 563 1826 EPSG:4326:11 757 1137 1126 3652 EPSG:4326:12 1515 2275 2252 7304 EPSG:4326:13 3031 4551 4505 14609 EPSG:4326:14 6063 9102 9010 29219 EPSG:4326:15 12126 18204 18021 58439 EPSG:4326:16 24253 36408 36042 116878 EPSG:4326:17 48507 72817 72084 233756 EPSG:4326:18 97015 145635 144168 467513 EPSG:4326:19 194031 291270 288337 935027 EPSG:4326:20 388063 582541 576675 1870054 EPSG:4326:21 776127 1165082 1153351 3740108 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 16 8 28 EPSG:3857:6 27 33 17 57 EPSG:3857:7 55 67 35 114 EPSG:3857:8 110 135 70 228 EPSG:3857:9 221 270 140 456 EPSG:3857:10 443 540 281 913 EPSG:3857:11 887 1081 563 1826 EPSG:3857:12 1774 2162 1126 3652 EPSG:3857:13 3548 4324 2252 7304 EPSG:3857:14 7096 8649 4505 14609 EPSG:3857:15 14193 17298 9010 29219 EPSG:3857:16 28387 34597 18021 58439 EPSG:3857:17 56775 69195 36042 116878 EPSG:3857:18 113550 138390 72084 233756 EPSG:3857:19 227101 276781 144168 467513 EPSG:3857:20 454202 553563 288337 935027 EPSG:3857:21 908404 1107127 576675 1870054 EPSG:3857:22 1816808 2214254 1153351 3740108 EPSG:3857:23 3633616 4428509 2306703 7480217 EPSG:3857:24 7267232 8857019 4613407 14960435 EPSG:3857:25 14534465 17714038 9226815 29920871 EPSG:3857:26 29068930 35428077 18453631 59841743 EPSG:3857:27 58137860 70856155 36907263 119683487 EPSG:3857:28 116275721 141712310 73814527 239366975 EPSG:3857:29 232551442 283424621 147629055 478733950 EPSG:3857:30 465102885 566849242 295258111 957467900 Asia Forest Height (Montana State University) The forest structural condition index is derived from the University of Maryland canopy cover, canopy height, and time since forest loss data sets. The index spans from short, open-canopy, recently disturbed forests to tall, closed canopy forests that have not been disturbed with the last 14 years. Forest stature and canopy cover are products of both the biophysical potential of a local site and of disturbance history. The tallest, most dense forests are found in settings with favorable climate and soils but with low levels if natural or human disturbance. Such forests have been shown to support high levels of biodiversity, store high levels of carbon, and be more resilient to climate variability. Our maps of forest structural condition are the first to identify locations in the humid tropics of tall, dense forests resulting from high biophysical potential and low disturbance rates. Data are provided by the Montana State University for South America, Africa and Asia separately, and have been merged into a single dataset here. License information: CC-4.0 Attribution. 60.9995 -32.0005 180.0 32.0005 MapX_UNDP:asia_forheight image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 3 EPSG:3857:3 3 4 5 7 EPSG:3857:4 6 9 10 15 EPSG:3857:5 12 19 21 31 EPSG:3857:6 25 38 42 63 EPSG:3857:7 51 76 85 127 EPSG:3857:8 103 152 171 255 EPSG:3857:9 207 304 342 511 EPSG:3857:10 415 608 685 1023 EPSG:3857:11 831 1216 1371 2047 EPSG:3857:12 1663 2432 2742 4095 EPSG:3857:13 3326 4865 5484 8191 EPSG:3857:14 6653 9730 10968 16383 EPSG:3857:15 13306 19461 21936 32767 EPSG:3857:16 26613 38922 43872 65535 EPSG:3857:17 53227 77844 87745 131071 EPSG:3857:18 106454 155689 175490 262143 EPSG:3857:19 212909 311378 350980 524287 EPSG:3857:20 425818 622757 701961 1048575 EPSG:3857:21 851636 1245515 1403923 2097151 EPSG:3857:22 1703272 2491031 2807847 4194304 EPSG:3857:23 3406544 4982063 5615695 8388608 EPSG:3857:24 6813088 9964127 11231390 16777215 EPSG:3857:25 13626176 19928255 22462781 33554431 EPSG:3857:26 27252353 39856510 44925562 67108863 EPSG:3857:27 54504706 79713021 89851125 134217727 EPSG:3857:28 109009413 159426042 179702251 268435456 EPSG:3857:29 218018827 318852084 359404503 536870911 EPSG:3857:30 436037654 637704169 718809007 1073741823 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 3 EPSG:4326:2 1 2 5 7 EPSG:4326:3 2 5 10 15 EPSG:4326:4 5 10 21 31 EPSG:4326:5 10 21 42 63 EPSG:4326:6 20 43 85 127 EPSG:4326:7 41 86 171 255 EPSG:4326:8 82 173 342 511 EPSG:4326:9 164 347 685 1023 EPSG:4326:10 329 694 1371 2047 EPSG:4326:11 659 1388 2742 4095 EPSG:4326:12 1319 2776 5484 8191 EPSG:4326:13 2639 5552 10968 16383 EPSG:4326:14 5279 11104 21936 32767 EPSG:4326:15 10558 22209 43872 65535 EPSG:4326:16 21116 44419 87745 131071 EPSG:4326:17 42233 88838 175490 262143 EPSG:4326:18 84467 177676 350980 524287 EPSG:4326:19 168935 355352 701961 1048575 EPSG:4326:20 337871 710704 1403923 2097151 EPSG:4326:21 675743 1421408 2807847 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 1 1 EPSG:900913:2 1 2 2 3 EPSG:900913:3 3 4 5 7 EPSG:900913:4 6 9 10 15 EPSG:900913:5 12 19 21 31 EPSG:900913:6 25 38 42 63 EPSG:900913:7 51 76 85 127 EPSG:900913:8 103 152 171 255 EPSG:900913:9 207 304 342 511 EPSG:900913:10 415 608 685 1023 EPSG:900913:11 831 1216 1371 2047 EPSG:900913:12 1663 2432 2742 4095 EPSG:900913:13 3326 4865 5484 8191 EPSG:900913:14 6653 9730 10968 16383 EPSG:900913:15 13306 19461 21936 32767 EPSG:900913:16 26613 38922 43872 65535 EPSG:900913:17 53227 77844 87745 131071 EPSG:900913:18 106454 155689 175490 262143 EPSG:900913:19 212909 311378 350980 524287 EPSG:900913:20 425818 622757 701961 1048575 EPSG:900913:21 851636 1245515 1403923 2097151 EPSG:900913:22 1703272 2491031 2807847 4194303 EPSG:900913:23 3406544 4982063 5615695 8388607 EPSG:900913:24 6813088 9964127 11231390 16777215 EPSG:900913:25 13626176 19928255 22462781 33554431 EPSG:900913:26 27252353 39856510 44925562 67108863 EPSG:900913:27 54504706 79713021 89851125 134217727 EPSG:900913:28 109009413 159426042 179702251 268435455 EPSG:900913:29 218018827 318852084 359404503 536870911 EPSG:900913:30 436037654 637704169 718809007 1073741823 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 3 EPSG:3857:3 3 4 5 7 EPSG:3857:4 6 9 10 15 EPSG:3857:5 12 19 21 31 EPSG:3857:6 25 38 42 63 EPSG:3857:7 51 76 85 127 EPSG:3857:8 103 152 171 255 EPSG:3857:9 207 304 342 511 EPSG:3857:10 415 608 685 1023 EPSG:3857:11 831 1216 1371 2047 EPSG:3857:12 1663 2432 2742 4095 EPSG:3857:13 3326 4865 5484 8191 EPSG:3857:14 6653 9730 10968 16383 EPSG:3857:15 13306 19461 21936 32767 EPSG:3857:16 26613 38922 43872 65535 EPSG:3857:17 53227 77844 87745 131071 EPSG:3857:18 106454 155689 175490 262143 EPSG:3857:19 212909 311378 350980 524287 EPSG:3857:20 425818 622757 701961 1048575 EPSG:3857:21 851636 1245515 1403923 2097152 EPSG:3857:22 1703272 2491031 2807847 4194304 EPSG:3857:23 3406544 4982063 5615695 8388607 EPSG:3857:24 6813088 9964127 11231390 16777215 EPSG:3857:25 13626176 19928255 22462781 33554431 EPSG:3857:26 27252353 39856510 44925562 67108863 EPSG:3857:27 54504706 79713021 89851125 134217728 EPSG:3857:28 109009413 159426042 179702251 268435455 EPSG:3857:29 218018827 318852084 359404503 536870911 EPSG:3857:30 436037654 637704169 718809007 1073741824 Global Soil Organic Carbon Map V1.0 Soil organic carbon (SOC) is the carbon that remains in the soil after partial decomposition of any material produced by living organisms. It constitutes a key element of the global carbon cycle through atmosphere, vegetation, soil, rivers and the ocean. The Global Soil Organic Carbon Map (GSOCmap) allows the estimation of SOC stock from 0 to 30 cm. It represents a key contribution to SDG indicator 15.3.1 which defines the area of degraded land. The GSOCmap represents the first ever global soil organic carbon assessment produced through a participatory approach in which countries developed their capacities and stepped up efforts to compile all the available soil information at national level. Values are in tonnes per hectare. Source: Food and Agricultural Organization of The United Nations (FAO) Data Source: http://www.fao.org/global-soil-partnership/pillars-action/4-information-and-data/global-soil-organic-carbon-gsoc-map/en/ -180.0 -70.91725146799998 180.0 83.616081247 MapX_UNDP:GSOCmapV1 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 12 0 15 EPSG:3857:5 1 25 0 31 EPSG:3857:6 2 50 0 63 EPSG:3857:7 5 100 0 127 EPSG:3857:8 10 200 0 255 EPSG:3857:9 20 401 0 511 EPSG:3857:10 41 802 0 1023 EPSG:3857:11 83 1605 0 2047 EPSG:3857:12 166 3210 0 4095 EPSG:3857:13 332 6421 0 8191 EPSG:3857:14 665 12842 0 16383 EPSG:3857:15 1330 25684 0 32767 EPSG:3857:16 2660 51368 0 65535 EPSG:3857:17 5320 102736 0 131071 EPSG:3857:18 10640 205473 0 262143 EPSG:3857:19 21280 410946 0 524287 EPSG:3857:20 42561 821893 0 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EPSG:4326:21 74378 1874821 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 12 0 15 EPSG:900913:5 1 25 0 31 EPSG:900913:6 2 50 0 63 EPSG:900913:7 5 100 0 127 EPSG:900913:8 10 200 0 255 EPSG:900913:9 20 401 0 511 EPSG:900913:10 41 802 0 1023 EPSG:900913:11 83 1605 0 2047 EPSG:900913:12 166 3210 0 4095 EPSG:900913:13 332 6421 0 8191 EPSG:900913:14 665 12842 0 16383 EPSG:900913:15 1330 25684 0 32767 EPSG:900913:16 2660 51368 0 65535 EPSG:900913:17 5320 102736 0 131071 EPSG:900913:18 10640 205473 0 262143 EPSG:900913:19 21280 410946 0 524287 EPSG:900913:20 42561 821893 0 1048575 EPSG:900913:21 85123 1643786 0 2097151 EPSG:900913:22 170247 3287573 0 4194303 EPSG:900913:23 340495 6575147 0 8388607 EPSG:900913:24 680991 13150295 0 16777215 EPSG:900913:25 1361982 26300590 0 33554431 EPSG:900913:26 2723964 52601180 0 67108863 EPSG:900913:27 5447928 105202360 0 134217727 EPSG:900913:28 10895856 210404720 0 268435455 EPSG:900913:29 21791713 420809440 0 536870911 EPSG:900913:30 43583426 841618880 0 1073741823 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 12 0 15 EPSG:3857:5 1 25 0 31 EPSG:3857:6 2 50 0 63 EPSG:3857:7 5 100 0 127 EPSG:3857:8 10 200 0 255 EPSG:3857:9 20 401 0 511 EPSG:3857:10 41 802 0 1023 EPSG:3857:11 83 1605 0 2047 EPSG:3857:12 166 3210 0 4095 EPSG:3857:13 332 6421 0 8191 EPSG:3857:14 665 12842 0 16383 EPSG:3857:15 1330 25684 0 32767 EPSG:3857:16 2660 51368 0 65535 EPSG:3857:17 5320 102736 0 131071 EPSG:3857:18 10640 205473 0 262143 EPSG:3857:19 21280 410946 0 524287 EPSG:3857:20 42561 821893 0 1048575 EPSG:3857:21 85123 1643786 0 2097152 EPSG:3857:22 170247 3287573 0 4194304 EPSG:3857:23 340495 6575147 0 8388607 EPSG:3857:24 680991 13150295 0 16777215 EPSG:3857:25 1361982 26300590 0 33554431 EPSG:3857:26 2723964 52601180 0 67108863 EPSG:3857:27 5447928 105202360 0 134217728 EPSG:3857:28 10895856 210404720 0 268435455 EPSG:3857:29 21791713 420809440 0 536870911 EPSG:3857:30 43583426 841618880 0 1073741824 tza_wb_buffer 29.42290987105417 -12.249352377620772 40.54185706243741 0.418418794759549 mapx_chemobs:tza_wb_buffer image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 9 9 EPSG:3857:5 15 17 18 19 EPSG:3857:6 31 34 37 39 EPSG:3857:7 63 68 74 78 EPSG:3857:8 127 136 148 156 EPSG:3857:9 255 273 297 313 EPSG:3857:10 510 547 595 627 EPSG:3857:11 1021 1094 1191 1254 EPSG:3857:12 2043 2188 2382 2509 EPSG:3857:13 4086 4376 4765 5018 EPSG:3857:14 8172 8753 9531 10037 EPSG:3857:15 16345 17507 19062 20074 EPSG:3857:16 32691 35015 38124 40148 EPSG:3857:17 65383 70030 76248 80296 EPSG:3857:18 130767 140060 152497 160593 EPSG:3857:19 261534 280120 304994 321187 EPSG:3857:20 523069 560241 609988 642374 EPSG:3857:21 1046138 1120483 1219976 1284749 EPSG:3857:22 2092277 2240967 2439953 2569498 EPSG:3857:23 4184554 4481934 4879907 5138997 EPSG:3857:24 8369108 8963868 9759814 10277995 EPSG:3857:25 16738216 17927736 19519629 20555990 EPSG:3857:26 33476432 35855473 39039259 41111981 EPSG:3857:27 66952864 71710946 78078519 82223963 EPSG:3857:28 133905729 143421892 156157039 164447927 EPSG:3857:29 267811459 286843784 312314079 328895855 EPSG:3857:30 535622918 573687568 624628158 657791710 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 9 9 EPSG:4326:4 7 9 18 19 EPSG:4326:5 15 18 37 39 EPSG:4326:6 31 36 74 78 EPSG:4326:7 63 72 148 156 EPSG:4326:8 127 145 297 313 EPSG:4326:9 254 290 595 627 EPSG:4326:10 509 581 1191 1254 EPSG:4326:11 1019 1163 2382 2509 EPSG:4326:12 2038 2326 4765 5018 EPSG:4326:13 4076 4653 9531 10037 EPSG:4326:14 8153 9306 19062 20074 EPSG:4326:15 16307 18613 38124 40148 EPSG:4326:16 32615 37227 76248 80296 EPSG:4326:17 65231 74455 152497 160593 EPSG:4326:18 130462 148911 304994 321187 EPSG:4326:19 260925 297822 609988 642374 EPSG:4326:20 521850 595645 1219976 1284749 EPSG:4326:21 1043701 1191291 2439953 2569498 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 9 9 EPSG:3857:5 15 17 18 19 EPSG:3857:6 31 34 37 39 EPSG:3857:7 63 68 74 78 EPSG:3857:8 127 136 148 156 EPSG:3857:9 255 273 297 313 EPSG:3857:10 510 547 595 627 EPSG:3857:11 1021 1094 1191 1254 EPSG:3857:12 2043 2188 2382 2509 EPSG:3857:13 4086 4376 4765 5018 EPSG:3857:14 8172 8753 9531 10037 EPSG:3857:15 16345 17507 19062 20074 EPSG:3857:16 32691 35015 38124 40148 EPSG:3857:17 65383 70030 76248 80296 EPSG:3857:18 130767 140060 152497 160593 EPSG:3857:19 261534 280120 304994 321187 EPSG:3857:20 523069 560241 609988 642374 EPSG:3857:21 1046138 1120483 1219976 1284749 EPSG:3857:22 2092277 2240967 2439953 2569498 EPSG:3857:23 4184554 4481934 4879907 5138997 EPSG:3857:24 8369108 8963868 9759814 10277995 EPSG:3857:25 16738216 17927736 19519629 20555990 EPSG:3857:26 33476432 35855473 39039259 41111981 EPSG:3857:27 66952864 71710946 78078519 82223963 EPSG:3857:28 133905729 143421892 156157039 164447927 EPSG:3857:29 267811459 286843784 312314079 328895855 EPSG:3857:30 535622918 573687568 624628158 657791710 Summer temperature change (°C) for the period 2080 - 2099 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_jja_ENDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 20130401_originals 7.1100148908217635 44.996576646230245 10.103215000055275 47.04180362738302 hotspots:20130401_originals image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 2 4 4 EPSG:3857:4 5 5 8 8 EPSG:3857:5 11 11 16 16 EPSG:3857:6 22 23 33 33 EPSG:3857:7 44 46 66 67 EPSG:3857:8 89 92 133 135 EPSG:3857:9 179 184 266 270 EPSG:3857:10 359 368 532 540 EPSG:3857:11 719 736 1064 1081 EPSG:3857:12 1439 1473 2128 2162 EPSG:3857:13 2879 2946 4257 4325 EPSG:3857:14 5759 5893 8515 8651 EPSG:3857:15 11519 11787 17031 17303 EPSG:3857:16 23039 23575 34062 34607 EPSG:3857:17 46079 47151 68124 69214 EPSG:3857:18 92158 94303 136249 138428 EPSG:3857:19 184316 188606 272498 276857 EPSG:3857:20 368633 377213 544997 553715 EPSG:3857:21 737266 754426 1089994 1107431 EPSG:3857:22 1474532 1508852 2179989 2214862 EPSG:3857:23 2949064 3017705 4359979 4429725 EPSG:3857:24 5898129 6035410 8719958 8859451 EPSG:3857:25 11796258 12070820 17439917 17718903 EPSG:3857:26 23592516 24141641 34879834 35437807 EPSG:3857:27 47185032 48283282 69759669 70875615 EPSG:3857:28 94370065 96566564 139519339 141751231 EPSG:3857:29 188740131 193133128 279038678 283502462 EPSG:3857:30 377480263 386266256 558077357 567004924 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 0 1 4 4 EPSG:4326:3 1 2 8 8 EPSG:4326:4 3 4 16 16 EPSG:4326:5 7 8 33 33 EPSG:4326:6 15 16 66 67 EPSG:4326:7 30 32 133 135 EPSG:4326:8 61 64 266 270 EPSG:4326:9 122 128 532 540 EPSG:4326:10 244 256 1064 1081 EPSG:4326:11 488 512 2128 2162 EPSG:4326:12 977 1024 4257 4325 EPSG:4326:13 1955 2048 8515 8651 EPSG:4326:14 3910 4096 17031 17303 EPSG:4326:15 7820 8192 34062 34607 EPSG:4326:16 15640 16385 68124 69214 EPSG:4326:17 31281 32770 136249 138428 EPSG:4326:18 62562 65540 272498 276857 EPSG:4326:19 125124 131081 544997 553715 EPSG:4326:20 250249 262163 1089994 1107431 EPSG:4326:21 500499 524327 2179989 2214862 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 2 4 4 EPSG:3857:4 5 5 8 8 EPSG:3857:5 11 11 16 16 EPSG:3857:6 22 23 33 33 EPSG:3857:7 44 46 66 67 EPSG:3857:8 89 92 133 135 EPSG:3857:9 179 184 266 270 EPSG:3857:10 359 368 532 540 EPSG:3857:11 719 736 1064 1081 EPSG:3857:12 1439 1473 2128 2162 EPSG:3857:13 2879 2946 4257 4325 EPSG:3857:14 5759 5893 8515 8651 EPSG:3857:15 11519 11787 17031 17303 EPSG:3857:16 23039 23575 34062 34607 EPSG:3857:17 46079 47151 68124 69214 EPSG:3857:18 92158 94303 136249 138428 EPSG:3857:19 184316 188606 272498 276857 EPSG:3857:20 368633 377213 544997 553715 EPSG:3857:21 737266 754426 1089994 1107431 EPSG:3857:22 1474532 1508852 2179989 2214862 EPSG:3857:23 2949064 3017705 4359979 4429725 EPSG:3857:24 5898129 6035410 8719958 8859451 EPSG:3857:25 11796258 12070820 17439917 17718903 EPSG:3857:26 23592516 24141641 34879834 35437807 EPSG:3857:27 47185032 48283282 69759669 70875615 EPSG:3857:28 94370065 96566564 139519339 141751231 EPSG:3857:29 188740131 193133128 279038678 283502462 EPSG:3857:30 377480263 386266256 558077357 567004924 Automn temperature change (°C) for the period 2040 - 2059 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_son_MIDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Global Terrestrial Human Footprint (HFP) - 2005 (subset) This update to the Human Footprint (HFP) provides a measure of the direct and indirect human pressures on the environment globally in years 2000, 2005, 2010, and 2013. Per the orinal Human Footprint, this dataset is derived from remotely-sensed and bottom-up survey information compiled on eight measured variables. This represents not only the most current information of its type, but also the first temporally-consistent set of Human Footprint maps. Data on human pressures were acquired or developed for: 1) built environments, 2) population density, 3) electric infrastructure, 4) crop lands, 5) pasture lands, 6) roads, 7) railways, and 8) navigable waterways. This update incorporates updated and higher resolution population, nightlights, pasture, road, and railway input datasets. The Human Footprint maps find a range of uses as proxies for human disturbance of natural systems and can provide an increased understanding of the human pressures that drive macro-ecological patterns, as well as for tracking environmental change and informing conservation science and application. HFP values range from 0 (no human impact) to 50 (heavily human impacted).<br><br>See: <a href="https://www.nature.com/articles/ncomms12558" target="_blank">Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11</a>.<br/><br>This dataset can be downloaded uniquly from UN Biodiversity Lab. <br> Updated data is made available only to FIP pilot countires at present - rasters are clipped to other FIP data extents. -81.71613729134685 -20.618092964606667 153.42326553667291 26.043388408099844 MapX_UNDP:hfp2005_merisINT_subsetsGlobal image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27854 36605 17892 60697 EPSG:3857:17 55709 73210 35784 121395 EPSG:3857:18 111418 146420 71568 242791 EPSG:3857:19 222837 292841 143136 485582 EPSG:3857:20 445675 585682 286272 971165 EPSG:3857:21 891350 1171364 572544 1942331 EPSG:3857:22 1782701 2342729 1145089 3884662 EPSG:3857:23 3565403 4685458 2290179 7769325 EPSG:3857:24 7130806 9370916 4580359 15538650 EPSG:3857:25 14261613 18741832 9160719 31077300 EPSG:3857:26 28523227 37483665 18321439 62154601 EPSG:3857:27 57046454 74967331 36642879 124309203 EPSG:3857:28 114092909 149934663 73285759 248618406 EPSG:3857:29 228185818 299869326 146571519 497236812 EPSG:3857:30 456371636 599738652 293143038 994473625 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 90 157 139 474 EPSG:4326:9 181 314 279 948 EPSG:4326:10 363 629 559 1896 EPSG:4326:11 727 1258 1118 3793 EPSG:4326:12 1455 2517 2236 7587 EPSG:4326:13 2910 5034 4473 15174 EPSG:4326:14 5821 10068 8946 30348 EPSG:4326:15 11642 20137 17892 60697 EPSG:4326:16 23285 40274 35784 121395 EPSG:4326:17 46571 80549 71568 242791 EPSG:4326:18 93143 161099 143136 485582 EPSG:4326:19 186287 322198 286272 971165 EPSG:4326:20 372574 644397 572544 1942331 EPSG:4326:21 745148 1288794 1145089 3884662 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27854 36605 17892 60697 EPSG:3857:17 55709 73210 35784 121395 EPSG:3857:18 111418 146420 71568 242791 EPSG:3857:19 222837 292841 143136 485582 EPSG:3857:20 445675 585682 286272 971165 EPSG:3857:21 891350 1171364 572544 1942331 EPSG:3857:22 1782701 2342729 1145089 3884662 EPSG:3857:23 3565403 4685458 2290179 7769325 EPSG:3857:24 7130806 9370916 4580359 15538650 EPSG:3857:25 14261613 18741832 9160719 31077300 EPSG:3857:26 28523227 37483665 18321439 62154601 EPSG:3857:27 57046454 74967331 36642879 124309203 EPSG:3857:28 114092909 149934663 73285759 248618406 EPSG:3857:29 228185818 299869326 146571519 497236812 EPSG:3857:30 456371636 599738652 293143038 994473625 World Roads - Esri -159.789321899414 -34.6280746459961 180.0 70.44384765625 grid_data_core:roads_esri image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 2 0 7 EPSG:4326:3 0 5 0 15 EPSG:4326:4 1 11 1 31 EPSG:4326:5 3 22 3 63 EPSG:4326:6 6 44 7 127 EPSG:4326:7 13 88 14 255 EPSG:4326:8 27 177 28 511 EPSG:4326:9 55 354 57 1023 EPSG:4326:10 111 708 114 2047 EPSG:4326:11 222 1417 229 4095 EPSG:4326:12 445 2835 459 8191 EPSG:4326:13 890 5671 919 16383 EPSG:4326:14 1780 11343 1839 32767 EPSG:4326:15 3560 22687 3679 65535 EPSG:4326:16 7120 45375 7358 131071 EPSG:4326:17 14240 90751 14716 262143 EPSG:4326:18 28480 181502 29433 524287 EPSG:4326:19 56961 363005 58867 1048575 EPSG:4326:20 113922 726011 117735 2097151 EPSG:4326:21 227845 1452022 235471 4194303 EPSG:900913 Kerala Flood 10 Years RP - Historical Kerala State flood hazard map - Historical. Maximum expected flood event water height in a 10 years return period, expressed in cm. 74.85875 8.25375 77.49291666666667 12.842916666666673 ECO-DRR:Kerala_Flood_10_Yrs_Historical image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185582 187500 EPSG:4326:18 112368 119051 371164 375001 EPSG:4326:19 224736 238103 742329 750002 EPSG:4326:20 449472 476206 1484659 1500004 EPSG:4326:21 898945 952412 2969319 3000009 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 Self-calibrating Palmer Drought Severity Index (scPDSI) 1960-1969 (CRU) This layer shows the average values over the 1960 to 1969 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901 to 2018. Original data were subset and processed using QGIS at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> The dataset has been updated each year using newer versions of CRU TS input data, currently to the end of 2018 using a preliminary version of CRU TS 4.03 (0.5° resolution). <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 UN_Sahel:scPDSI.cru_ts403_1960-1969 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 International boundaries Level 2 subdivision - GADM 3.6 Source: https://gadm.org/data.html -179.99999999999994 -90.0 180.0 83.65833282470703 MAPX_nd:gadm36_2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 40 1023 0 1023 EPSG:3857:11 80 2047 0 2047 EPSG:3857:12 161 4095 0 4095 EPSG:3857:13 323 8191 0 8191 EPSG:3857:14 647 16383 0 16383 EPSG:3857:15 1295 32767 0 32767 EPSG:3857:16 2590 65535 0 65535 EPSG:3857:17 5181 131071 0 131071 EPSG:3857:18 10362 262143 0 262143 EPSG:3857:19 20725 524287 0 524287 EPSG:3857:20 41451 1048575 0 1048575 EPSG:3857:21 82902 2097151 0 2097151 EPSG:3857:22 165805 4194303 0 4194304 EPSG:3857:23 331611 8388607 0 8388608 EPSG:3857:24 663223 16777215 0 16777215 EPSG:3857:25 1326446 33554431 0 33554431 EPSG:3857:26 2652893 67108863 0 67108863 EPSG:3857:27 5305787 134217727 0 134217727 EPSG:3857:28 10611574 268435455 0 268435456 EPSG:3857:29 21223148 536870911 0 536870911 EPSG:3857:30 42446297 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 9 255 0 511 EPSG:4326:9 18 511 0 1023 EPSG:4326:10 36 1023 0 2047 EPSG:4326:11 72 2047 0 4095 EPSG:4326:12 144 4095 0 8191 EPSG:4326:13 288 8191 0 16383 EPSG:4326:14 577 16383 0 32767 EPSG:4326:15 1154 32767 0 65535 EPSG:4326:16 2308 65535 0 131071 EPSG:4326:17 4617 131071 0 262143 EPSG:4326:18 9235 262143 0 524287 EPSG:4326:19 18471 524287 0 1048575 EPSG:4326:20 36942 1048575 0 2097151 EPSG:4326:21 73885 2097151 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 40 1023 0 1023 EPSG:3857:11 80 2047 0 2047 EPSG:3857:12 161 4095 0 4095 EPSG:3857:13 323 8191 0 8191 EPSG:3857:14 647 16383 0 16383 EPSG:3857:15 1295 32767 0 32767 EPSG:3857:16 2590 65535 0 65535 EPSG:3857:17 5181 131071 0 131071 EPSG:3857:18 10362 262143 0 262143 EPSG:3857:19 20725 524287 0 524287 EPSG:3857:20 41451 1048575 0 1048575 EPSG:3857:21 82902 2097151 0 2097152 EPSG:3857:22 165805 4194303 0 4194304 EPSG:3857:23 331611 8388607 0 8388607 EPSG:3857:24 663223 16777215 0 16777215 EPSG:3857:25 1326446 33554431 0 33554431 EPSG:3857:26 2652893 67108863 0 67108863 EPSG:3857:27 5305787 134217727 0 134217728 EPSG:3857:28 10611574 268435455 0 268435455 EPSG:3857:29 21223148 536870911 0 536870911 EPSG:3857:30 42446297 1073741823 0 1073741824 Central Congo Basin peatland map (2022, smoothed) Metadata for the file: Crezee_2022_Smoothed_7x7_Classification_Most_likely_class.tif This file is a simplified version of the map presented in Figure 1b of the paper: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This raster file is a smoothed version of the landcover classification map. For each pixel, the most likely class is displayed, based on the highest probability obtained from the 5 landcover classes presented in the Crezee_2022_Central_Congo_Peat_Probability_Layers.zip archive. The class values are: 0. No data 1. Open water 2. Savanna 3. Non-peat forming forest (Terra firme and seasonally inundated forest) 4. Palm-dominated peat swamp forest 5. Hardwood-dominated peat swamp forest Only class 4 and 5 are associated with the presence of peat. Total peatland area extent is obtained by summing class 4 and 5 areas. The speckle inherent in the classification was reduced through the use of a 7x7 majority filter, whereby the central pixel in a moving 7x7 window was replaced by the most common pixel type found in that window. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 15.0 -4.999916949999999 25.72744828 3.30533333 peatlands:Crezee_2022_Smoothed_7x7_Classification_Most_likely_class_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 8 17 18 EPSG:4326:5 15 16 34 36 EPSG:4326:6 30 33 69 73 EPSG:4326:7 61 67 138 146 EPSG:4326:8 123 135 277 292 EPSG:4326:9 246 270 554 585 EPSG:4326:10 493 540 1109 1170 EPSG:4326:11 986 1080 2218 2340 EPSG:4326:12 1972 2161 4437 4681 EPSG:4326:13 3945 4323 8874 9362 EPSG:4326:14 7891 8647 17749 18725 EPSG:4326:15 15782 17294 35498 37451 EPSG:4326:16 31564 34588 70997 74903 EPSG:4326:17 63129 69176 141994 149806 EPSG:4326:18 126258 138353 283989 299612 EPSG:4326:19 252516 276707 567978 599224 EPSG:4326:20 505033 553414 1135957 1198449 EPSG:4326:21 1010066 1106829 2271914 2396898 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 Spring temperature change (°C) for the period 2080 - 2099 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_mam_ENDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 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62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Kerala Global Land Cover 2009 ESA Global Land Cover 2009 for Kerala State. 74.85972222222227 8.254166666666677 77.49305555555561 12.843055555555566 ECO-DRR:Kerala_Global_Land_Cover_2009 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375001 EPSG:3857:20 486562 500162 742332 750002 EPSG:3857:21 973125 1000324 1484665 1500005 EPSG:3857:22 1946250 2000649 2969330 3000011 EPSG:3857:23 3892501 4001299 5938661 6000023 EPSG:3857:24 7785002 8002598 11877323 12000046 EPSG:3857:25 15570004 16005196 23754647 24000092 EPSG:3857:26 31140008 32010393 47509295 48000184 EPSG:3857:27 62280017 64020787 95018591 96000369 EPSG:3857:28 124560034 128041574 190037182 192000738 EPSG:3857:29 249120069 256083149 380074365 384001476 EPSG:3857:30 498240138 512166299 760148730 768002953 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 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EPSG:3857:21 973125 1000324 1484665 1500005 EPSG:3857:22 1946250 2000649 2969330 3000011 EPSG:3857:23 3892501 4001299 5938661 6000023 EPSG:3857:24 7785002 8002598 11877323 12000046 EPSG:3857:25 15570004 16005196 23754647 24000092 EPSG:3857:26 31140008 32010393 47509295 48000184 EPSG:3857:27 62280017 64020787 95018591 96000369 EPSG:3857:28 124560034 128041574 190037182 192000738 EPSG:3857:29 249120069 256083149 380074365 384001476 EPSG:3857:30 498240138 512166299 760148730 768002953 Combination Tropical cyclone surge/ Mangroves at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_man9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Annual Mean Temperature - Climatology (1979-2013) [°C/10] Mean annual daily mean air temperatures averaged over 1 year [°C/10]. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. 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127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 Tsunami hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:ts_phex_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 GLO_ecodrr -180.0 -60.35499999999999 180.0 84.43 ECO-DRR:GLO_ecodrr image/png image/vnd.jpeg-png image/jpeg image/png8 EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 45 0 63 EPSG:3857:7 2 91 0 127 EPSG:3857:8 4 182 0 255 EPSG:3857:9 9 364 0 511 EPSG:3857:10 19 728 0 1023 EPSG:3857:11 38 1457 0 2047 EPSG:3857:12 77 2914 0 4095 EPSG:3857:13 154 5829 0 8191 EPSG:3857:14 308 11658 0 16383 EPSG:3857:15 617 23317 0 32767 EPSG:3857:16 1234 46634 0 65535 EPSG:3857:17 2469 93268 0 131071 EPSG:3857:18 4939 186537 0 262143 EPSG:3857:19 9879 373074 0 524287 EPSG:3857:20 19759 746149 0 1048575 EPSG:3857:21 39519 1492298 0 2097151 EPSG:3857:22 79038 2984596 0 4194304 EPSG:3857:23 158076 5969192 0 8388608 EPSG:3857:24 316153 11938385 0 16777215 EPSG:3857:25 632306 23876771 0 33554431 EPSG:3857:26 1264612 47753543 0 67108863 EPSG:3857:27 2529224 95507087 0 134217727 EPSG:3857:28 5058449 191014175 0 268435456 EPSG:3857:29 10116899 382028350 0 536870911 EPSG:3857:30 20233798 764056700 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 1 53 0 127 EPSG:4326:7 3 106 0 255 EPSG:4326:8 7 213 0 511 EPSG:4326:9 15 427 0 1023 EPSG:4326:10 31 855 0 2047 EPSG:4326:11 63 1710 0 4095 EPSG:4326:12 126 3421 0 8191 EPSG:4326:13 253 6842 0 16383 EPSG:4326:14 506 13685 0 32767 EPSG:4326:15 1013 27371 0 65535 EPSG:4326:16 2027 54742 0 131071 EPSG:4326:17 4055 109485 0 262143 EPSG:4326:18 8111 218970 0 524287 EPSG:4326:19 16223 437940 0 1048575 EPSG:4326:20 32447 875881 0 2097151 EPSG:4326:21 64895 1751762 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 45 0 63 EPSG:3857:7 2 91 0 127 EPSG:3857:8 4 182 0 255 EPSG:3857:9 9 364 0 511 EPSG:3857:10 19 728 0 1023 EPSG:3857:11 38 1457 0 2047 EPSG:3857:12 77 2914 0 4095 EPSG:3857:13 154 5829 0 8191 EPSG:3857:14 308 11658 0 16383 EPSG:3857:15 617 23317 0 32767 EPSG:3857:16 1234 46634 0 65535 EPSG:3857:17 2469 93268 0 131071 EPSG:3857:18 4939 186537 0 262143 EPSG:3857:19 9879 373074 0 524287 EPSG:3857:20 19759 746149 0 1048575 EPSG:3857:21 39519 1492298 0 2097152 EPSG:3857:22 79038 2984596 0 4194304 EPSG:3857:23 158076 5969192 0 8388607 EPSG:3857:24 316153 11938385 0 16777215 EPSG:3857:25 632306 23876771 0 33554431 EPSG:3857:26 1264612 47753543 0 67108863 EPSG:3857:27 2529224 95507087 0 134217728 EPSG:3857:28 5058449 191014175 0 268435455 EPSG:3857:29 10116899 382028350 0 536870911 EPSG:3857:30 20233798 764056700 0 1073741824 Total built-up surface in 2030 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_2030 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Combination Tropical cyclone surge/ Mangroves at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_man6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 International Boundaries Coastalines Level 0 - UNmap UNmap is a global multi-scale geospatial dataset that is designed to serve as a base geodatabase for map production and web mapping to meet the needs of the United Nations Secretariat in supporting the work of the Security Council and field operations. It consists of basic geospatial information at different scales. -180.0 -86.4279861450195 180.0 84.3074951171875 grid_data_core_pro:ungiwg_cst_ln_01m image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 62 0 127 EPSG:4326:7 4 125 0 255 EPSG:4326:8 8 250 0 511 EPSG:4326:9 16 501 0 1023 EPSG:4326:10 32 1003 0 2047 EPSG:4326:11 64 2007 0 4095 EPSG:4326:12 129 4014 0 8191 EPSG:4326:13 259 8029 0 16383 EPSG:4326:14 518 16058 0 32767 EPSG:4326:15 1036 32117 0 65535 EPSG:4326:16 2072 64235 0 131071 EPSG:4326:17 4145 128470 0 262143 EPSG:4326:18 8290 256941 0 524287 EPSG:4326:19 16580 513883 0 1048575 EPSG:4326:20 33161 1027767 0 2097151 EPSG:4326:21 66322 2055535 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 0 31 0 31 EPSG:900913:6 1 63 0 63 EPSG:900913:7 2 127 0 127 EPSG:900913:8 5 255 0 255 EPSG:900913:9 11 511 0 511 EPSG:900913:10 22 1023 0 1023 EPSG:900913:11 45 2047 0 2047 EPSG:900913:12 91 4095 0 4095 EPSG:900913:13 182 8191 0 8191 EPSG:900913:14 365 16383 0 16383 EPSG:900913:15 731 32767 0 32767 EPSG:900913:16 1462 65535 0 65535 EPSG:900913:17 2924 131071 0 131071 EPSG:900913:18 5849 262143 0 262143 EPSG:900913:19 11698 524287 0 524287 EPSG:900913:20 23396 1048575 0 1048575 EPSG:900913:21 46792 2097151 0 2097151 EPSG:900913:22 93584 4194303 0 4194303 EPSG:900913:23 187168 8388607 0 8388607 EPSG:900913:24 374337 16777215 0 16777215 EPSG:900913:25 748674 33554431 0 33554431 EPSG:900913:26 1497349 67108863 0 67108863 EPSG:900913:27 2994698 134217727 0 134217727 EPSG:900913:28 5989396 268435455 0 268435455 EPSG:900913:29 11978792 536870911 0 536870911 EPSG:900913:30 23957585 1073741823 0 1073741823 International boundaries Level 1 subdivision - GADM 3.6 - Edited by GRID - simplified DP 0.001 on QGIS using Simplify -179.99999999999994 -90.0 180.0 83.65833282470703 grid_data_core_pro:gadm36_1_0.001_shp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 40 1023 0 1023 EPSG:3857:11 80 2047 0 2047 EPSG:3857:12 161 4095 0 4095 EPSG:3857:13 323 8191 0 8191 EPSG:3857:14 647 16383 0 16383 EPSG:3857:15 1295 32767 0 32767 EPSG:3857:16 2590 65535 0 65535 EPSG:3857:17 5181 131071 0 131071 EPSG:3857:18 10362 262143 0 262143 EPSG:3857:19 20725 524287 0 524287 EPSG:3857:20 41451 1048575 0 1048575 EPSG:3857:21 82902 2097151 0 2097151 EPSG:3857:22 165805 4194303 0 4194304 EPSG:3857:23 331611 8388607 0 8388608 EPSG:3857:24 663223 16777215 0 16777215 EPSG:3857:25 1326446 33554431 0 33554431 EPSG:3857:26 2652893 67108863 0 67108863 EPSG:3857:27 5305787 134217727 0 134217727 EPSG:3857:28 10611574 268435455 0 268435456 EPSG:3857:29 21223148 536870911 0 536870911 EPSG:3857:30 42446297 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 9 255 0 511 EPSG:4326:9 18 511 0 1023 EPSG:4326:10 36 1023 0 2047 EPSG:4326:11 72 2047 0 4095 EPSG:4326:12 144 4095 0 8191 EPSG:4326:13 288 8191 0 16383 EPSG:4326:14 577 16383 0 32767 EPSG:4326:15 1154 32767 0 65535 EPSG:4326:16 2308 65535 0 131071 EPSG:4326:17 4617 131071 0 262143 EPSG:4326:18 9235 262143 0 524287 EPSG:4326:19 18471 524287 0 1048575 EPSG:4326:20 36942 1048575 0 2097151 EPSG:4326:21 73885 2097151 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 40 1023 0 1023 EPSG:3857:11 80 2047 0 2047 EPSG:3857:12 161 4095 0 4095 EPSG:3857:13 323 8191 0 8191 EPSG:3857:14 647 16383 0 16383 EPSG:3857:15 1295 32767 0 32767 EPSG:3857:16 2590 65535 0 65535 EPSG:3857:17 5181 131071 0 131071 EPSG:3857:18 10362 262143 0 262143 EPSG:3857:19 20725 524287 0 524287 EPSG:3857:20 41451 1048575 0 1048575 EPSG:3857:21 82902 2097151 0 2097152 EPSG:3857:22 165805 4194303 0 4194304 EPSG:3857:23 331611 8388607 0 8388607 EPSG:3857:24 663223 16777215 0 16777215 EPSG:3857:25 1326446 33554431 0 33554431 EPSG:3857:26 2652893 67108863 0 67108863 EPSG:3857:27 5305787 134217727 0 134217728 EPSG:3857:28 10611574 268435455 0 268435455 EPSG:3857:29 21223148 536870911 0 536870911 EPSG:3857:30 42446297 1073741823 0 1073741824 h100ic 0.1675000015994978 11.697500041616369 16.000833334932196 23.52416670828256 risk_niger_undp:h100ic image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 3 8 8 EPSG:4326:4 5 6 16 17 EPSG:4326:5 11 13 32 34 EPSG:4326:6 23 27 64 69 EPSG:4326:7 47 55 128 139 EPSG:4326:8 94 111 256 278 EPSG:4326:9 189 222 512 557 EPSG:4326:10 378 445 1024 1115 EPSG:4326:11 756 890 2049 2230 EPSG:4326:12 1512 1781 4099 4460 EPSG:4326:13 3025 3563 8199 8920 EPSG:4326:14 6050 7127 16399 17840 EPSG:4326:15 12101 14254 32798 35680 EPSG:4326:16 24203 28509 65596 71361 EPSG:4326:17 48406 57018 131193 142723 EPSG:4326:18 96812 114036 262387 285446 EPSG:4326:19 193624 228072 524775 570893 EPSG:4326:20 387249 456145 1049551 1141787 EPSG:4326:21 774499 912290 2099103 2283575 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 Year precipitations 2013 - Central African Republic Total precipitations observed in 2013 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2013_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Gridded Livestock of the World – Goats This updated layer of The Gridded Livestock of the World (GLW)database provided modelled livestock densities of the world, adjusted to match official (FAOSTAT)national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 565 km at the equator).Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analyticalprocedure has been revised and extended to include a more systematic assessment of model accuracy and therepresentation of uncertainties associated with the predictions.<br><br>For further details on mapping methods see: Robinson, T.P., Wint, G.R.W., Conchedda, G., Van Boeckel, T.P., Ercoli, V., Palamara, E., Cinardi, G., D’Aietti, L., Hay, S.I., Gilbert, M., 2014. Mapping the Global Distribution of Livestock. PLoS ONE 9, e96084. <a href=\"https://doi.org/10.1371/journal.pone.0096084\"target=_blank>https://doi.org/10.1371/journal.pone.0096084</a><br/><br>These digital layers are made publically available via the Livestock Geo-Wiki (<a href=\"http://www.livestock.geo-wiki.org\"target=_blank>livestock.geo-wiki.org</a><br/> -180.0 -90.0 180.0 90.0 MapX_UNDP:Glb_GTAD_2006 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone surge/ Mangroves at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_man6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Water bodies -ESA300m- Global map of open permanent water bodies at 300m spatial resolution derived from the full ENVISAT-ASAR dataset between 2005 and 2010. -180.0 -90.0 180.0 90.0 grid_data_core:ESA_WB-Map-v30 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 0 31 0 31 EPSG:900913:6 0 63 0 63 EPSG:900913:7 0 127 0 127 EPSG:900913:8 0 255 0 255 EPSG:900913:9 0 511 0 511 EPSG:900913:10 0 1023 0 1023 EPSG:900913:11 0 2047 0 2047 EPSG:900913:12 0 4095 0 4095 EPSG:900913:13 0 8191 0 8191 EPSG:900913:14 0 16383 0 16383 EPSG:900913:15 0 32767 0 32767 EPSG:900913:16 0 65535 0 65535 EPSG:900913:17 0 131071 0 131071 EPSG:900913:18 0 262143 0 262143 EPSG:900913:19 0 524287 0 524287 EPSG:900913:20 0 1048575 0 1048575 EPSG:900913:21 0 2097151 0 2097151 EPSG:900913:22 0 4194303 0 4194303 EPSG:900913:23 0 8388607 0 8388607 EPSG:900913:24 0 16777215 0 16777215 EPSG:900913:25 0 33554431 0 33554431 EPSG:900913:26 0 67108863 0 67108862 EPSG:900913:27 0 134217727 0 134217724 EPSG:900913:28 0 268435455 0 268435448 EPSG:900913:29 0 536870911 0 536870896 EPSG:900913:30 0 1073741823 0 1073741793 Cities with more than 5'000 inhabitants -179.953155517578 -44.4762802124023 180.0 72.2679595947266 grid_data_core:city5k_gis image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 2 0 7 EPSG:4326:3 0 5 0 15 EPSG:4326:4 1 11 0 31 EPSG:4326:5 3 23 0 63 EPSG:4326:6 6 47 0 127 EPSG:4326:7 12 95 0 255 EPSG:4326:8 25 191 0 511 EPSG:4326:9 50 382 0 1023 EPSG:4326:10 100 765 0 2047 EPSG:4326:11 201 1530 0 4095 EPSG:4326:12 403 3060 1 8191 EPSG:4326:13 807 6120 2 16383 EPSG:4326:14 1614 12240 4 32767 EPSG:4326:15 3228 24480 8 65535 EPSG:4326:16 6456 48961 17 131071 EPSG:4326:17 12912 97922 34 262143 EPSG:4326:18 25824 195845 68 524287 EPSG:4326:19 51648 391690 136 1048575 EPSG:4326:20 103296 783381 272 2097151 EPSG:4326:21 206593 1566762 545 4194303 EPSG:900913 Threatened Mammals of the World (Jenkins, Pimm & Joppa - 2013) Maps of mammal diversity include the total species richness, major taxonomic Orders (Cetartiodactyla, Carnivora, Primates, Eulipotyphla, Chiroptera, Rodentia), marsupials, threatened species, and small-ranged species. Species considered small-ranged are those with a geographic range size smaller than the global median (i.e., the 50% of species with the smallest ranges). Maps are based on data from the IUCN, July 2013 update. All maps were generated at a spatial resolution of 10×10 km and use the Eckert IV equal-area projection. Maps represent native, extant species only. Tables of the mammal species included are available for download here: http://biodiversitymapping.org/wordpress/index.php/mammals/ Direct Link to download:http://biodiversitymapping.org/wordpress/index.php/download/ -179.49349086582234 -56.61353702601424 179.52408225466056 83.78813167493983 MAPX_nd:wld_richness_10km_mammals_threatened image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 4 88 0 127 EPSG:3857:8 9 177 0 255 EPSG:3857:9 18 354 0 511 EPSG:3857:10 37 708 1 1022 EPSG:3857:11 74 1416 2 2045 EPSG:3857:12 148 2833 5 4090 EPSG:3857:13 296 5666 11 8181 EPSG:3857:14 593 11332 23 16362 EPSG:3857:15 1187 22664 46 32724 EPSG:3857:16 2374 45329 92 65449 EPSG:3857:17 4749 90659 184 130898 EPSG:3857:18 9498 181319 368 261797 EPSG:3857:19 18996 362638 737 523594 EPSG:3857:20 37993 725277 1475 1047189 EPSG:3857:21 75986 1450555 2950 2094379 EPSG:3857:22 151973 2901111 5901 4188759 EPSG:3857:23 303946 5802223 11802 8377518 EPSG:3857:24 607893 11604446 23605 16755036 EPSG:3857:25 1215787 23208893 47210 33510073 EPSG:3857:26 2431574 46417786 94420 67020146 EPSG:3857:27 4863148 92835572 188840 134040293 EPSG:3857:28 9726297 185671145 377680 268080586 EPSG:3857:29 19452594 371342291 755361 536161172 EPSG:3857:30 38905189 742684582 1510722 1072322344 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 52 0 127 EPSG:4326:7 4 104 0 255 EPSG:4326:8 8 208 0 511 EPSG:4326:9 17 417 1 1022 EPSG:4326:10 35 834 2 2045 EPSG:4326:11 70 1668 5 4090 EPSG:4326:12 141 3336 11 8181 EPSG:4326:13 282 6672 23 16362 EPSG:4326:14 565 13345 46 32724 EPSG:4326:15 1130 26690 92 65449 EPSG:4326:16 2261 53380 184 130898 EPSG:4326:17 4523 106760 368 261797 EPSG:4326:18 9046 213521 737 523594 EPSG:4326:19 18093 427042 1475 1047189 EPSG:4326:20 36186 854085 2950 2094379 EPSG:4326:21 72373 1708171 5901 4188759 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 1 22 0 31 EPSG:900913:6 2 44 0 63 EPSG:900913:7 4 88 0 127 EPSG:900913:8 9 177 0 255 EPSG:900913:9 18 354 0 511 EPSG:900913:10 37 708 1 1022 EPSG:900913:11 74 1416 2 2045 EPSG:900913:12 148 2833 5 4090 EPSG:900913:13 296 5666 11 8181 EPSG:900913:14 593 11332 23 16362 EPSG:900913:15 1187 22664 46 32724 EPSG:900913:16 2374 45329 92 65449 EPSG:900913:17 4749 90659 184 130898 EPSG:900913:18 9498 181319 368 261797 EPSG:900913:19 18996 362638 737 523594 EPSG:900913:20 37993 725277 1475 1047189 EPSG:900913:21 75986 1450555 2950 2094379 EPSG:900913:22 151973 2901111 5901 4188759 EPSG:900913:23 303946 5802223 11802 8377518 EPSG:900913:24 607893 11604446 23605 16755036 EPSG:900913:25 1215787 23208893 47210 33510073 EPSG:900913:26 2431574 46417786 94420 67020146 EPSG:900913:27 4863148 92835572 188840 134040293 EPSG:900913:28 9726297 185671145 377680 268080586 EPSG:900913:29 19452594 371342291 755361 536161172 EPSG:900913:30 38905189 742684582 1510722 1072322344 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 4 88 0 127 EPSG:3857:8 9 177 0 255 EPSG:3857:9 18 354 0 511 EPSG:3857:10 37 708 1 1022 EPSG:3857:11 74 1416 2 2045 EPSG:3857:12 148 2833 5 4090 EPSG:3857:13 296 5666 11 8181 EPSG:3857:14 593 11332 23 16362 EPSG:3857:15 1187 22664 46 32724 EPSG:3857:16 2374 45329 92 65449 EPSG:3857:17 4749 90659 184 130898 EPSG:3857:18 9498 181319 368 261797 EPSG:3857:19 18996 362638 737 523594 EPSG:3857:20 37993 725277 1475 1047189 EPSG:3857:21 75986 1450555 2950 2094379 EPSG:3857:22 151973 2901111 5901 4188759 EPSG:3857:23 303946 5802223 11802 8377518 EPSG:3857:24 607893 11604446 23605 16755036 EPSG:3857:25 1215787 23208893 47210 33510073 EPSG:3857:26 2431574 46417786 94420 67020146 EPSG:3857:27 4863148 92835572 188840 134040293 EPSG:3857:28 9726297 185671145 377680 268080586 EPSG:3857:29 19452594 371342291 755361 536161172 EPSG:3857:30 38905189 742684582 1510722 1072322344 Travel_time_final_Togo_opt -0.1462858377361148 5.639838970959496 1.832407081892993 11.150878574350621 AccessMod:Travel_time_final_Togo_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 3 3 3 4 EPSG:3857:4 7 7 7 8 EPSG:3857:5 15 15 15 16 EPSG:3857:6 30 30 31 32 EPSG:3857:7 60 61 63 64 EPSG:3857:8 120 123 127 129 EPSG:3857:9 240 247 255 258 EPSG:3857:10 480 495 511 517 EPSG:3857:11 960 991 1023 1034 EPSG:3857:12 1920 1983 2046 2068 EPSG:3857:13 3840 3967 4092 4137 EPSG:3857:14 7681 7934 8185 8275 EPSG:3857:15 15362 15869 16370 16550 EPSG:3857:16 30725 31739 32741 33101 EPSG:3857:17 61450 63479 65482 66203 EPSG:3857:18 122900 126958 130965 132406 EPSG:3857:19 245800 253917 261930 264812 EPSG:3857:20 491601 507834 523861 529625 EPSG:3857:21 983203 1015668 1047723 1059250 EPSG:3857:22 1966406 2031336 2095447 2118501 EPSG:3857:23 3932813 4062673 4190895 4237002 EPSG:3857:24 7865627 8125346 8381790 8474004 EPSG:3857:25 15731254 16250693 16763581 16948008 EPSG:3857:26 31462509 32501387 33527162 33896017 EPSG:3857:27 62925019 65002775 67054324 67792034 EPSG:3857:28 125850038 130005551 134108649 135584069 EPSG:3857:29 251700077 260011103 268217298 271168139 EPSG:3857:30 503400154 520022206 536434597 542336279 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 1 1 3 4 EPSG:4326:3 3 3 7 8 EPSG:4326:4 7 7 15 16 EPSG:4326:5 14 14 31 32 EPSG:4326:6 28 29 63 64 EPSG:4326:7 56 59 127 129 EPSG:4326:8 112 119 255 258 EPSG:4326:9 224 239 511 517 EPSG:4326:10 448 479 1023 1034 EPSG:4326:11 897 959 2046 2068 EPSG:4326:12 1794 1919 4092 4137 EPSG:4326:13 3588 3839 8185 8275 EPSG:4326:14 7177 7678 16370 16550 EPSG:4326:15 14354 15357 32741 33101 EPSG:4326:16 28708 30714 65482 66203 EPSG:4326:17 57416 61429 130965 132406 EPSG:4326:18 114832 122858 261930 264812 EPSG:4326:19 229664 245716 523861 529625 EPSG:4326:20 459329 491433 1047723 1059250 EPSG:4326:21 918658 982867 2095447 2118501 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 3 3 3 4 EPSG:3857:4 7 7 7 8 EPSG:3857:5 15 15 15 16 EPSG:3857:6 30 30 31 32 EPSG:3857:7 60 61 63 64 EPSG:3857:8 120 123 127 129 EPSG:3857:9 240 247 255 258 EPSG:3857:10 480 495 511 517 EPSG:3857:11 960 991 1023 1034 EPSG:3857:12 1920 1983 2046 2068 EPSG:3857:13 3840 3967 4092 4137 EPSG:3857:14 7681 7934 8185 8275 EPSG:3857:15 15362 15869 16370 16550 EPSG:3857:16 30725 31739 32741 33101 EPSG:3857:17 61450 63479 65482 66203 EPSG:3857:18 122900 126958 130965 132406 EPSG:3857:19 245800 253917 261930 264812 EPSG:3857:20 491601 507834 523861 529625 EPSG:3857:21 983203 1015668 1047723 1059250 EPSG:3857:22 1966406 2031336 2095447 2118501 EPSG:3857:23 3932813 4062673 4190895 4237002 EPSG:3857:24 7865627 8125346 8381790 8474004 EPSG:3857:25 15731254 16250693 16763581 16948008 EPSG:3857:26 31462509 32501387 33527162 33896017 EPSG:3857:27 62925019 65002775 67054324 67792034 EPSG:3857:28 125850038 130005551 134108649 135584069 EPSG:3857:29 251700077 260011103 268217298 271168139 EPSG:3857:30 503400154 520022206 536434597 542336279 Mean temperatures 2006 - Central African Republic Mean observed temperatures in 2006 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2006_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Forest Integrity Indonesia Vietnam Forest Integrity (100m res.) in Indonesia and Vietnam (Montana State University) The forest integrrity index is derived by overlaying the human footprint (Venter et al. 2016) on the forest structural condition. The name is consistent with the concept of ecological integrity. Ecological integrity has been defined as, “the system’s capacity to maintain structure and ecosystem functions using processes and elements characteristic for its ecoregion.” (Parks Canada 2008).  This capacity is a result of the climate, soil, topography, biota and other biophysical properties of the ecoregion and the extent to which these properties are not altered by modern human pressures. Consistent with this definition, the forest integrity index is based on on the structural complexity of a stand relative to the natural potential of the ecoregion and level of human pressure. Thus, forest of high integrity are relatively tall, high in canopy cover, older, and with relatively low human pressure.  An increasing number of studies have shown that human pressure in various forms can have negative effects on native species.  Thus, high integrity forests may be uniquely important for conservation because they support species and processes that are require well-developed forests and are sensitive to human activities.  Such forests often also have high economic value and have likely been preferentially converted to more intense human land uses.  Thus, identifying remaining areas of high forest integrity is important for conservation planning.<br><br>Data is provided by Montana State University.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/">CC-4.0 Attribution</a>.<br/> 100.0 -9.999861112471002 141.016129418236 23.384477504501 MapX_UNDP:indo_forint100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain 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239366975 EPSG:900913:29 232551442 283424621 417566264 478733950 EPSG:900913:30 465102885 566849242 835132529 957467900 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 3 3 EPSG:3857:3 3 4 6 7 EPSG:3857:4 6 8 12 14 EPSG:3857:5 13 16 24 28 EPSG:3857:6 27 33 49 57 EPSG:3857:7 55 67 99 114 EPSG:3857:8 110 135 199 228 EPSG:3857:9 221 270 398 456 EPSG:3857:10 443 540 796 913 EPSG:3857:11 887 1081 1592 1826 EPSG:3857:12 1774 2162 3185 3652 EPSG:3857:13 3548 4324 6371 7304 EPSG:3857:14 7096 8649 12743 14609 EPSG:3857:15 14193 17298 25486 29219 EPSG:3857:16 28387 34597 50972 58439 EPSG:3857:17 56775 69195 101944 116878 EPSG:3857:18 113550 138390 203889 233756 EPSG:3857:19 227101 276781 407779 467513 EPSG:3857:20 454202 553563 815559 935027 EPSG:3857:21 908404 1107127 1631118 1870054 EPSG:3857:22 1816808 2214254 3262236 3740108 EPSG:3857:23 3633616 4428509 6524472 7480217 EPSG:3857:24 7267232 8857019 13048945 14960435 EPSG:3857:25 14534465 17714038 26097891 29920871 EPSG:3857:26 29068930 35428077 52195783 59841743 EPSG:3857:27 58137860 70856155 104391566 119683487 EPSG:3857:28 116275721 141712310 208783132 239366975 EPSG:3857:29 232551442 283424621 417566264 478733950 EPSG:3857:30 465102885 566849242 835132529 957467900 popV10a 0.1734108579448161 11.647777821277227 13.816738733944817 21.183607340277227 risk_niger_undp:popV10a image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 17 EPSG:3857:6 28 29 32 34 EPSG:3857:7 56 59 64 68 EPSG:3857:8 112 119 128 137 EPSG:3857:9 225 239 256 275 EPSG:3857:10 450 478 512 551 EPSG:3857:11 900 957 1024 1102 EPSG:3857:12 1801 1914 2049 2205 EPSG:3857:13 3602 3829 4099 4410 EPSG:3857:14 7205 7658 8199 8820 EPSG:3857:15 14410 15316 16399 17641 EPSG:3857:16 28820 30632 32799 35283 EPSG:3857:17 57641 61265 65599 70566 EPSG:3857:18 115282 122531 131198 141133 EPSG:3857:19 230565 245062 262396 282266 EPSG:3857:20 461130 490125 524793 564532 EPSG:3857:21 922261 980250 1049586 1129064 EPSG:3857:22 1844522 1960501 2099172 2258128 EPSG:3857:23 3689044 3921002 4198344 4516257 EPSG:3857:24 7378088 7842004 8396689 9032514 EPSG:3857:25 14756176 15684008 16793379 18065029 EPSG:3857:26 29512352 31368016 33586758 36130058 EPSG:3857:27 59024705 62736033 67173516 72260117 EPSG:3857:28 118049411 125472066 134347032 144520235 EPSG:3857:29 236098822 250944132 268694065 289040470 EPSG:3857:30 472197645 501888265 537388130 578080940 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 6 6 16 17 EPSG:4326:5 12 13 32 34 EPSG:4326:6 24 27 64 68 EPSG:4326:7 48 55 128 137 EPSG:4326:8 97 111 256 275 EPSG:4326:9 195 222 512 551 EPSG:4326:10 391 445 1024 1102 EPSG:4326:11 782 891 2049 2205 EPSG:4326:12 1565 1782 4099 4410 EPSG:4326:13 3131 3565 8199 8820 EPSG:4326:14 6263 7131 16399 17641 EPSG:4326:15 12527 14263 32799 35283 EPSG:4326:16 25055 28527 65599 70566 EPSG:4326:17 50110 57054 131198 141133 EPSG:4326:18 100221 114108 262396 282266 EPSG:4326:19 200442 228217 524793 564532 EPSG:4326:20 400884 456434 1049586 1129064 EPSG:4326:21 801769 912869 2099172 2258128 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 17 EPSG:3857:6 28 29 32 34 EPSG:3857:7 56 59 64 68 EPSG:3857:8 112 119 128 137 EPSG:3857:9 225 239 256 275 EPSG:3857:10 450 478 512 551 EPSG:3857:11 900 957 1024 1102 EPSG:3857:12 1801 1914 2049 2205 EPSG:3857:13 3602 3829 4099 4410 EPSG:3857:14 7205 7658 8199 8820 EPSG:3857:15 14410 15316 16399 17641 EPSG:3857:16 28820 30632 32799 35283 EPSG:3857:17 57641 61265 65599 70566 EPSG:3857:18 115282 122531 131198 141133 EPSG:3857:19 230565 245062 262396 282266 EPSG:3857:20 461130 490125 524793 564532 EPSG:3857:21 922261 980250 1049586 1129064 EPSG:3857:22 1844522 1960501 2099172 2258128 EPSG:3857:23 3689044 3921002 4198344 4516257 EPSG:3857:24 7378088 7842004 8396689 9032514 EPSG:3857:25 14756176 15684008 16793379 18065029 EPSG:3857:26 29512352 31368016 33586758 36130058 EPSG:3857:27 59024705 62736033 67173516 72260117 EPSG:3857:28 118049411 125472066 134347032 144520235 EPSG:3857:29 236098822 250944132 268694065 289040470 EPSG:3857:30 472197645 501888265 537388130 578080940 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from Institute for Numerical Mathematics, Russia, INMCM3.0 Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_inmcm3_0_5km_2041-2060_debiasedmean_tas_av_12m_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Combination Tsunami/Coral reefs at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_cor6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Self-calibrating Palmer Drought Severity Index (scPDSI) 2016 (CRU) This layer shows the average values for 2016 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_16_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Precipitation anomalies (mm) 2045-2065 (RCP8.5) Yearly precipitation anomalies (mm) for the period 2045-2065 based on the climate scenario RCP8.5 (reference 1986-2005). -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:pr_85_46_65 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 6 11 EPSG:4326:4 3 8 13 22 EPSG:4326:5 7 17 27 45 EPSG:4326:6 15 34 54 90 EPSG:4326:7 31 68 109 181 EPSG:4326:8 63 137 218 363 EPSG:4326:9 127 275 436 726 EPSG:4326:10 255 550 872 1453 EPSG:4326:11 510 1101 1745 2906 EPSG:4326:12 1021 2203 3490 5813 EPSG:4326:13 2043 4406 6980 11626 EPSG:4326:14 4086 8812 13960 23252 EPSG:4326:15 8173 17625 27921 46505 EPSG:4326:16 16347 35251 55843 93010 EPSG:4326:17 32695 70502 111687 186020 EPSG:4326:18 65390 141004 223375 372040 EPSG:4326:19 130780 282008 446751 744081 EPSG:4326:20 261561 564017 893503 1488162 EPSG:4326:21 523122 1128034 1787006 2976324 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 Tropical cyclone hazard frequency -180.0 -90.0 180.0 90.0 ECO-DRR:cy_freqa_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Global Wetlands (v2) - CIFOR This dataset shows a distribution of wetland that covers the tropics and sub tropics (40° N to 60° S; 180° E to -180° W), excluding small islands. It was mapped in 231 meters spatial resolution by combining a hydrological model and annual time series of satellite-derived estimates of soil moisture to represent water flow and surface wetness that are then combined with geomorphological data.<br><br>The Global Wetlands Map is produced by the Sustainable Wetlands Adaptation and Mitigation Program (SWAMP), a collaborative effort between the Center for International Forestry Research (<a href="https://www.cifor.org">CIFOR</a>) and the <a href="http://www.fs.fed.us">United States Forest Service</a>, supported by the United States Agency for International Development (<a href="https://www.usaid.gov">USAID</a>) and the CGIAR Research Program on Forests, Trees and Agroforestry (<a href="http://foreststreesagroforestry.org">FTA</a>).<br/><br>Term of Use: The information contained in this dataset is the exclusive property of Center for International Forestry Research (CIFOR) and any respective copyright owners. This work is protected under international copyright treaties and convention (<a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a>). All uses for commercial purposes require the written permission of the <a href="https://www.cifor.org/">Center for International Forestry Research (CIFOR)</a><br/>. -179.99999777114783 -60.001279841670446 179.99926251758217 40.00080455854803 MapX_UNDP:trop-subtrop_wetlandv2_2016_cifor_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 5 0 7 EPSG:3857:4 6 11 0 15 EPSG:3857:5 12 22 0 31 EPSG:3857:6 24 45 0 63 EPSG:3857:7 48 90 0 127 EPSG:3857:8 96 181 0 255 EPSG:3857:9 193 363 0 511 EPSG:3857:10 387 726 0 1023 EPSG:3857:11 775 1453 0 2047 EPSG:3857:12 1550 2906 0 4095 EPSG:3857:13 3101 5813 0 8191 EPSG:3857:14 6202 11626 0 16383 EPSG:3857:15 12405 23252 0 32767 EPSG:3857:16 24810 46504 0 65535 EPSG:3857:17 49620 93009 0 131071 EPSG:3857:18 99241 186019 0 262143 EPSG:3857:19 198482 372038 0 524286 EPSG:3857:20 396965 744077 0 1048573 EPSG:3857:21 793931 1488154 0 2097147 EPSG:3857:22 1587863 2976309 0 4194295 EPSG:3857:23 3175727 5952618 0 8388590 EPSG:3857:24 6351455 11905237 0 16777181 EPSG:3857:25 12702910 23810475 0 33554363 EPSG:3857:26 25405821 47620951 0 67108726 EPSG:3857:27 50811642 95241902 0 134217453 EPSG:3857:28 101623285 190483804 1 268434906 EPSG:3857:29 203246571 380967609 3 536869812 EPSG:3857:30 406493142 761935218 6 1073739624 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 1 3 0 7 EPSG:4326:3 2 6 0 15 EPSG:4326:4 4 13 0 31 EPSG:4326:5 8 26 0 63 EPSG:4326:6 17 53 0 127 EPSG:4326:7 35 106 0 255 EPSG:4326:8 71 213 0 511 EPSG:4326:9 142 426 0 1023 EPSG:4326:10 284 853 0 2047 EPSG:4326:11 568 1706 0 4095 EPSG:4326:12 1137 3413 0 8191 EPSG:4326:13 2275 6826 0 16383 EPSG:4326:14 4551 13653 0 32767 EPSG:4326:15 9102 27306 0 65535 EPSG:4326:16 18204 54613 0 131071 EPSG:4326:17 36408 109227 0 262143 EPSG:4326:18 72816 218455 0 524286 EPSG:4326:19 145633 436910 0 1048573 EPSG:4326:20 291266 873820 0 2097147 EPSG:4326:21 582532 1747641 0 4194295 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 5 0 7 EPSG:3857:4 6 11 0 15 EPSG:3857:5 12 22 0 31 EPSG:3857:6 24 45 0 63 EPSG:3857:7 48 90 0 127 EPSG:3857:8 96 181 0 255 EPSG:3857:9 193 363 0 511 EPSG:3857:10 387 726 0 1023 EPSG:3857:11 775 1453 0 2047 EPSG:3857:12 1550 2906 0 4095 EPSG:3857:13 3101 5813 0 8191 EPSG:3857:14 6202 11626 0 16383 EPSG:3857:15 12405 23252 0 32767 EPSG:3857:16 24810 46504 0 65535 EPSG:3857:17 49620 93009 0 131071 EPSG:3857:18 99241 186019 0 262143 EPSG:3857:19 198482 372038 0 524286 EPSG:3857:20 396965 744077 0 1048573 EPSG:3857:21 793931 1488154 0 2097147 EPSG:3857:22 1587863 2976309 0 4194295 EPSG:3857:23 3175727 5952618 0 8388590 EPSG:3857:24 6351455 11905237 0 16777181 EPSG:3857:25 12702910 23810475 0 33554363 EPSG:3857:26 25405821 47620951 0 67108726 EPSG:3857:27 50811642 95241902 0 134217453 EPSG:3857:28 101623285 190483804 1 268434906 EPSG:3857:29 203246571 380967609 3 536869812 EPSG:3857:30 406493142 761935218 6 1073739624 Selyaninov's Hydrothermic Coefficient (1979-2013) - CHELSA Unit=(kg/m^2/10)/Celsius The Selyaninov's Hydrothermic Coefficient (shc) describes moistening conditions. Unlike precipitation measurements, shc takes into account temperature-related vaporability. shc is calculated using the following formula: the amount of precipitation during the period in which air temperatures are above + 5°C is divided by the sum of average daily temperatures for the same period reduced to its tenth part (Selyaninov, 1937). On the whole, shc values over 1 are typical of normal or excessive moistening, while those less than 1 are typical of moistening insufficient for basic cultivated crops. This dataset is provided by CHELSA. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_shc_5_1979-2013_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 Temperature anomalies (°C) 2045-2065 (RCP8.5) Temperature anomalies (°C) for the period 2045-2065 based on the climate scenario RCP8.5 (reference 1986-2005). -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:tas_85_46_65 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 6 11 EPSG:4326:4 3 8 13 22 EPSG:4326:5 7 17 27 45 EPSG:4326:6 15 34 54 90 EPSG:4326:7 31 68 109 181 EPSG:4326:8 63 137 218 363 EPSG:4326:9 127 275 436 726 EPSG:4326:10 255 550 872 1453 EPSG:4326:11 510 1101 1745 2906 EPSG:4326:12 1021 2203 3490 5813 EPSG:4326:13 2043 4406 6980 11626 EPSG:4326:14 4086 8812 13960 23252 EPSG:4326:15 8173 17625 27921 46505 EPSG:4326:16 16347 35251 55843 93010 EPSG:4326:17 32695 70502 111687 186020 EPSG:4326:18 65390 141004 223375 372040 EPSG:4326:19 130780 282008 446751 744081 EPSG:4326:20 261561 564017 893503 1488162 EPSG:4326:21 523122 1128034 1787006 2976324 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 Spring temperature change (°C) for the period 2020 - 2039 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_mam_NEARREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Average year temperature (2001-2010) Average year temperature in °Celsius across the period 2001-2010. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_01_10_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 wesr_climate_slr_tropex_n -180.0 -85.0 180.0 85.0 wesr_climat:wesr_climate_slr_tropex_n image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 1 1022 0 1023 EPSG:3857:11 3 2044 0 2047 EPSG:3857:12 6 4089 0 4095 EPSG:3857:13 13 8178 0 8191 EPSG:3857:14 26 16357 0 16383 EPSG:3857:15 53 32714 0 32767 EPSG:3857:16 107 65428 0 65535 EPSG:3857:17 214 130857 0 131071 EPSG:3857:18 429 261714 0 262143 EPSG:3857:19 858 523429 0 524287 EPSG:3857:20 1717 1046858 0 1048575 EPSG:3857:21 3434 2093717 0 2097151 EPSG:3857:22 6869 4187434 0 4194304 EPSG:3857:23 13739 8374868 0 8388608 EPSG:3857:24 27479 16749736 0 16777215 EPSG:3857:25 54959 33499472 0 33554431 EPSG:3857:26 109918 66998945 0 67108863 EPSG:3857:27 219837 133997890 0 134217727 EPSG:3857:28 439674 267995781 0 268435456 EPSG:3857:29 879348 535991563 0 536870911 EPSG:3857:30 1758697 1071983126 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 62 0 127 EPSG:4326:7 3 124 0 255 EPSG:4326:8 7 248 0 511 EPSG:4326:9 14 497 0 1023 EPSG:4326:10 28 995 0 2047 EPSG:4326:11 56 1991 0 4095 EPSG:4326:12 113 3982 0 8191 EPSG:4326:13 227 7964 0 16383 EPSG:4326:14 455 15928 0 32767 EPSG:4326:15 910 31857 0 65535 EPSG:4326:16 1820 63715 0 131071 EPSG:4326:17 3640 127431 0 262143 EPSG:4326:18 7281 254862 0 524287 EPSG:4326:19 14563 509724 0 1048575 EPSG:4326:20 29127 1019448 0 2097151 EPSG:4326:21 58254 2038897 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 1 1022 0 1023 EPSG:3857:11 3 2044 0 2047 EPSG:3857:12 6 4089 0 4095 EPSG:3857:13 13 8178 0 8191 EPSG:3857:14 26 16357 0 16383 EPSG:3857:15 53 32714 0 32767 EPSG:3857:16 107 65428 0 65535 EPSG:3857:17 214 130857 0 131071 EPSG:3857:18 429 261714 0 262143 EPSG:3857:19 858 523429 0 524287 EPSG:3857:20 1717 1046858 0 1048575 EPSG:3857:21 3434 2093717 0 2097152 EPSG:3857:22 6869 4187434 0 4194304 EPSG:3857:23 13739 8374868 0 8388607 EPSG:3857:24 27479 16749736 0 16777215 EPSG:3857:25 54959 33499472 0 33554431 EPSG:3857:26 109918 66998945 0 67108863 EPSG:3857:27 219837 133997890 0 134217728 EPSG:3857:28 439674 267995781 0 268435455 EPSG:3857:29 879348 535991563 0 536870911 EPSG:3857:30 1758697 1071983126 0 1073741824 Winter temperature change (°C) for the period 2020 - 2039 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_djf_NEARREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 site_0060_Landsat_jpgs_extra -10.858176899138206 8.079534492312552 -10.189521743955197 8.79879002262406 test_antonio_mosaics:site_0060_Landsat_jpgs_extra image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 30 30 EPSG:4326:6 28 29 60 60 EPSG:4326:7 57 58 120 120 EPSG:4326:8 115 116 240 241 EPSG:4326:9 230 233 481 483 EPSG:4326:10 461 466 962 966 EPSG:4326:11 923 932 1924 1932 EPSG:4326:12 1847 1864 3848 3864 EPSG:4326:13 3695 3728 7697 7728 EPSG:4326:14 7391 7456 15395 15456 EPSG:4326:15 14782 14913 30791 30913 EPSG:4326:16 29564 29826 61582 61826 EPSG:4326:17 59128 59652 123165 123652 EPSG:4326:18 118257 119305 246330 247304 EPSG:4326:19 236515 238610 492661 494608 EPSG:4326:20 473031 477221 985322 989217 EPSG:4326:21 946062 954442 1970645 1978435 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 Combination Tsunami/Coral reefs at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_cor6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 site_0060_Landsat_jpgs -10.858176899138206 8.079534492312552 -10.189521743955197 8.79879002262406 test_antonio_mosaics:site_0060_Landsat_jpgs image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 30 30 EPSG:4326:6 28 29 60 60 EPSG:4326:7 57 58 120 120 EPSG:4326:8 115 116 240 241 EPSG:4326:9 230 233 481 483 EPSG:4326:10 461 466 962 966 EPSG:4326:11 923 932 1924 1932 EPSG:4326:12 1847 1864 3848 3864 EPSG:4326:13 3695 3728 7697 7728 EPSG:4326:14 7391 7456 15395 15456 EPSG:4326:15 14782 14913 30791 30913 EPSG:4326:16 29564 29826 61582 61826 EPSG:4326:17 59128 59652 123165 123652 EPSG:4326:18 118257 119305 246330 247304 EPSG:4326:19 236515 238610 492661 494608 EPSG:4326:20 473031 477221 985322 989217 EPSG:4326:21 946062 954442 1970645 1978435 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 TZA_kilombero_sequest_fut_SAGCOTwc 34.553167266769464 -10.038048450490551 37.239835341004294 -7.663994368030097 TEEB:sequest_fut_SAGCOTwc_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 19 19 EPSG:4326:5 17 17 38 38 EPSG:4326:6 34 35 76 77 EPSG:4326:7 69 71 152 154 EPSG:4326:8 138 142 305 308 EPSG:4326:9 277 284 610 617 EPSG:4326:10 555 569 1220 1235 EPSG:4326:11 1111 1138 2441 2471 EPSG:4326:12 2222 2276 4882 4943 EPSG:4326:13 4444 4552 9764 9886 EPSG:4326:14 8889 9105 19529 19773 EPSG:4326:15 17779 18211 39058 39547 EPSG:4326:16 35558 36422 78116 79094 EPSG:4326:17 71116 72845 156232 158189 EPSG:4326:18 142233 145690 312465 316378 EPSG:4326:19 284467 291381 624931 632756 EPSG:4326:20 568934 582763 1249862 1265513 EPSG:4326:21 1137868 1165527 2499725 2531027 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 Crop Suitability Change 2011-2100 This dataset show general agricultural suitability at a spatial resolution of 30 arc-second (~1km), considering rainfed conditions and irrigation on currently irrigated areas. The agricultural suitability represents for each pixel the maximum suitability value of considered 16 plants, including: We show a subset of the data that covers three time periods (1981-2010, 2011-2040, 2071-2100), as well as changes in agricultural suitability over the same periods.<br><br>For futher details see: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107522">Zabel F., Putzenlechner B., Mauser W. (2014): Global agricultural land resources – a high resolution suitability evaluation and its perspectives until 2100 under climate change conditions</a><br/><br>Data can also be downloaded from <a href="http://geoportal-glues.ufz.de/stories/globalsuitability.html">here</a>.<br/> -180.0 -60.0 180.0 90.0 MapX_UNDP:overall_cropsuit_i_diff_20112040_20712100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 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10.498445831783116 MAPX:test_ssd image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 30 30 37 37 EPSG:3857:7 60 60 75 75 EPSG:3857:8 120 120 151 151 EPSG:3857:9 240 241 302 302 EPSG:3857:10 481 482 604 604 EPSG:3857:11 963 964 1208 1209 EPSG:3857:12 1927 1929 2417 2418 EPSG:3857:13 3855 3858 4834 4836 EPSG:3857:14 7711 7716 9668 9673 EPSG:3857:15 15423 15432 19337 19346 EPSG:3857:16 30846 30864 38674 38693 EPSG:3857:17 61692 61728 77349 77387 EPSG:3857:18 123384 123456 154699 154774 EPSG:3857:19 246768 246913 309398 309549 EPSG:3857:20 493536 493827 618797 619098 EPSG:3857:21 987072 987654 1237595 1238197 EPSG:3857:22 1974145 1975308 2475190 2476394 EPSG:3857:23 3948291 3950617 4950380 4952789 EPSG:3857:24 7896583 7901235 9900760 9905579 EPSG:3857:25 15793167 15802471 19801520 19811159 EPSG:3857:26 31586335 31604943 39603041 39622319 EPSG:3857:27 63172671 63209887 79206083 79244639 EPSG:3857:28 126345343 126419774 158412166 158489278 EPSG:3857:29 252690687 252839549 316824332 316978557 EPSG:3857:30 505381375 505679098 633648665 633957115 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 14 14 37 37 EPSG:4326:6 28 28 75 75 EPSG:4326:7 56 56 151 151 EPSG:4326:8 113 113 302 302 EPSG:4326:9 226 226 604 604 EPSG:4326:10 452 452 1208 1209 EPSG:4326:11 904 905 2417 2418 EPSG:4326:12 1809 1811 4834 4836 EPSG:4326:13 3618 3622 9668 9673 EPSG:4326:14 7236 7245 19337 19346 EPSG:4326:15 14472 14490 38674 38693 EPSG:4326:16 28945 28981 77349 77387 EPSG:4326:17 57891 57962 154699 154774 EPSG:4326:18 115782 115925 309398 309549 EPSG:4326:19 231565 231850 618797 619098 EPSG:4326:20 463130 463701 1237595 1238197 EPSG:4326:21 926260 927403 2475190 2476394 EPSG:900913 Sand Demand Distribution in Western Area and Lungi-Mahera corridor -13.2995832582623 8.093137521714812 -12.904858119938874 8.716250167822336 sand:new_road_aggregate_change__2030 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 14 14 EPSG:3857:6 30 30 29 29 EPSG:3857:7 60 61 59 59 EPSG:3857:8 121 122 118 118 EPSG:3857:9 243 244 237 237 EPSG:3857:10 487 488 474 475 EPSG:3857:11 974 977 948 950 EPSG:3857:12 1948 1955 1896 1901 EPSG:3857:13 3896 3911 3793 3802 EPSG:3857:14 7793 7822 7586 7604 EPSG:3857:15 15587 15644 15173 15209 EPSG:3857:16 31175 31289 30346 30418 EPSG:3857:17 62350 62579 60693 60837 EPSG:3857:18 124700 125159 121387 121674 EPSG:3857:19 249400 250318 242775 243349 EPSG:3857:20 498801 500636 485550 486699 EPSG:3857:21 997603 1001272 971100 973399 EPSG:3857:22 1995206 2002544 1942200 1946799 EPSG:3857:23 3990412 4005089 3884401 3893599 EPSG:3857:24 7980825 8010179 7768802 7787198 EPSG:3857:25 15961650 16020359 15537604 15574396 EPSG:3857:26 31923301 32040719 31075209 31148792 EPSG:3857:27 63846603 64081439 62150419 62297584 EPSG:3857:28 127693206 128162879 124300839 124595168 EPSG:3857:29 255386412 256325758 248601679 249190336 EPSG:3857:30 510772824 512651516 497203359 498380673 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 14 14 EPSG:4326:5 14 14 29 29 EPSG:4326:6 28 29 59 59 EPSG:4326:7 57 58 118 118 EPSG:4326:8 115 116 237 237 EPSG:4326:9 231 232 474 475 EPSG:4326:10 462 465 948 950 EPSG:4326:11 924 931 1896 1901 EPSG:4326:12 1849 1863 3793 3802 EPSG:4326:13 3699 3727 7586 7604 EPSG:4326:14 7398 7455 15173 15209 EPSG:4326:15 14797 14910 30346 30418 EPSG:4326:16 29594 29821 60693 60837 EPSG:4326:17 59189 59642 121387 121674 EPSG:4326:18 118378 119285 242775 243349 EPSG:4326:19 236756 238571 485550 486699 EPSG:4326:20 473512 477142 971100 973399 EPSG:4326:21 947024 954284 1942200 1946799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 14 14 EPSG:3857:6 30 30 29 29 EPSG:3857:7 60 61 59 59 EPSG:3857:8 121 122 118 118 EPSG:3857:9 243 244 237 237 EPSG:3857:10 487 488 474 475 EPSG:3857:11 974 977 948 950 EPSG:3857:12 1948 1955 1896 1901 EPSG:3857:13 3896 3911 3793 3802 EPSG:3857:14 7793 7822 7586 7604 EPSG:3857:15 15587 15644 15173 15209 EPSG:3857:16 31175 31289 30346 30418 EPSG:3857:17 62350 62579 60693 60837 EPSG:3857:18 124700 125159 121387 121674 EPSG:3857:19 249400 250318 242775 243349 EPSG:3857:20 498801 500636 485550 486699 EPSG:3857:21 997603 1001272 971100 973399 EPSG:3857:22 1995206 2002544 1942200 1946799 EPSG:3857:23 3990412 4005089 3884401 3893599 EPSG:3857:24 7980825 8010179 7768802 7787198 EPSG:3857:25 15961650 16020359 15537604 15574396 EPSG:3857:26 31923301 32040719 31075209 31148792 EPSG:3857:27 63846603 64081439 62150419 62297584 EPSG:3857:28 127693206 128162879 124300839 124595168 EPSG:3857:29 255386412 256325758 248601679 249190336 EPSG:3857:30 510772824 512651516 497203359 498380673 Precipitation Anomalies Oct_Nov_2016_(mm) - CHIRPS https://earlywarning.usgs.gov/fews/ewx/index.html?region=af -19.125063083055668 -35.37238257858172 52.6296893492118 38.256795423617206 MAPX:CHIRPS_Anomaly_2-Monthly_Oct-Nov_2016_(mm) image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 1 2 3 5 EPSG:4326:3 2 5 7 10 EPSG:4326:4 4 11 14 20 EPSG:4326:5 9 22 28 41 EPSG:4326:6 18 44 57 82 EPSG:4326:7 36 89 114 165 EPSG:4326:8 73 178 228 330 EPSG:4326:9 147 356 457 661 EPSG:4326:10 294 713 915 1323 EPSG:4326:11 588 1426 1830 2646 EPSG:4326:12 1177 2852 3660 5293 EPSG:4326:13 2354 5705 7321 10587 EPSG:4326:14 4709 11411 14643 21174 EPSG:4326:15 9419 22823 29286 42348 EPSG:4326:16 18839 45646 58572 84697 EPSG:4326:17 37678 91293 117145 169395 EPSG:4326:18 75356 182586 234291 338791 EPSG:4326:19 150713 365173 468582 677583 EPSG:4326:20 301426 730347 937164 1355166 EPSG:4326:21 602852 1460694 1874328 2710332 EPSG:900913 T56HKJ_20190927_843_QG 149.771202334192 -33.51085410265266 150.97478007537504 -32.49681353198739 wesr_swipe:T56HKJ_20190927_843_QG image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 76 117 117 EPSG:3857:8 152 153 234 235 EPSG:3857:9 304 306 469 470 EPSG:3857:10 609 613 938 941 EPSG:3857:11 1219 1226 1876 1882 EPSG:3857:12 2439 2453 3752 3765 EPSG:3857:13 4878 4906 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EPSG:4326:9 348 351 938 941 EPSG:4326:10 696 702 1876 1882 EPSG:4326:11 1393 1405 3752 3765 EPSG:4326:12 2787 2810 7504 7531 EPSG:4326:13 5574 5621 15008 15063 EPSG:4326:14 11149 11242 30016 30126 EPSG:4326:15 22299 22484 60033 60252 EPSG:4326:16 44599 44968 120066 120504 EPSG:4326:17 89199 89937 240132 241008 EPSG:4326:18 178398 179875 480264 482016 EPSG:4326:19 356797 359751 960528 964033 EPSG:4326:20 713595 719502 1921056 1928067 EPSG:4326:21 1427191 1439005 3842112 3856135 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 76 117 117 EPSG:3857:8 152 153 234 235 EPSG:3857:9 304 306 469 470 EPSG:3857:10 609 613 938 941 EPSG:3857:11 1219 1226 1876 1882 EPSG:3857:12 2439 2453 3752 3765 EPSG:3857:13 4878 4906 7504 7531 EPSG:3857:14 9757 9812 15008 15063 EPSG:3857:15 19514 19624 30016 30126 EPSG:3857:16 39029 39249 60033 60252 EPSG:3857:17 78058 78498 120066 120504 EPSG:3857:18 156116 156997 240132 241008 EPSG:3857:19 312233 313994 480264 482016 EPSG:3857:20 624467 627989 960528 964033 EPSG:3857:21 1248934 1255978 1921056 1928067 EPSG:3857:22 2497869 2511957 3842112 3856135 EPSG:3857:23 4995738 5023914 7684225 7712271 EPSG:3857:24 9991476 10047828 15368451 15424542 EPSG:3857:25 19982952 20095657 30736903 30849085 EPSG:3857:26 39965905 40191314 61473807 61698170 EPSG:3857:27 79931811 80382629 122947615 123396341 EPSG:3857:28 159863623 160765258 245895230 246792683 EPSG:3857:29 319727247 321530517 491790461 493585366 EPSG:3857:30 639454495 643061034 983580923 987170733 Yearly emissions of N2O - 1990 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -90.0 180.0 90.0 wesr_climat:v60_N2O_1990_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Yearly emissions of CO2 (excluding short cycle organic Carbon) - 1970 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -88.79999999998984 179.99999999997954 90.0 wesr_climat:v60_CO2_excl_short-cycle_org_C_1970_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 254 0 511 EPSG:4326:9 0 508 0 1023 EPSG:4326:10 0 1017 0 2047 EPSG:4326:11 0 2034 0 4095 EPSG:4326:12 0 4068 0 8191 EPSG:4326:13 0 8137 0 16383 EPSG:4326:14 0 16274 0 32767 EPSG:4326:15 0 32549 0 65535 EPSG:4326:16 0 65099 0 131071 EPSG:4326:17 0 130198 0 262143 EPSG:4326:18 0 260396 0 524287 EPSG:4326:19 0 520792 0 1048575 EPSG:4326:20 0 1041585 0 2097151 EPSG:4326:21 0 2083170 0 4194303 EPSG:900913 EPSG:3857_512 Recurrence map of burned areas between 1995 and 2024 The combined burned area map shows the recurrence of wildfires throughout the study period. It allows for the identification of fire "hotspots, " i.e., areas where fires recur chronically. This map identifies three levels of recurrence: areas burned at least once during one of the periods, areas burned at least once during two separate periods, and areas burned at least once during each study period. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:burn image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491251 EPSG:4326:20 445870 452589 971450 982502 EPSG:4326:21 891741 905179 1942901 1965005 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 Multi Hazards Mortality Risk This dataset includes an estimate of the global risk induced by multiple hazards (tropical cyclone, flood and landslide induced by precipitations). Unit is estimated risk index from 1 (low) to 5 (extreme). This product was designed by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: UNEP/GRID-Europe. -180.0 -90.0 179.99999999985602 83.99999999993042 wesr_risk:ml_risk image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097151 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388608 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217727 EPSG:3857:28 8240909 268435455 0 268435456 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34952 1048575 0 2097151 EPSG:4326:21 69905 2097151 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097152 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388607 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217728 EPSG:3857:28 8240909 268435455 0 268435455 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741824 afg_flood_mortality_risk 68.249999901 35.49999995 75.166666565 39.833333281 afg_transboundary:afg_flood_mortality_risk image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 11 11 EPSG:3857:5 12 12 22 22 EPSG:3857:6 24 25 44 45 EPSG:3857:7 48 50 88 90 EPSG:3857:8 97 100 176 181 EPSG:3857:9 194 201 353 362 EPSG:3857:10 388 403 706 725 EPSG:3857:11 776 807 1412 1451 EPSG:3857:12 1553 1615 2824 2903 EPSG:3857:13 3106 3230 5649 5806 EPSG:3857:14 6212 6461 11298 11612 EPSG:3857:15 12425 12923 22596 23225 EPSG:3857:16 24850 25847 45192 46451 EPSG:3857:17 49700 51694 90385 92903 EPSG:3857:18 99400 103388 180770 185806 EPSG:3857:19 198800 206777 361540 371613 EPSG:3857:20 397601 413555 723080 743226 EPSG:3857:21 795203 827110 1446161 1486453 EPSG:3857:22 1590407 1654221 2892322 2972907 EPSG:3857:23 3180815 3308442 5784644 5945814 EPSG:3857:24 6361631 6616885 11569288 11891628 EPSG:3857:25 12723262 13233770 23138577 23783257 EPSG:3857:26 25446525 26467540 46277154 47566514 EPSG:3857:27 50893050 52935081 92554308 95133028 EPSG:3857:28 101786101 105870162 185108616 190266056 EPSG:3857:29 203572203 211740324 370217232 380532113 EPSG:3857:30 407144407 423480648 740434465 761064227 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 2 2 11 11 EPSG:4326:4 4 4 22 22 EPSG:4326:5 8 9 44 45 EPSG:4326:6 17 19 88 90 EPSG:4326:7 35 38 176 181 EPSG:4326:8 71 77 353 362 EPSG:4326:9 142 155 706 725 EPSG:4326:10 285 310 1412 1451 EPSG:4326:11 570 620 2824 2903 EPSG:4326:12 1141 1240 5649 5806 EPSG:4326:13 2283 2480 11298 11612 EPSG:4326:14 4566 4960 22596 23225 EPSG:4326:15 9132 9921 45192 46451 EPSG:4326:16 18265 19842 90385 92903 EPSG:4326:17 36530 39685 180770 185806 EPSG:4326:18 73060 79371 361540 371613 EPSG:4326:19 146121 158742 723080 743226 EPSG:4326:20 292242 317485 1446161 1486453 EPSG:4326:21 584484 634971 2892322 2972907 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 11 11 EPSG:3857:5 12 12 22 22 EPSG:3857:6 24 25 44 45 EPSG:3857:7 48 50 88 90 EPSG:3857:8 97 100 176 181 EPSG:3857:9 194 201 353 362 EPSG:3857:10 388 403 706 725 EPSG:3857:11 776 807 1412 1451 EPSG:3857:12 1553 1615 2824 2903 EPSG:3857:13 3106 3230 5649 5806 EPSG:3857:14 6212 6461 11298 11612 EPSG:3857:15 12425 12923 22596 23225 EPSG:3857:16 24850 25847 45192 46451 EPSG:3857:17 49700 51694 90385 92903 EPSG:3857:18 99400 103388 180770 185806 EPSG:3857:19 198800 206777 361540 371613 EPSG:3857:20 397601 413555 723080 743226 EPSG:3857:21 795203 827110 1446161 1486453 EPSG:3857:22 1590407 1654221 2892322 2972907 EPSG:3857:23 3180815 3308442 5784644 5945814 EPSG:3857:24 6361631 6616885 11569288 11891628 EPSG:3857:25 12723262 13233770 23138577 23783257 EPSG:3857:26 25446525 26467540 46277154 47566514 EPSG:3857:27 50893050 52935081 92554308 95133028 EPSG:3857:28 101786101 105870162 185108616 190266056 EPSG:3857:29 203572203 211740324 370217232 380532113 EPSG:3857:30 407144407 423480648 740434465 761064227 Automn temperature change (°C) for the period 2080 - 2099 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_son_ENDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 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62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 samericaFI3 -81.70902543656312 -20.630653749343182 -34.24694876580037 13.092434648616072 MapX_UNDP:samericaFI3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 3 EPSG:3857:4 7 8 4 6 EPSG:3857:5 14 17 8 12 EPSG:3857:6 29 35 17 25 EPSG:3857:7 59 71 34 51 EPSG:3857:8 118 142 69 103 EPSG:3857:9 237 285 139 207 EPSG:3857:10 474 571 279 414 EPSG:3857:11 948 1143 559 829 EPSG:3857:12 1897 2287 1118 1658 EPSG:3857:13 3795 4575 2236 3316 EPSG:3857:14 7590 9151 4473 6633 EPSG:3857:15 15181 18303 8946 13266 EPSG:3857:16 30363 36607 17893 26533 EPSG:3857:17 60727 73215 35786 53067 EPSG:3857:18 121454 146430 71573 106134 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4685770 2290345 3396292 EPSG:3857:24 7773076 9371541 4580691 6792584 EPSG:3857:25 15546152 18743083 9161382 13585169 EPSG:3857:26 31092304 37486167 18322765 27170338 EPSG:3857:27 62184608 74972335 36645531 54340676 EPSG:3857:28 124369217 149944670 73291062 108681352 EPSG:3857:29 248738434 299889341 146582125 217362704 EPSG:3857:30 497476869 599778682 293164250 434725408 Forest Integrity Index (FI) - South America The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> -81.70875583396088 -20.582447168229265 -34.24721833519705 13.047396176983916 MapX_UNDP:samericaFI2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 3 EPSG:3857:4 7 8 4 6 EPSG:3857:5 14 17 8 12 EPSG:3857:6 29 35 17 25 EPSG:3857:7 59 71 34 51 EPSG:3857:8 118 142 69 103 EPSG:3857:9 237 285 139 207 EPSG:3857:10 474 571 279 414 EPSG:3857:11 949 1143 559 829 EPSG:3857:12 1898 2287 1118 1658 EPSG:3857:13 3796 4574 2236 3316 EPSG:3857:14 7592 9149 4473 6633 EPSG:3857:15 15185 18299 8946 13266 EPSG:3857:16 30371 36598 17893 26533 EPSG:3857:17 60743 73196 35786 53066 EPSG:3857:18 121487 146392 71573 106133 EPSG:3857:19 242975 292785 143146 212267 EPSG:3857:20 485951 585571 286293 424535 EPSG:3857:21 971903 1171142 572587 849071 EPSG:3857:22 1943807 2342285 1145175 1698142 EPSG:3857:23 3887615 4684570 2290351 3396285 EPSG:3857:24 7775230 9369141 4580703 6792571 EPSG:3857:25 15550461 18738283 9161407 13585143 EPSG:3857:26 31100923 37476567 18322815 27170287 EPSG:3857:27 62201846 74953134 36645631 54340575 EPSG:3857:28 124403693 149906268 73291263 108681151 EPSG:3857:29 248807387 299812536 146582527 217362302 EPSG:3857:30 497614774 599625072 293165054 434724604 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 1 1 1 EPSG:4326:2 1 2 2 3 EPSG:4326:3 3 4 4 6 EPSG:4326:4 6 9 8 12 EPSG:4326:5 13 19 17 25 EPSG:4326:6 27 39 34 51 EPSG:4326:7 54 78 69 103 EPSG:4326:8 109 157 139 207 EPSG:4326:9 218 314 279 414 EPSG:4326:10 437 629 559 829 EPSG:4326:11 875 1258 1118 1658 EPSG:4326:12 1751 2516 2236 3316 EPSG:4326:13 3502 5032 4473 6633 EPSG:4326:14 7004 10065 8946 13266 EPSG:4326:15 14008 20130 17893 26533 EPSG:4326:16 28017 40261 35786 53066 EPSG:4326:17 56035 80523 71573 106133 EPSG:4326:18 112070 161047 143146 212267 EPSG:4326:19 224140 322094 286293 424535 EPSG:4326:20 448281 644189 572587 849071 EPSG:4326:21 896562 1288378 1145175 1698142 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 3 EPSG:3857:4 7 8 4 6 EPSG:3857:5 14 17 8 12 EPSG:3857:6 29 35 17 25 EPSG:3857:7 59 71 34 51 EPSG:3857:8 118 142 69 103 EPSG:3857:9 237 285 139 207 EPSG:3857:10 474 571 279 414 EPSG:3857:11 949 1143 559 829 EPSG:3857:12 1898 2287 1118 1658 EPSG:3857:13 3796 4574 2236 3316 EPSG:3857:14 7592 9149 4473 6633 EPSG:3857:15 15185 18299 8946 13266 EPSG:3857:16 30371 36598 17893 26533 EPSG:3857:17 60743 73196 35786 53066 EPSG:3857:18 121487 146392 71573 106133 EPSG:3857:19 242975 292785 143146 212267 EPSG:3857:20 485951 585571 286293 424535 EPSG:3857:21 971903 1171142 572587 849071 EPSG:3857:22 1943807 2342285 1145175 1698142 EPSG:3857:23 3887615 4684570 2290351 3396285 EPSG:3857:24 7775230 9369141 4580703 6792571 EPSG:3857:25 15550461 18738283 9161407 13585143 EPSG:3857:26 31100923 37476567 18322815 27170287 EPSG:3857:27 62201846 74953134 36645631 54340575 EPSG:3857:28 124403693 149906268 73291263 108681151 EPSG:3857:29 248807387 299812536 146582527 217362302 EPSG:3857:30 497614774 599625072 293165054 434724604 Tropical Cyclone Wind 100 Years Return Period (km/h) The tropical cyclonic strong wind and storm surge hazard model uses information from 2594 historical tropical cyclones besides data on topography, terrain roughness, and bathymetry. The historical tropical cyclones used in the cyclone wind and storm surge hazard model for the GAR Atlas cover the five different oceanic basins: Northeast Pacific, Northwest Pacific, South Pacific, North Indian, South Indian and North Atlantic. In all cases, the data associated to each track were obtained from the IBTrACS database (Knapp et al., 2010). Topography data from the Shuttle Radar Topography Mission (SRTM) of NASA, which provides terrain elevation grids at a 90 meters resolution, delivered by quadrants over the world was used and, additionally, to account for surface roughness, polygons of urban areas worldwide were obtained from the Socioeconomic Data and Applications Centre, SEDAC (CIESIN et al., 2011). A digital bathymetry model, with a spatial resolution of 30 arc-seconds, from the GEBCO_08 (General Bathymetric Chart of the Oceans) Grid Database of the British Oceanographic Data Centre (2009) was used. More information about the cyclone wind and storm surge hazard model can be found in Cardona et al., 2015. Hazard analysis was performed using the software CAPRA Team Tropical Cyclones Hazard Modeler (Bernal, 2014). -180.0 -55.13566066745048 179.9077507461337 59.904585330559826 wesr_risk:cy_hazard_100_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 0 15 EPSG:4326:4 2 12 0 31 EPSG:4326:5 5 25 0 63 EPSG:4326:6 10 51 0 127 EPSG:4326:7 21 103 0 255 EPSG:4326:8 42 206 0 511 EPSG:4326:9 85 412 0 1023 EPSG:4326:10 171 825 0 2047 EPSG:4326:11 342 1651 0 4094 EPSG:4326:12 684 3302 0 8189 EPSG:4326:13 1369 6605 0 16379 EPSG:4326:14 2739 13210 0 32759 EPSG:4326:15 5478 26421 0 65519 EPSG:4326:16 10957 52842 0 131038 EPSG:4326:17 21914 105684 0 262076 EPSG:4326:18 43829 211369 0 524153 EPSG:4326:19 87659 422738 0 1048307 EPSG:4326:20 175318 845476 0 2096614 EPSG:4326:21 350636 1690953 0 4193229 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 Combination Tropical cyclone surge/ Mangroves at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_man9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from NOAA Geophysical Fluid Dynamics Laboratory, CM2.1 Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_gfdl_cm2_1_5km_2041-2060_debiasedmean_tas_av_12m_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Satellite Mogadisho Urban Growth 2012 Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2012-01-18. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov. 45.195394649846214 1.955229029551538 45.47923060483454 2.141476613353127 MAPX:Mogadisho_Landsat7_20120118-531 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 10 10 EPSG:3857:5 15 15 20 20 EPSG:3857:6 31 31 40 40 EPSG:3857:7 63 63 80 80 EPSG:3857:8 126 126 160 160 EPSG:3857:9 252 253 320 320 EPSG:3857:10 505 506 640 641 EPSG:3857:11 1011 1012 1281 1282 EPSG:3857:12 2023 2025 2562 2565 EPSG:3857:13 4047 4051 5124 5130 EPSG:3857:14 8094 8102 10248 10261 EPSG:3857:15 16189 16205 20497 20523 EPSG:3857:16 32378 32411 40995 41047 EPSG:3857:17 64756 64823 81991 82094 EPSG:3857:18 129512 129647 163982 164188 EPSG:3857:19 259024 259295 327964 328377 EPSG:3857:20 518049 518591 655929 656755 EPSG:3857:21 1036098 1037183 1311858 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EPSG:4326:16 16199 21749 63586 78634 EPSG:4326:17 32398 43498 127172 157269 EPSG:4326:18 64797 86996 254344 314539 EPSG:4326:19 129595 173992 508689 629078 EPSG:4326:20 259190 347984 1017378 1258157 EPSG:4326:21 518380 695968 2034756 2516315 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 31 38 EPSG:3857:7 45 52 62 76 EPSG:3857:8 91 105 124 153 EPSG:3857:9 183 210 248 307 EPSG:3857:10 366 421 496 614 EPSG:3857:11 732 843 993 1228 EPSG:3857:12 1465 1686 1987 2457 EPSG:3857:13 2930 3372 3974 4914 EPSG:3857:14 5860 6745 7948 9829 EPSG:3857:15 11721 13491 15896 19658 EPSG:3857:16 23443 26982 31793 39317 EPSG:3857:17 46887 53965 63586 78634 EPSG:3857:18 93775 107931 127172 157269 EPSG:3857:19 187550 215862 254344 314539 EPSG:3857:20 375100 431725 508689 629078 EPSG:3857:21 750201 863450 1017378 1258157 EPSG:3857:22 1500403 1726901 2034756 2516315 EPSG:3857:23 3000807 3453803 4069513 5032630 EPSG:3857:24 6001615 6907606 8139027 10065261 EPSG:3857:25 12003230 13815212 16278055 20130523 EPSG:3857:26 24006460 27630425 32556110 40261046 EPSG:3857:27 48012920 55260850 65112220 80522092 EPSG:3857:28 96025840 110521701 130224440 161044185 EPSG:3857:29 192051680 221043403 260448880 322088371 EPSG:3857:30 384103360 442086806 520897760 644176743 Self-calibrating Palmer Drought Severity Index (scPDSI) 2021-2022 (CRU) This layer shows the average values over the 2021 to 2022 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_21_22_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 20190927_843_QG_mos 149.66386433258654 -36.214355797728665 150.97478007537504 -32.49681353198739 wesr_swipe:20190927_843_QG image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 152 155 234 235 EPSG:3857:9 304 311 468 470 EPSG:3857:10 609 622 937 941 EPSG:3857:11 1219 1245 1875 1882 EPSG:3857:12 2439 2490 3750 3765 EPSG:3857:13 4878 4981 7501 7531 EPSG:3857:14 9757 9962 15003 15063 EPSG:3857:15 19514 19924 30006 30126 EPSG:3857:16 39029 39849 60013 60252 EPSG:3857:17 78058 79698 120026 120504 EPSG:3857:18 156116 159396 240053 241008 EPSG:3857:19 312233 318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 EPSG:3857:22 2497869 2550351 3840862 3856135 EPSG:3857:23 4995738 5100703 7681724 7712271 EPSG:3857:24 9991476 10201407 15363449 15424542 EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 3 3 EPSG:4326:2 2 2 7 7 EPSG:4326:3 5 5 14 14 EPSG:4326:4 10 11 29 29 EPSG:4326:5 21 22 58 58 EPSG:4326:6 43 44 117 117 EPSG:4326:7 87 89 234 235 EPSG:4326:8 174 179 468 470 EPSG:4326:9 348 359 937 941 EPSG:4326:10 696 718 1875 1882 EPSG:4326:11 1393 1436 3750 3765 EPSG:4326:12 2787 2872 7501 7531 EPSG:4326:13 5574 5744 15003 15063 EPSG:4326:14 11149 11488 30006 30126 EPSG:4326:15 22299 22976 60013 60252 EPSG:4326:16 44599 45953 120026 120504 EPSG:4326:17 89199 91906 240053 241008 EPSG:4326:18 178398 183812 480107 482016 EPSG:4326:19 356797 367625 960215 964033 EPSG:4326:20 713595 735251 1920431 1928067 EPSG:4326:21 1427191 1470503 3840862 3856135 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 152 155 234 235 EPSG:3857:9 304 311 468 470 EPSG:3857:10 609 622 937 941 EPSG:3857:11 1219 1245 1875 1882 EPSG:3857:12 2439 2490 3750 3765 EPSG:3857:13 4878 4981 7501 7531 EPSG:3857:14 9757 9962 15003 15063 EPSG:3857:15 19514 19924 30006 30126 EPSG:3857:16 39029 39849 60013 60252 EPSG:3857:17 78058 79698 120026 120504 EPSG:3857:18 156116 159396 240053 241008 EPSG:3857:19 312233 318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 EPSG:3857:22 2497869 2550351 3840862 3856135 EPSG:3857:23 4995738 5100703 7681724 7712271 EPSG:3857:24 9991476 10201407 15363449 15424542 EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 Organic Pollution (pesticides) 2013 - KNB Pesticides were used as a proxy measure for organic pollution. Input data are from 2007-2010 FAO statistics, the most recent available. Missing pesticide values were filled using a linear regression model of pesticides as a function of fertilizers (gaps: N=69; regression: R2 = 0.72) when fertilizer data were available or agricultural GDP (gaps: N=22; regression: R2 = 0.82) when not. These country-level average pesticides values were then dasymetrically distributed over a country’s landscape using global land cover data from 2009, derived from the Moderate Resolution imaging Spectroradiometer (MODIS) instrument at ~500m resolution. Finally, spread of the driver values into coastal waters at each pour point was modelled with a cost-path surface on the basis of a decay function that assigns a fixed amount of the driver (0.5% of the value in the previous cell) in the initial cell and then evenly distributes the remaining amount of driver in all adjacent and ‘unvisited’ cells, repeated until a minimum threshold (0.05% of global maximum) is reached. This approach to modelling river plumes is diffusive and so allows drivers to wrap around headlands and islands. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS." -179.99999869409874 -57.96420981377538 179.9994455075789 84.9958245860871 unea_pollution:13_plumes_pest_halpern_KNB_WGS84 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 44 0 63 EPSG:3857:7 0 89 0 127 EPSG:3857:8 0 178 0 255 EPSG:3857:9 0 357 0 511 EPSG:3857:10 1 715 0 1023 EPSG:3857:11 3 1430 0 2047 EPSG:3857:12 7 2861 0 4095 EPSG:3857:13 14 5723 0 8191 EPSG:3857:14 29 11446 0 16383 EPSG:3857:15 58 22892 0 32767 EPSG:3857:16 116 45784 0 65535 EPSG:3857:17 232 91569 0 131071 EPSG:3857:18 464 183139 0 262143 EPSG:3857:19 928 366279 0 524287 EPSG:3857:20 1856 732558 0 1048574 EPSG:3857:21 3713 1465117 0 2097148 EPSG:3857:22 7427 2930235 0 4194297 EPSG:3857:23 14855 5860470 0 8388595 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71977191 76111966 EPSG:3857:28 116156768 128674502 143954382 152223933 EPSG:3857:29 232313536 257349005 287908765 304447867 EPSG:3857:30 464627073 514698010 575817530 608895734 20190927_843_grass_mos 149.66386433258654 -36.214355797728665 150.97478007537504 -32.49681353198739 wesr_swipe:20190927_843 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 152 155 234 235 EPSG:3857:9 304 311 468 470 EPSG:3857:10 609 622 937 941 EPSG:3857:11 1219 1245 1875 1882 EPSG:3857:12 2439 2490 3750 3765 EPSG:3857:13 4878 4981 7501 7531 EPSG:3857:14 9757 9962 15003 15063 EPSG:3857:15 19514 19924 30006 30126 EPSG:3857:16 39029 39849 60013 60252 EPSG:3857:17 78058 79698 120026 120504 EPSG:3857:18 156116 159396 240053 241008 EPSG:3857:19 312233 318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 EPSG:3857:22 2497869 2550351 3840862 3856135 EPSG:3857:23 4995738 5100703 7681724 7712271 EPSG:3857:24 9991476 10201407 15363449 15424542 EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 3 3 EPSG:4326:2 2 2 7 7 EPSG:4326:3 5 5 14 14 EPSG:4326:4 10 11 29 29 EPSG:4326:5 21 22 58 58 EPSG:4326:6 43 44 117 117 EPSG:4326:7 87 89 234 235 EPSG:4326:8 174 179 468 470 EPSG:4326:9 348 359 937 941 EPSG:4326:10 696 718 1875 1882 EPSG:4326:11 1393 1436 3750 3765 EPSG:4326:12 2787 2872 7501 7531 EPSG:4326:13 5574 5744 15003 15063 EPSG:4326:14 11149 11488 30006 30126 EPSG:4326:15 22299 22976 60013 60252 EPSG:4326:16 44599 45953 120026 120504 EPSG:4326:17 89199 91906 240053 241008 EPSG:4326:18 178398 183812 480107 482016 EPSG:4326:19 356797 367625 960215 964033 EPSG:4326:20 713595 735251 1920431 1928067 EPSG:4326:21 1427191 1470503 3840862 3856135 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 152 155 234 235 EPSG:3857:9 304 311 468 470 EPSG:3857:10 609 622 937 941 EPSG:3857:11 1219 1245 1875 1882 EPSG:3857:12 2439 2490 3750 3765 EPSG:3857:13 4878 4981 7501 7531 EPSG:3857:14 9757 9962 15003 15063 EPSG:3857:15 19514 19924 30006 30126 EPSG:3857:16 39029 39849 60013 60252 EPSG:3857:17 78058 79698 120026 120504 EPSG:3857:18 156116 159396 240053 241008 EPSG:3857:19 312233 318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 EPSG:3857:22 2497869 2550351 3840862 3856135 EPSG:3857:23 4995738 5100703 7681724 7712271 EPSG:3857:24 9991476 10201407 15363449 15424542 EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 Year precipitations 2012 - Central African Republic Total precipitations observed in 2012 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2012_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Global protected marine areas: IUCN categories IUCN protected area management categories classify protected areas according to their management objectives. The categories are recognised by international bodies such as the United Nations and by many national governments as the global standard for defining and recording protected areas and as such are increasingly being incorporated into government legislation -179.99998853999992 -63.99999999999994 179.99999706000008 83.73332742400007 unea_pollution_nd:prot_marine_iucn image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 27 0 63 EPSG:4326:6 2 54 0 127 EPSG:4326:7 4 109 0 255 EPSG:4326:8 8 219 0 511 EPSG:4326:9 17 438 0 1023 EPSG:4326:10 35 876 0 2047 EPSG:4326:11 71 1752 0 4095 EPSG:4326:12 142 3504 0 8191 EPSG:4326:13 285 7008 0 16383 EPSG:4326:14 570 14017 0 32767 EPSG:4326:15 1140 28034 0 65535 EPSG:4326:16 2281 56069 0 131071 EPSG:4326:17 4563 112139 0 262143 EPSG:4326:18 9126 224278 0 524287 EPSG:4326:19 18253 448557 0 1048575 EPSG:4326:20 36506 897115 0 2097151 EPSG:4326:21 73012 1794230 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 1 23 0 31 EPSG:900913:6 2 46 0 63 EPSG:900913:7 4 93 0 127 EPSG:900913:8 9 187 0 255 EPSG:900913:9 19 375 0 511 EPSG:900913:10 38 750 0 1023 EPSG:900913:11 77 1501 0 2047 EPSG:900913:12 154 3003 0 4095 EPSG:900913:13 308 6007 0 8191 EPSG:900913:14 616 12014 0 16383 EPSG:900913:15 1233 24028 0 32767 EPSG:900913:16 2466 48057 0 65535 EPSG:900913:17 4932 96115 0 131071 EPSG:900913:18 9865 192231 0 262143 EPSG:900913:19 19731 384463 0 524287 EPSG:900913:20 39462 768927 0 1048575 EPSG:900913:21 78924 1537855 0 2097151 EPSG:900913:22 157848 3075710 0 4194303 EPSG:900913:23 315697 6151421 0 8388607 EPSG:900913:24 631394 12302842 0 16777215 EPSG:900913:25 1262788 24605685 1 33554431 EPSG:900913:26 2525577 49211370 2 67108863 EPSG:900913:27 5051154 98422740 4 134217726 EPSG:900913:28 10102309 196845480 8 268435453 EPSG:900913:29 20204618 393690960 17 536870907 EPSG:900913:30 40409237 787381920 34 1073741815 Climate Exposure The map displays total exposure to climate at province level scale using the first administrative division polygon files from the Global Administrative Areas database version 2.8. The map retains the five exposure categories of low to high exposure (1 to 5) based on the k-median clustering algorithm. The median climate exposure score for each administrative division is determined with spatial analysis in ArcGIS. These median scores are then clustered into five categories of low to high exposure using the k-median algorithm contained in Stata. The climate exposure portion of this study aims to identify places most likely vulnerable to a combination of climate hazards. Geographic location makes some countries more susceptible to climate hazards. Within countries, some areas, such as the coasts, have more exposure to certain kinds of climate hazards. This study assesses climate hazard exposure using historical data on the frequency and magnitude of six hazards, including cyclones, flood events, wildfire events, rainfall anomalies, and chronic aridity. The sixth hazard is a measure of low-elevation coastal zones, which may be susceptible to storm surges and future sea-level rise. The goal is to identify places that in the recent historical record have faced high exposure to climaterelated hazards. This seeks to get a snapshot of places of chronic concern over a long enough time period to say that these are places that have been historically affected by climate-related hazards. The indicators included here use the most recent data available. Some of these indicators, like cyclones, have longerterm data available, while others like floods have data for fewer years. In all cases, this project uses the most recent and broadest set of years for which global data are available to get the best snapshot of climate exposure in the recent past, as close as possible to the present. This <a href="https://pdf.usaid.gov/pdf_docs/PA00TBFH.pdf"target=_blank>document</a> outlines the process of mapping individual climate hazards, the rationale for including particular indicators, and the process of calculating total climate exposure. -179.99999999999994 -90.0 180.0 83.65833282470703 UN_Sahel:USAID_CMM_exp_0-001_v image/png image/vnd.jpeg-png image/jpeg image/png8 EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 40 1023 0 1023 EPSG:3857:11 80 2047 0 2047 EPSG:3857:12 161 4095 0 4095 EPSG:3857:13 323 8191 0 8191 EPSG:3857:14 647 16383 0 16383 EPSG:3857:15 1295 32767 0 32767 EPSG:3857:16 2590 65535 0 65535 EPSG:3857:17 5181 131071 0 131071 EPSG:3857:18 10362 262143 0 262143 EPSG:3857:19 20725 524287 0 524287 EPSG:3857:20 41451 1048575 0 1048575 EPSG:3857:21 82902 2097151 0 2097151 EPSG:3857:22 165805 4194303 0 4194304 EPSG:3857:23 331611 8388607 0 8388608 EPSG:3857:24 663223 16777215 0 16777215 EPSG:3857:25 1326446 33554431 0 33554431 EPSG:3857:26 2652893 67108863 0 67108863 EPSG:3857:27 5305787 134217727 0 134217727 EPSG:3857:28 10611574 268435455 0 268435456 EPSG:3857:29 21223148 536870911 0 536870911 EPSG:3857:30 42446297 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 9 255 0 511 EPSG:4326:9 18 511 0 1023 EPSG:4326:10 36 1023 0 2047 EPSG:4326:11 72 2047 0 4095 EPSG:4326:12 144 4095 0 8191 EPSG:4326:13 288 8191 0 16383 EPSG:4326:14 577 16383 0 32767 EPSG:4326:15 1154 32767 0 65535 EPSG:4326:16 2308 65535 0 131071 EPSG:4326:17 4617 131071 0 262143 EPSG:4326:18 9235 262143 0 524287 EPSG:4326:19 18471 524287 0 1048575 EPSG:4326:20 36942 1048575 0 2097151 EPSG:4326:21 73885 2097151 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 1 31 0 31 EPSG:900913:6 2 63 0 63 EPSG:900913:7 5 127 0 127 EPSG:900913:8 10 255 0 255 EPSG:900913:9 20 511 0 511 EPSG:900913:10 40 1023 0 1023 EPSG:900913:11 80 2047 0 2047 EPSG:900913:12 161 4095 0 4095 EPSG:900913:13 323 8191 0 8191 EPSG:900913:14 647 16383 0 16383 EPSG:900913:15 1295 32767 0 32767 EPSG:900913:16 2590 65535 0 65535 EPSG:900913:17 5181 131071 0 131071 EPSG:900913:18 10362 262143 0 262143 EPSG:900913:19 20725 524287 0 524287 EPSG:900913:20 41451 1048575 0 1048575 EPSG:900913:21 82902 2097151 0 2097151 EPSG:900913:22 165805 4194303 0 4194303 EPSG:900913:23 331611 8388607 0 8388607 EPSG:900913:24 663223 16777215 0 16777215 EPSG:900913:25 1326446 33554431 0 33554431 EPSG:900913:26 2652893 67108863 0 67108863 EPSG:900913:27 5305787 134217727 0 134217727 EPSG:900913:28 10611574 268435455 0 268435455 EPSG:900913:29 21223148 536870911 0 536870911 EPSG:900913:30 42446297 1073741823 0 1073741823 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 40 1023 0 1023 EPSG:3857:11 80 2047 0 2047 EPSG:3857:12 161 4095 0 4095 EPSG:3857:13 323 8191 0 8191 EPSG:3857:14 647 16383 0 16383 EPSG:3857:15 1295 32767 0 32767 EPSG:3857:16 2590 65535 0 65535 EPSG:3857:17 5181 131071 0 131071 EPSG:3857:18 10362 262143 0 262143 EPSG:3857:19 20725 524287 0 524287 EPSG:3857:20 41451 1048575 0 1048575 EPSG:3857:21 82902 2097151 0 2097152 EPSG:3857:22 165805 4194303 0 4194304 EPSG:3857:23 331611 8388607 0 8388607 EPSG:3857:24 663223 16777215 0 16777215 EPSG:3857:25 1326446 33554431 0 33554431 EPSG:3857:26 2652893 67108863 0 67108863 EPSG:3857:27 5305787 134217727 0 134217728 EPSG:3857:28 10611574 268435455 0 268435455 EPSG:3857:29 21223148 536870911 0 536870911 EPSG:3857:30 42446297 1073741823 0 1073741824 Active Fires Frequency (2003 - 2025) Raster of Active Fires frequency per square kilometer, based on MODIS Collection 6 Active Fire Product MCD14ML. Only location points described as "presumed vegetation fire" in the attributes are included in the frequency calculation. <br> This layer was produced by UNEP/GRID-Geneva. -180.0 -90.0 180.0 90.0 wesr_risk:fires_density_total image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 ethiopia_remote_site_screening_res50 32.99994 3.4043378313011186 47.94344 14.869337831301118 mapx_chemobs:ethiopia_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 5 EPSG:3857:4 7 7 9 10 EPSG:3857:5 14 15 18 20 EPSG:3857:6 29 31 37 40 EPSG:3857:7 58 62 75 81 EPSG:3857:8 117 125 151 162 EPSG:3857:9 234 251 302 324 EPSG:3857:10 469 502 605 648 EPSG:3857:11 938 1004 1211 1296 EPSG:3857:12 1876 2009 2423 2593 EPSG:3857:13 3753 4018 4846 5186 EPSG:3857:14 7507 8036 9693 10373 EPSG:3857:15 15015 16073 19387 20747 EPSG:3857:16 30030 32147 38775 41495 EPSG:3857:17 60060 64295 77550 82991 EPSG:3857:18 120120 128591 155101 165983 EPSG:3857:19 240241 257183 310203 331966 EPSG:3857:20 480483 514366 620407 663933 EPSG:3857:21 960966 1028732 1240814 1327866 EPSG:3857:22 1921933 2057465 2481629 2655733 EPSG:3857:23 3843867 4114930 4963258 5311467 EPSG:3857:24 7687734 8229860 9926516 10622934 EPSG:3857:25 15375469 16459721 19853033 21245868 EPSG:3857:26 30750938 32919443 39706066 42491736 EPSG:3857:27 61501876 65838887 79412133 84983473 EPSG:3857:28 123003752 131677774 158824266 169966947 EPSG:3857:29 246007505 263355549 317648533 339933895 EPSG:3857:30 492015010 526711099 635297066 679867791 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 5 EPSG:4326:3 3 3 9 10 EPSG:4326:4 6 7 18 20 EPSG:4326:5 13 15 37 40 EPSG:4326:6 26 30 75 81 EPSG:4326:7 53 61 151 162 EPSG:4326:8 106 123 302 324 EPSG:4326:9 213 246 605 648 EPSG:4326:10 427 492 1211 1296 EPSG:4326:11 854 985 2423 2593 EPSG:4326:12 1709 1970 4846 5186 EPSG:4326:13 3419 3941 9693 10373 EPSG:4326:14 6838 7882 19387 20747 EPSG:4326:15 13677 15764 38775 41495 EPSG:4326:16 27354 31528 77550 82991 EPSG:4326:17 54708 63057 155101 165983 EPSG:4326:18 109416 126114 310203 331966 EPSG:4326:19 218833 252228 620407 663933 EPSG:4326:20 437667 504456 1240814 1327866 EPSG:4326:21 875335 1008912 2481629 2655733 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 5 EPSG:3857:4 7 7 9 10 EPSG:3857:5 14 15 18 20 EPSG:3857:6 29 31 37 40 EPSG:3857:7 58 62 75 81 EPSG:3857:8 117 125 151 162 EPSG:3857:9 234 251 302 324 EPSG:3857:10 469 502 605 648 EPSG:3857:11 938 1004 1211 1296 EPSG:3857:12 1876 2009 2423 2593 EPSG:3857:13 3753 4018 4846 5186 EPSG:3857:14 7507 8036 9693 10373 EPSG:3857:15 15015 16073 19387 20747 EPSG:3857:16 30030 32147 38775 41495 EPSG:3857:17 60060 64295 77550 82991 EPSG:3857:18 120120 128591 155101 165983 EPSG:3857:19 240241 257183 310203 331966 EPSG:3857:20 480483 514366 620407 663933 EPSG:3857:21 960966 1028732 1240814 1327866 EPSG:3857:22 1921933 2057465 2481629 2655733 EPSG:3857:23 3843867 4114930 4963258 5311467 EPSG:3857:24 7687734 8229860 9926516 10622934 EPSG:3857:25 15375469 16459721 19853033 21245868 EPSG:3857:26 30750938 32919443 39706066 42491736 EPSG:3857:27 61501876 65838887 79412133 84983473 EPSG:3857:28 123003752 131677774 158824266 169966947 EPSG:3857:29 246007505 263355549 317648533 339933895 EPSG:3857:30 492015010 526711099 635297066 679867791 Global Land Cover -2015 v2.0.7 The Climate Change Initiative (CCI) Land Cover (LC) project of the European Space Agency (ESA) delivers consistent global LC maps at 300 m spatial resolution on an annual basis from 1992 to 2015. Each pixel value corresponds to the label of a land cover class defined based on the UN Land Cover Classification System (LCCS). UN Biodiversity Lab shows only the data for year 2015.<br><br>For further information or to download the full dataset please visit the: <a href="http://maps.elie.ucl.ac.be/CCI/viewer/">European Space Agency Climate Change Innitiative</a>.<br><br>Citation: European Space Agency Climate Change Initiative, Land Cover project. 2017. 300m Annual Global Land Cover Time Series from 1992 to 2015. Retrieved from http://maps.elie.ucl.ac.be/CCI/viewer/. Accessed through UN Biodiversity Lab, (date). www.unbiodiversitylab.org. -180.0 -90.0 180.0 90.0 MapX_UNDP:ESACCI-LC-L4-LCCS-Map-300m-P1Y-1992_2015-v2.0.7_2015 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Cumulative Impact - Sum of Pressure Data 2013 - KNB This is the cumulative human impact based on raw stressors for the year 2013 (Halpern et al. 2015. Spatial and temporal changes in cumulative human impacts on the world's ocean.). The cumulative human impact for the year 2013 is the sum of all normalized stressor data adjusted for habitat/pressure vulnerability. List of stressor data: artisanal_fishing, demersal_destructive_fishing, demersal_nondest_high_bycatch, demersal_nondest_low_bycatch, inorganic, invasives, night_lights, ocean_acidification, ocean_pollution, oil_rigs, pelagic_high_bycatch, pelagic_low_bycatch, plumes_fert, plumes_pest, population, shipping, slr, sst, uv. Cumulative human impact from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: pressure and cumulative impacts data (2013, all pressures). Knowledge Network for Biocomplexity. doi:10.5063/F15718ZN." -179.99999978928923 -89.99765318081656 179.99802237904845 85.28467978960619 unea_pollution:13_global_cumul_impact_all_pressures_KNB_WGS84 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262142 EPSG:3857:19 0 524287 0 524285 EPSG:3857:20 0 1048575 0 1048570 EPSG:3857:21 0 2097151 0 2097140 EPSG:3857:22 -1 4194303 0 4194280 EPSG:3857:23 -1 8388607 0 8388561 EPSG:3857:24 0 16777215 0 16777123 EPSG:3857:25 0 33554431 0 33554247 EPSG:3857:26 0 67108863 0 67108495 EPSG:3857:27 0 134217727 0 134216990 EPSG:3857:28 -1 268435455 0 268433981 EPSG:3857:29 0 536870911 0 536867962 EPSG:3857:30 0 1073741823 0 1073735925 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 6 255 0 511 EPSG:4326:9 13 511 0 1023 EPSG:4326:10 26 1023 0 2047 EPSG:4326:11 53 2047 0 4095 EPSG:4326:12 107 4095 0 8191 EPSG:4326:13 214 8191 0 16383 EPSG:4326:14 429 16383 0 32767 EPSG:4326:15 858 32767 0 65535 EPSG:4326:16 1716 65535 0 131071 EPSG:4326:17 3433 131070 0 262142 EPSG:4326:18 6867 262140 0 524285 EPSG:4326:19 13734 524281 0 1048570 EPSG:4326:20 27468 1048562 0 2097140 EPSG:4326:21 54937 2097124 0 4194280 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 0 31 0 31 EPSG:900913:6 0 63 0 63 EPSG:900913:7 0 127 0 127 EPSG:900913:8 0 255 0 255 EPSG:900913:9 0 511 0 511 EPSG:900913:10 0 1023 0 1023 EPSG:900913:11 0 2047 0 2047 EPSG:900913:12 0 4095 0 4095 EPSG:900913:13 0 8191 0 8191 EPSG:900913:14 0 16383 0 16383 EPSG:900913:15 0 32767 0 32767 EPSG:900913:16 0 65535 0 65535 EPSG:900913:17 0 131071 0 131071 EPSG:900913:18 0 262143 0 262142 EPSG:900913:19 0 524287 0 524285 EPSG:900913:20 0 1048575 0 1048570 EPSG:900913:21 0 2097151 0 2097140 EPSG:900913:22 0 4194303 0 4194280 EPSG:900913:23 0 8388607 0 8388561 EPSG:900913:24 0 16777215 0 16777123 EPSG:900913:25 0 33554431 0 33554247 EPSG:900913:26 0 67108863 0 67108495 EPSG:900913:27 0 134217727 0 134216990 EPSG:900913:28 0 268435455 0 268433981 EPSG:900913:29 0 536870911 0 536867962 EPSG:900913:30 0 1073741823 0 1073735925 Combination Landslide/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_lds_for6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mean predicted temperatures 2022 - Central African Republic Mean predicted temperatures in 2022 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_predict_2022_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 GSOCmapV150 Soil organic carbon (SOC) is the carbon that remains in the soil after partial decomposition of any material produced by living organisms. It constitutes a key element of the global carbon cycle through atmosphere, vegetation, soil, rivers and the ocean. The Global Soil Organic Carbon Map (GSOCmap) allows the estimation of SOC stock from 0 to 30 cm. It represents a key contribution to SDG indicator 15.3.1 which defines the area of degraded land. The GSOCmap represents the first ever global soil organic carbon assessment produced through a participatory approach in which countries developed their capacities and stepped up efforts to compile all the available soil information at national level. Values are in tonnes per hectare. Source: Food and Agricultural Organization of The United Nations (FAO) Data Source: http://www.fao.org/global-soil-partnership/pillars-action/4-information-and-data/global-soil-organic-carbon-gsoc-map/en/ -180.0 -70.91725146799998 179.99999856000005 83.616081247 MapX_UNDP:GSOCmapV150 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 12 0 15 EPSG:3857:5 1 25 0 31 EPSG:3857:6 2 50 0 63 EPSG:3857:7 5 100 0 127 EPSG:3857:8 10 200 0 255 EPSG:3857:9 20 401 0 511 EPSG:3857:10 41 802 0 1023 EPSG:3857:11 83 1605 0 2047 EPSG:3857:12 166 3210 0 4095 EPSG:3857:13 332 6421 0 8191 EPSG:3857:14 665 12842 0 16383 EPSG:3857:15 1330 25684 0 32767 EPSG:3857:16 2660 51368 0 65535 EPSG:3857:17 5320 102736 0 131071 EPSG:3857:18 10640 205473 0 262143 EPSG:3857:19 21280 410946 0 524287 EPSG:3857:20 42561 821893 0 1048575 EPSG:3857:21 85123 1643786 0 2097151 EPSG:3857:22 170247 3287573 0 4194303 EPSG:3857:23 340495 6575147 0 8388607 EPSG:3857:24 680991 13150295 0 16777215 EPSG:3857:25 1361982 26300590 0 33554431 EPSG:3857:26 2723964 52601180 0 67108863 EPSG:3857:27 5447928 105202360 0 134217727 EPSG:3857:28 10895856 210404720 0 268435454 EPSG:3857:29 21791713 420809440 0 536870909 EPSG:3857:30 43583426 841618880 0 1073741819 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 1 28 0 63 EPSG:4326:6 2 57 0 127 EPSG:4326:7 4 114 0 255 EPSG:4326:8 9 228 0 511 EPSG:4326:9 18 457 0 1023 EPSG:4326:10 36 915 0 2047 EPSG:4326:11 72 1830 0 4095 EPSG:4326:12 145 3661 0 8191 EPSG:4326:13 290 7323 0 16383 EPSG:4326:14 581 14647 0 32767 EPSG:4326:15 1162 29294 0 65535 EPSG:4326:16 2324 58588 0 131071 EPSG:4326:17 4648 117176 0 262143 EPSG:4326:18 9297 234352 0 524287 EPSG:4326:19 18594 468705 0 1048575 EPSG:4326:20 37189 937410 0 2097151 EPSG:4326:21 74378 1874821 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 12 0 15 EPSG:3857:5 1 25 0 31 EPSG:3857:6 2 50 0 63 EPSG:3857:7 5 100 0 127 EPSG:3857:8 10 200 0 255 EPSG:3857:9 20 401 0 511 EPSG:3857:10 41 802 0 1023 EPSG:3857:11 83 1605 0 2047 EPSG:3857:12 166 3210 0 4095 EPSG:3857:13 332 6421 0 8191 EPSG:3857:14 665 12842 0 16383 EPSG:3857:15 1330 25684 0 32767 EPSG:3857:16 2660 51368 0 65535 EPSG:3857:17 5320 102736 0 131071 EPSG:3857:18 10640 205473 0 262143 EPSG:3857:19 21280 410946 0 524287 EPSG:3857:20 42561 821893 0 1048575 EPSG:3857:21 85123 1643786 0 2097151 EPSG:3857:22 170247 3287573 0 4194303 EPSG:3857:23 340495 6575147 0 8388607 EPSG:3857:24 680991 13150295 0 16777215 EPSG:3857:25 1361982 26300590 0 33554431 EPSG:3857:26 2723964 52601180 0 67108863 EPSG:3857:27 5447928 105202360 0 134217727 EPSG:3857:28 10895856 210404720 0 268435454 EPSG:3857:29 21791713 420809440 0 536870909 EPSG:3857:30 43583426 841618880 0 1073741819 Temperature change trend (2001-2010) Trend of year temperatures change in '°C per year' across the period 2001-2010. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_01_10_lm image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 v432_CH4_1970_opt_deflate -180.0 -77.95 179.95 88.15000000000002 wesr_climat:v432_CH4_1970_opt_deflate image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 0 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 -1 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 0 115142440 0 134199086 EPSG:3857:28 -1 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 0 921139526 0 1073592693 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 -1 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 0 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 -1 115142440 0 134199086 EPSG:3857:28 0 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 -1 921139526 0 1073592693 Spectral Acceleration 0.2 Sec 975 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_02_s_975_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Lakes -178.871 -54.6059 179.995 81.9818 wesr_risk:lakes_glwd image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 10 0 15 EPSG:3857:5 2 21 0 31 EPSG:3857:6 4 43 0 63 EPSG:3857:7 9 87 0 127 EPSG:3857:8 19 174 0 255 EPSG:3857:9 39 349 1 511 EPSG:3857:10 78 698 3 1023 EPSG:3857:11 157 1396 6 2047 EPSG:3857:12 315 2792 12 4095 EPSG:3857:13 630 5585 25 8191 EPSG:3857:14 1260 11170 51 16383 EPSG:3857:15 2521 22341 102 32767 EPSG:3857:16 5043 44682 205 65535 EPSG:3857:17 10087 89365 411 131070 EPSG:3857:18 20175 178730 822 262140 EPSG:3857:19 40350 357461 1644 524280 EPSG:3857:20 80700 714922 3288 1048561 EPSG:3857:21 161400 1429844 6576 2097122 EPSG:3857:22 322801 2859688 13153 4194245 EPSG:3857:23 645603 5719376 26307 8388491 EPSG:3857:24 1291207 11438753 52615 16776982 EPSG:3857:25 2582415 22877507 105230 33553965 EPSG:3857:26 5164830 45755014 210460 67107931 EPSG:3857:27 10329661 91510028 420921 134215863 EPSG:3857:28 20659323 183020057 841843 268431727 EPSG:3857:29 41318646 366040114 1683686 536863455 EPSG:3857:30 82637292 732080228 3367373 1073726910 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 5 102 0 255 EPSG:4326:8 11 205 1 511 EPSG:4326:9 22 411 3 1023 EPSG:4326:10 45 822 6 2047 EPSG:4326:11 91 1645 12 4095 EPSG:4326:12 182 3290 25 8191 EPSG:4326:13 364 6581 51 16383 EPSG:4326:14 729 13162 102 32767 EPSG:4326:15 1459 26324 205 65535 EPSG:4326:16 2919 52649 411 131070 EPSG:4326:17 5838 105298 822 262140 EPSG:4326:18 11677 210597 1644 524280 EPSG:4326:19 23354 421195 3288 1048561 EPSG:4326:20 46709 842390 6576 2097122 EPSG:4326:21 93418 1684780 13153 4194245 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 10 0 15 EPSG:3857:5 2 21 0 31 EPSG:3857:6 4 43 0 63 EPSG:3857:7 9 87 0 127 EPSG:3857:8 19 174 0 255 EPSG:3857:9 39 349 1 511 EPSG:3857:10 78 698 3 1023 EPSG:3857:11 157 1396 6 2047 EPSG:3857:12 315 2792 12 4095 EPSG:3857:13 630 5585 25 8191 EPSG:3857:14 1260 11170 51 16383 EPSG:3857:15 2521 22341 102 32767 EPSG:3857:16 5043 44682 205 65535 EPSG:3857:17 10087 89365 411 131070 EPSG:3857:18 20175 178730 822 262140 EPSG:3857:19 40350 357461 1644 524280 EPSG:3857:20 80700 714922 3288 1048561 EPSG:3857:21 161400 1429844 6576 2097122 EPSG:3857:22 322801 2859688 13153 4194245 EPSG:3857:23 645603 5719376 26307 8388491 EPSG:3857:24 1291207 11438753 52615 16776982 EPSG:3857:25 2582415 22877507 105230 33553965 EPSG:3857:26 5164830 45755014 210460 67107931 EPSG:3857:27 10329661 91510028 420921 134215863 EPSG:3857:28 20659323 183020057 841843 268431727 EPSG:3857:29 41318646 366040114 1683686 536863455 EPSG:3857:30 82637292 732080228 3367373 1073726910 Mean temperatures 2007 - Central African Republic Mean observed temperatures in 2007 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2007_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Precipitation anomalies (mm) 2081-2100 (RCP8.5) Yearly precipitation anomalies (mm) for the period 2081-2100 based on the climate scenario RCP8.5 (reference 1986-2005). -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:pr_85_81_00 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 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EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 frac_cats_transition_2019_2020_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_transition_2019_2020_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 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EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Human pressures <span style="font-size:1em"> This maps shows the spatial distribution of combined pressures on biodiversity, water provisioning services, and carbon (in biomass and soils) at a global scale. We selected a number of existing datasets which best represented pressures on these 3 components, including: <ul> <li> The Human Footprint (HFP)(Venter et al. 2009); </li> <li> Data derived from the top five weighted water security risk factors obtained from Vörösmarty et al. (2010), aggregated within HydroBASINS (level 5) catchments (Lehner and Grill, 2013); </li> <li> Data on the number and intensity of active fires (MODIS), and climate change risk, based on the estimated difference between average annual future temperature for the reference year 2050 and mean annual historic temperature (1970 – present)(Karger et al. 2017). </li> </ul> These three layers are combined to illustrate broad scale patterns of cumulative human pressures and ascertain where the intrinsic values of nature are most at risk. <br /> <br /> <u>See:</u> <ul> <li> UNEP-WCMC (2020). Human pressures on biodiversity, water and carbon. Cambridge, UK. </li> </ul> <u>Other References:</u> <ul> <li> Karger, D.N. et al. (2017) Climatologies at high resolution for the earth's land surface areas. Scientific Data 4, 170122. <a href="https://doi.org/10.1038/sdata.2017.122." target="_blank">doi.org/10.1038/sdata.2017.122.</a> </li> <li> Lehner, B. and Grill G. (2013): Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems. Hydrological Processes, 27(15): 2171–2186. Data is available at <a href="www.hydrosheds.org">www.hydrosheds.org.</a> </li> <li> Venter, O., Sanderson, E. W., Magrach, A., et al. (2016). Global terrestrial Human Footprint maps for 1993 and 2009. Scientific Data, 3, 160067. <a href="https://doi.org/10.1038/sdata.2016.67." target="_blank">doi.org/10.1038/sdata.2016.67.</a> </li> <li> Vörösmarty, C., McIntyre, P., Gessner, M. et al. (2010). Global threats to human water security and river biodiversity. Nature, 467(7315), 555–561. <a href="https://doi.org/10.1038/nature09440." target="_blank">doi.org/10.1038/nature09440.</a> </li> </ul> </span> -179.99051999985159 -81.82870752472896 179.99257988732398 81.82264272729027 MapX_UNDP:Human_pressures_wgs_opt_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 1 14 0 15 EPSG:3857:5 2 29 0 31 EPSG:3857:6 5 58 0 63 EPSG:3857:7 10 117 0 127 EPSG:3857:8 20 235 0 255 EPSG:3857:9 41 471 0 511 EPSG:3857:10 82 942 0 1023 EPSG:3857:11 164 1884 0 2047 EPSG:3857:12 328 3768 0 4095 EPSG:3857:13 656 7536 0 8191 EPSG:3857:14 1312 15073 0 16383 EPSG:3857:15 2624 30147 0 32767 EPSG:3857:16 5249 60294 1 65534 EPSG:3857:17 10498 120588 3 131069 EPSG:3857:18 20997 241177 6 262138 EPSG:3857:19 41995 482354 13 524277 EPSG:3857:20 83991 964708 27 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EPSG:4326:20 47636 1000974 55 2097108 EPSG:4326:21 95273 2001949 110 4194217 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 1 14 0 15 EPSG:3857:5 2 29 0 31 EPSG:3857:6 5 58 0 63 EPSG:3857:7 10 117 0 127 EPSG:3857:8 20 235 0 255 EPSG:3857:9 41 471 0 511 EPSG:3857:10 82 942 0 1023 EPSG:3857:11 164 1884 0 2047 EPSG:3857:12 328 3768 0 4095 EPSG:3857:13 656 7536 0 8191 EPSG:3857:14 1312 15073 0 16383 EPSG:3857:15 2624 30147 0 32767 EPSG:3857:16 5249 60294 1 65534 EPSG:3857:17 10498 120588 3 131069 EPSG:3857:18 20997 241177 6 262138 EPSG:3857:19 41995 482354 13 524277 EPSG:3857:20 83991 964708 27 1048554 EPSG:3857:21 167983 1929417 55 2097108 EPSG:3857:22 335966 3858834 110 4194217 EPSG:3857:23 671932 7717669 220 8388435 EPSG:3857:24 1343865 15435338 441 16776870 EPSG:3857:25 2687730 30870676 883 33553740 EPSG:3857:26 5375461 61741353 1767 67107480 EPSG:3857:27 10750922 123482707 3534 134214961 EPSG:3857:28 21501845 246965415 7068 268429923 EPSG:3857:29 43003690 493930831 14137 536859846 EPSG:3857:30 86007381 987861663 28275 1073719692 Global protected land areas: IUCN categories The World Database on Protected Areas (WDPA) is the most comprehensive global database on terrestrial and marine protected areas. -179.91959083499992 -55.61075097999992 179.77206144400006 83.13924347000008 unea_pollution:prot2 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 4 103 0 255 EPSG:4326:8 9 207 0 511 EPSG:4326:9 19 414 0 1023 EPSG:4326:10 39 828 0 2046 EPSG:4326:11 78 1656 0 4093 EPSG:4326:12 156 3313 1 8186 EPSG:4326:13 312 6626 3 16373 EPSG:4326:14 624 13253 7 32747 EPSG:4326:15 1248 26507 14 65494 EPSG:4326:16 2497 53015 29 130989 EPSG:4326:17 4995 106030 58 261978 EPSG:4326:18 9991 212061 117 523956 EPSG:4326:19 19983 424122 234 1047912 EPSG:4326:20 39966 848244 468 2095824 EPSG:4326:21 79933 1696488 936 4191648 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 10 0 15 EPSG:900913:5 1 21 0 31 EPSG:900913:6 3 43 0 63 EPSG:900913:7 6 87 0 127 EPSG:900913:8 13 175 0 255 EPSG:900913:9 26 351 0 511 EPSG:900913:10 53 703 0 1023 EPSG:900913:11 106 1406 0 2046 EPSG:900913:12 213 2812 0 4093 EPSG:900913:13 426 5625 1 8186 EPSG:900913:14 853 11250 3 16373 EPSG:900913:15 1706 22501 7 32747 EPSG:900913:16 3413 45002 14 65494 EPSG:900913:17 6826 90004 29 130989 EPSG:900913:18 13652 180009 58 261978 EPSG:900913:19 27305 360019 117 523956 EPSG:900913:20 54610 720039 234 1047912 EPSG:900913:21 109220 1440078 468 2095824 EPSG:900913:22 218441 2880156 936 4191648 EPSG:900913:23 436883 5760312 1873 8383296 EPSG:900913:24 873767 11520624 3747 16766593 EPSG:900913:25 1747535 23041249 7494 33533186 EPSG:900913:26 3495070 46082499 14989 67066373 EPSG:900913:27 6990140 92164998 29978 134132746 EPSG:900913:28 13980280 184329996 59957 268265492 EPSG:900913:29 27960561 368659993 119914 536530985 EPSG:900913:30 55921122 737319986 239829 1073061970 Marine Species Richness (Aquamaps) See: <a href="www.aquamaps.org">Kaschner, K., K. Kesner-Reyes, C. Garilao, J. Rius-Barile, T. Rees, and R. Froese. 2016. AquaMaps: Predicted range maps for aquatic species. World wide web electronic publication, www.aquamaps.org, Version 08/2016.</a><br/><br>Under terms of the licence <a href="https://creativecommons.org/licenses/by-nc/3.0/">Aquamaps cannot be used for commercial purposes</a> -180.0 -90.0 180.0 90.0 MapX_UNDP:richness image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262143 EPSG:3857:19 0 524287 0 524287 EPSG:3857:20 0 1048575 0 1048575 EPSG:3857:21 0 2097151 0 2097151 EPSG:3857:22 -1 4194303 0 4194304 EPSG:3857:23 -1 8388607 0 8388608 EPSG:3857:24 0 16777215 0 16777215 EPSG:3857:25 0 33554431 0 33554431 EPSG:3857:26 0 67108863 0 67108863 EPSG:3857:27 0 134217727 1 134217727 EPSG:3857:28 -1 268435455 3 268435456 EPSG:3857:29 0 536870911 7 536870911 EPSG:3857:30 0 1073741823 14 1073741823 EPSG:4326 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262143 EPSG:3857:19 0 524287 0 524287 EPSG:3857:20 0 1048575 0 1048575 EPSG:3857:21 -1 2097151 0 2097152 EPSG:3857:22 -1 4194303 0 4194304 EPSG:3857:23 0 8388607 0 8388607 EPSG:3857:24 0 16777215 0 16777215 EPSG:3857:25 0 33554431 0 33554431 EPSG:3857:26 0 67108863 0 67108863 EPSG:3857:27 -1 134217727 1 134217728 EPSG:3857:28 0 268435455 3 268435455 EPSG:3857:29 0 536870911 7 536870911 EPSG:3857:30 -1 1073741823 14 1073741824 Precipitation seasonality - Climatology (1973-2013) [coefficient of variation] The Coefficient of Variation is the standard deviation of the monthly precipitation estimates expressed as a percentage of the mean of those estimates (i.e. the annual mean). CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_bio10_15_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from INGV, National Institute of Geophysics and Volcanology, Italy, ECHAM 4.6 Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_ingv_echam4_5km_2041-2060_debiasedmean_tas_av_12m_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Combination Tsunami/Mangroves at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_man6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 International Boundaries Lakes - UNGIWG -125.12333 -17.9886099999999 109.965 67.04695 grid_data_core_pro:_2012_ungiwg_lks_ply_01 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 2 1 6 EPSG:4326:3 1 4 2 12 EPSG:4326:4 2 9 4 25 EPSG:4326:5 4 19 9 51 EPSG:4326:6 8 38 19 103 EPSG:4326:7 16 76 39 206 EPSG:4326:8 32 153 78 412 EPSG:4326:9 65 307 156 824 EPSG:4326:10 130 614 312 1649 EPSG:4326:11 261 1228 624 3299 EPSG:4326:12 522 2457 1248 6598 EPSG:4326:13 1044 4914 2497 13196 EPSG:4326:14 2089 9829 4994 26393 EPSG:4326:15 4178 19658 9989 52786 EPSG:4326:16 8356 39317 19979 105573 EPSG:4326:17 16713 78634 39959 211146 EPSG:4326:18 33427 157269 79919 422292 EPSG:4326:19 66855 314539 159839 844584 EPSG:4326:20 133711 629079 319679 1689168 EPSG:4326:21 267422 1258158 639359 3378337 EPSG:900913 EmodNet_HA_Vessel_density_2019avg_Part1_st5_Medcut_opt -8.2709345664445 26.19942653648442 40.67106379740462 46.977928287399635 Medicip:EmodNet_HA_Vessel_density_2019avg image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 27 30 39 EPSG:3857:7 45 54 61 78 EPSG:3857:8 90 108 122 156 EPSG:3857:9 180 217 244 313 EPSG:3857:10 360 434 488 627 EPSG:3857:11 720 869 976 1255 EPSG:3857:12 1441 1738 1953 2510 EPSG:3857:13 2882 3477 3907 5021 EPSG:3857:14 5764 6955 7815 10042 EPSG:3857:15 11528 13911 15631 20085 EPSG:3857:16 23056 27823 31262 40171 EPSG:3857:17 46113 55646 62524 80343 EPSG:3857:18 92226 111292 125049 160687 EPSG:3857:19 184452 222584 250098 321375 EPSG:3857:20 368905 445169 500197 642751 EPSG:3857:21 737811 890338 1000394 1285502 EPSG:3857:22 1475623 1780676 2000788 2571004 EPSG:3857:23 2951247 3561353 4001577 5142008 EPSG:3857:24 5902494 7122707 8003154 10284016 EPSG:3857:25 11804989 14245415 16006309 20568033 EPSG:3857:26 23609978 28490830 32012618 41136067 EPSG:3857:27 47219957 56981661 64025236 82272135 EPSG:3857:28 94439915 113963322 128050472 164544271 EPSG:3857:29 188879831 227926645 256100944 329088542 EPSG:3857:30 377759663 455853291 512201888 658177084 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 15 19 EPSG:4326:5 7 11 30 39 EPSG:4326:6 15 22 61 78 EPSG:4326:7 30 45 122 156 EPSG:4326:8 61 90 244 313 EPSG:4326:9 122 181 488 627 EPSG:4326:10 244 362 976 1255 EPSG:4326:11 489 725 1953 2510 EPSG:4326:12 978 1451 3907 5021 EPSG:4326:13 1957 2903 7815 10042 EPSG:4326:14 3915 5807 15631 20085 EPSG:4326:15 7831 11614 31262 40171 EPSG:4326:16 15663 23229 62524 80343 EPSG:4326:17 31327 46458 125049 160687 EPSG:4326:18 62655 92916 250098 321375 EPSG:4326:19 125310 185832 500197 642751 EPSG:4326:20 250621 371665 1000394 1285502 EPSG:4326:21 501243 743330 2000788 2571004 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 27 30 39 EPSG:3857:7 45 54 61 78 EPSG:3857:8 90 108 122 156 EPSG:3857:9 180 217 244 313 EPSG:3857:10 360 434 488 627 EPSG:3857:11 720 869 976 1255 EPSG:3857:12 1441 1738 1953 2510 EPSG:3857:13 2882 3477 3907 5021 EPSG:3857:14 5764 6955 7815 10042 EPSG:3857:15 11528 13911 15631 20085 EPSG:3857:16 23056 27823 31262 40171 EPSG:3857:17 46113 55646 62524 80343 EPSG:3857:18 92226 111292 125049 160687 EPSG:3857:19 184452 222584 250098 321375 EPSG:3857:20 368905 445169 500197 642751 EPSG:3857:21 737811 890338 1000394 1285502 EPSG:3857:22 1475623 1780676 2000788 2571004 EPSG:3857:23 2951247 3561353 4001577 5142008 EPSG:3857:24 5902494 7122707 8003154 10284016 EPSG:3857:25 11804989 14245415 16006309 20568033 EPSG:3857:26 23609978 28490830 32012618 41136067 EPSG:3857:27 47219957 56981661 64025236 82272135 EPSG:3857:28 94439915 113963322 128050472 164544271 EPSG:3857:29 188879831 227926645 256100944 329088542 EPSG:3857:30 377759663 455853291 512201888 658177084 Historical Land Cover of emerging Northwest Mining Region of Ghana (1990) This shows the existing land use and land cover of the Northwest region of Ghana prior to exploration and illegal mining activities in the area. The 1990 land cover data would instigate keen observations about the trends of land cover and land use change and the dynamics of the change, which could be associated to either mining or unsustainable local exploitation of naturals resources in the area. Thus, the data gives a three decade landscape outlook of the area, which could be used as baseline data for monitoring and validating the environmental responsiveness of both small-scale and large-scale mining activities in the Northwest Mining Region of Ghana. -2.941804951 9.626453977 -1.42736896 11.030613419 MAPX:GHA_LULC1990 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1828 4029 4063 EPSG:4326:13 3593 3657 8058 8127 EPSG:4326:14 7187 7315 16116 16254 EPSG:4326:15 14375 14631 32232 32508 EPSG:4326:16 28751 29263 64464 65016 EPSG:4326:17 57503 58526 128929 130032 EPSG:4326:18 115007 117052 257859 260065 EPSG:4326:19 230015 234104 515719 520130 EPSG:4326:20 460030 468209 1031438 1040260 EPSG:4326:21 920060 936419 2062877 2080521 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 Live Biomass Carbon Density <style> .p1 { overflow: auto; font-style: italic; font-size: .9em; padding: 10px; margin: 0; text-align: justify; -moz-hyphens: auto; -webkit-hyphens: auto; -ms-hypens: auto; -ms-hyphens: auto; hyphens: auto; max-height: 230px; overflow-x: auto; overflow-y: hidden; columns: 180px; column-rule: 1px solid #ccc; grid-column-gap: 10px; column-gap: 10px; } ul { list-style-type: none; padding: 0; } ul li { margin-bottom: 5px; } </style> <div class="p1"><p>This dataset provides a spatially explicit estimation of above- and below-ground terrestrial live biomass carbon density. The map was produced by combining the most reliable publicly-available datasets on biomass carbon. These datasets were selected based on a literature review of existing datasets on biomass carbon in terrestrial ecosystems, and evaluated against a criteria based on resolution, accuracy, biomass definition and reference date. The selected datasets were then overlaid with the Copernicus land cover dataset (Buchhorn et al. 2019) assigning to each grid cell the corresponding above-ground biomass value from the biomass map that was most appropriate for the grid cell's land cover type. Below-ground biomass was added by using root-to-shoot ratios from the 2006 IPCC guidelines for National Greenhouse Gas Inventories. The values of the resulting map (in tonnes of dry organic matter per hectare) were multiplied by 0.5 to convert to carbon, following the guidelines established in the IPCC Good Practice Guidance for Land Use, Land-Use Change and Forestry (Penman et al. 2003).</p><p><u>See:</u><ul><li>García-Rangel, S. et al. (In prep.) Global distribution of natural carbon stocks potentially vulnerable to land use changes References.</li></ul></p><p><u>Other References:</u><ul><li>Buchhorn, M. ; Smets, B. ; Bertels, L. ; De Roo, B. ; Lesiv, M. ; Tsendbazar, N. - E. ; Herold, M. ; Fritz, S. Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2015: Globe 2020. DOI 10.5281/zenodo.3939038.</li><li>Penman J et al. (2003) Good practice guidance for land use, land-use change and forestry. Kanagawa Prefecture: Institute for Global Environmental Strategies.</li></ul></p></div> -179.99994506847912 -59.59552039034499 179.99993096842002 83.66748265638508 MapX_UNDP:biomass_carbon_density_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 45 0 63 EPSG:3857:7 5 90 0 127 EPSG:3857:8 10 181 0 255 EPSG:3857:9 20 362 0 511 EPSG:3857:10 40 724 0 1023 EPSG:3857:11 80 1448 0 2047 EPSG:3857:12 160 2897 0 4095 EPSG:3857:13 321 5794 0 8191 EPSG:3857:14 643 11589 0 16383 EPSG:3857:15 1287 23178 0 32767 EPSG:3857:16 2575 46357 0 65535 EPSG:3857:17 5151 92715 0 131071 EPSG:3857:18 10302 185431 0 262143 EPSG:3857:19 20605 370863 0 524287 EPSG:3857:20 41210 741727 0 1048575 EPSG:3857:21 82420 1483455 0 2097151 EPSG:3857:22 164840 2966911 0 4194303 EPSG:3857:23 329680 5933823 1 8388606 EPSG:3857:24 659360 11867646 2 16777212 EPSG:3857:25 1318720 23735293 5 33554425 EPSG:3857:26 2637440 47470586 10 67108851 EPSG:3857:27 5274881 94941172 20 134217702 EPSG:3857:28 10549763 189882345 40 268435404 EPSG:3857:29 21099526 379764690 81 536870809 EPSG:3857:30 42199052 759529381 163 1073741618 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 9 212 0 511 EPSG:4326:9 18 425 0 1023 EPSG:4326:10 36 851 0 2047 EPSG:4326:11 72 1702 0 4095 EPSG:4326:12 144 3404 0 8191 EPSG:4326:13 288 6808 0 16383 EPSG:4326:14 576 13616 0 32767 EPSG:4326:15 1152 27233 0 65535 EPSG:4326:16 2305 54466 0 131071 EPSG:4326:17 4611 108932 0 262143 EPSG:4326:18 9222 217864 0 524287 EPSG:4326:19 18444 435728 0 1048575 EPSG:4326:20 36889 871457 0 2097151 EPSG:4326:21 73779 1742914 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 45 0 63 EPSG:3857:7 5 90 0 127 EPSG:3857:8 10 181 0 255 EPSG:3857:9 20 362 0 511 EPSG:3857:10 40 724 0 1023 EPSG:3857:11 80 1448 0 2047 EPSG:3857:12 160 2897 0 4095 EPSG:3857:13 321 5794 0 8191 EPSG:3857:14 643 11589 0 16383 EPSG:3857:15 1287 23178 0 32767 EPSG:3857:16 2575 46357 0 65535 EPSG:3857:17 5151 92715 0 131071 EPSG:3857:18 10302 185431 0 262143 EPSG:3857:19 20605 370863 0 524287 EPSG:3857:20 41210 741727 0 1048575 EPSG:3857:21 82420 1483455 0 2097151 EPSG:3857:22 164840 2966911 0 4194303 EPSG:3857:23 329680 5933823 1 8388606 EPSG:3857:24 659360 11867646 2 16777212 EPSG:3857:25 1318720 23735293 5 33554425 EPSG:3857:26 2637440 47470586 10 67108851 EPSG:3857:27 5274881 94941172 20 134217702 EPSG:3857:28 10549763 189882345 40 268435404 EPSG:3857:29 21099526 379764690 81 536870809 EPSG:3857:30 42199052 759529381 163 1073741618 Mean temperatures 2004 - Central African Republic Mean observed temperatures in 2004 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2004_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Global Dredging Activity 2012 to 2024 This layer maps global dredging activities from 2012 to 2024, including sand and gravel extraction zones across marine and coastal regions. It provides spatial insights into industrial footprints, temporal trends, and potential overlaps with protected areas and sensitive ecosystems. The dataset supports environmental impact assessments and sustainable ocean planning. -180.0 -90.0 180.0 90.0 sand:Dredging_points-2012-2024vf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Tropical Cyclones Frequency This dataset includes an estimate of tropical cyclone frequency of Saffir-Simpson category 5. It is based on two sources: 1) IBTrACS v02r01 (1969 - 2008, http://www.ncdc.noaa.gov/oa/ibtracs/), year 2009 completed by online data from JMA, JTWC, UNISYS, Meteo France and data sent by Alan Sharp from the Australian Bureau of Meteorology. 2) A GIS modeling based on an initial equation from Greg Holland, which was further modified to take into consideration the movement of the cyclones through time. Unit is expected average number of event per 100 years multiplied by 100. This product was designed by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: Raw data: IBTrACS, compilation and GIS processing UNEP/GRID-Geneva. -180.0 -90.0 179.99599307699998 83.99199665399996 wesr_risk:cy_frequency image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 63 2047 0 2047 EPSG:3857:12 126 4095 0 4095 EPSG:3857:13 253 8191 0 8191 EPSG:3857:14 506 16383 0 16383 EPSG:3857:15 1012 32767 0 32767 EPSG:3857:16 2025 65535 0 65535 EPSG:3857:17 4051 131071 0 131070 EPSG:3857:18 8103 262143 0 262141 EPSG:3857:19 16206 524287 0 524282 EPSG:3857:20 32413 1048575 0 1048564 EPSG:3857:21 64827 2097151 0 2097128 EPSG:3857:22 129655 4194303 0 4194257 EPSG:3857:23 259311 8388607 0 8388514 EPSG:3857:24 518622 16777215 0 16777029 EPSG:3857:25 1037245 33554431 0 33554058 EPSG:3857:26 2074490 67108863 0 67108117 EPSG:3857:27 4148981 134217727 0 134216234 EPSG:3857:28 8297963 268435455 0 268432468 EPSG:3857:29 16595927 536870911 0 536864936 EPSG:3857:30 33191854 1073741823 0 1073729872 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1093 32767 0 65535 EPSG:4326:16 2187 65535 0 131070 EPSG:4326:17 4374 131071 0 262141 EPSG:4326:18 8749 262143 0 524282 EPSG:4326:19 17499 524287 0 1048564 EPSG:4326:20 34999 1048575 0 2097128 EPSG:4326:21 69998 2097151 0 4194257 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 63 2047 0 2047 EPSG:3857:12 126 4095 0 4095 EPSG:3857:13 253 8191 0 8191 EPSG:3857:14 506 16383 0 16383 EPSG:3857:15 1012 32767 0 32767 EPSG:3857:16 2025 65535 0 65535 EPSG:3857:17 4051 131071 0 131070 EPSG:3857:18 8103 262143 0 262141 EPSG:3857:19 16206 524287 0 524282 EPSG:3857:20 32413 1048575 0 1048564 EPSG:3857:21 64827 2097151 0 2097128 EPSG:3857:22 129655 4194303 0 4194257 EPSG:3857:23 259311 8388607 0 8388514 EPSG:3857:24 518622 16777215 0 16777029 EPSG:3857:25 1037245 33554431 0 33554058 EPSG:3857:26 2074490 67108863 0 67108117 EPSG:3857:27 4148981 134217727 0 134216234 EPSG:3857:28 8297963 268435455 0 268432468 EPSG:3857:29 16595927 536870911 0 536864936 EPSG:3857:30 33191854 1073741823 0 1073729872 CAFI_FNF_2015_sinu_wgs84_opt The layer shows the extent of forests in the Congo Basin. Data produced in the frame of the project "Assessing deforestation and forest degradation trends and associated current and historical direct drivers in the six CAFI partner countries". Credits: CAFI. Central African Forest Initiative 5.354407954878081 -13.459105669480616 31.7723896460075 13.083556355951599 peatlands:CAFI_FNF_2015_sinu image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 14 17 16 18 EPSG:3857:6 29 34 32 37 EPSG:3857:7 59 68 65 75 EPSG:3857:8 118 137 131 150 EPSG:3857:9 237 275 263 301 EPSG:3857:10 474 550 527 602 EPSG:3857:11 948 1101 1054 1204 EPSG:3857:12 1897 2202 2108 2409 EPSG:3857:13 3795 4405 4217 4818 EPSG:3857:14 7591 8810 8435 9637 EPSG:3857:15 15182 17620 16871 19275 EPSG:3857:16 30365 35241 33742 38551 EPSG:3857:17 60730 70482 67485 77103 EPSG:3857:18 121460 140964 134970 154207 EPSG:3857:19 242921 281928 269941 308415 EPSG:3857:20 485843 563856 539883 616831 EPSG:3857:21 971687 1127712 1079767 1233663 EPSG:3857:22 1943375 2255424 2159535 2467327 EPSG:3857:23 3886750 4510848 4319070 4934654 EPSG:3857:24 7773500 9021697 8638141 9869308 EPSG:3857:25 15547001 18043394 17276282 19738617 EPSG:3857:26 31094003 36086789 34552565 39477234 EPSG:3857:27 62188007 72173578 69105131 78954469 EPSG:3857:28 124376014 144347156 138210263 157908938 EPSG:3857:29 248752028 288694312 276420527 315817877 EPSG:3857:30 497504056 577388624 552841055 631635755 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 6 9 16 18 EPSG:4326:5 13 18 32 37 EPSG:4326:6 27 36 65 75 EPSG:4326:7 54 73 131 150 EPSG:4326:8 109 147 263 301 EPSG:4326:9 218 294 527 602 EPSG:4326:10 437 588 1054 1204 EPSG:4326:11 875 1177 2108 2409 EPSG:4326:12 1750 2354 4217 4818 EPSG:4326:13 3500 4708 8435 9637 EPSG:4326:14 7001 9417 16871 19275 EPSG:4326:15 14002 18834 33742 38551 EPSG:4326:16 28004 37668 67485 77103 EPSG:4326:17 56008 75336 134970 154207 EPSG:4326:18 112017 150673 269941 308415 EPSG:4326:19 224035 301346 539883 616831 EPSG:4326:20 448070 602692 1079767 1233663 EPSG:4326:21 896141 1205385 2159535 2467327 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 14 17 16 18 EPSG:3857:6 29 34 32 37 EPSG:3857:7 59 68 65 75 EPSG:3857:8 118 137 131 150 EPSG:3857:9 237 275 263 301 EPSG:3857:10 474 550 527 602 EPSG:3857:11 948 1101 1054 1204 EPSG:3857:12 1897 2202 2108 2409 EPSG:3857:13 3795 4405 4217 4818 EPSG:3857:14 7591 8810 8435 9637 EPSG:3857:15 15182 17620 16871 19275 EPSG:3857:16 30365 35241 33742 38551 EPSG:3857:17 60730 70482 67485 77103 EPSG:3857:18 121460 140964 134970 154207 EPSG:3857:19 242921 281928 269941 308415 EPSG:3857:20 485843 563856 539883 616831 EPSG:3857:21 971687 1127712 1079767 1233663 EPSG:3857:22 1943375 2255424 2159535 2467327 EPSG:3857:23 3886750 4510848 4319070 4934654 EPSG:3857:24 7773500 9021697 8638141 9869308 EPSG:3857:25 15547001 18043394 17276282 19738617 EPSG:3857:26 31094003 36086789 34552565 39477234 EPSG:3857:27 62188007 72173578 69105131 78954469 EPSG:3857:28 124376014 144347156 138210263 157908938 EPSG:3857:29 248752028 288694312 276420527 315817877 EPSG:3857:30 497504056 577388624 552841055 631635755 gpcc_precipitation_anomaly_annual_19912020 Monthly Precipitation anomaly (mm, difference from the 1991-2020 average). Data shown are the median of the following one data sets: GPCC. White areas indicate where there were too few data to reliably estimate the percentiles. -180.0 -90.0 180.0 90.0 wmo:gpcc_precipitation_anomaly_annual_19912020 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Increase in SOC on Croplands After 20 Yr - Medium Scenario This dataset provides estimate of the potential increase in soil organic carbon within the top 30 cm of soil in croplands after 20 years, following implementation of better land managment practices under a medium sequestration scenario. The per pixel values here take in to consideration the percent of each pixel which is classified as cropland (from the GLC-Share/GLC-02 dataset), and values have been converted to total tonnes of carbon (x 100) per pixel.<br/><br>See: <a href="https://doi.org/10.1038/s41598-017-15794-8">Zomer, R.J., Bossio, D.A., Sommer, R., Verchot, L.V., 2017. Global Sequestration Potential of Increased Organic Carbon in Cropland Soils. Scientific Reports 7, 15554</a>.<br/>For descriptions of sequrestion scenarions see: <a href="https://doi.org/10.1016/j.jenvman.2014.05.017">Sommer, R., Bossio, D., 2014. Dynamics and climate change mitigation potential of soil organic carbon sequestration. Journal of Environmental Management 144, 83–87</a>.<br/> -180.0 -62.002087813 179.9999424 87.37080495400002 MapX_UNDP:soc_dif_me image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 46 0 63 EPSG:3857:7 0 92 0 127 EPSG:3857:8 0 184 0 255 EPSG:3857:9 0 369 0 511 EPSG:3857:10 0 738 0 1023 EPSG:3857:11 0 1476 0 2047 EPSG:3857:12 0 2953 0 4095 EPSG:3857:13 0 5907 0 8191 EPSG:3857:14 0 11814 0 16383 EPSG:3857:15 0 23628 0 32767 EPSG:3857:16 0 47256 0 65535 EPSG:3857:17 0 94512 0 131071 EPSG:3857:18 0 189025 0 262143 EPSG:3857:19 0 378051 0 524287 EPSG:3857:20 0 756103 0 1048575 EPSG:3857:21 0 1512206 0 2097151 EPSG:3857:22 -1 3024413 0 4194303 EPSG:3857:23 -1 6048826 0 8388606 EPSG:3857:24 0 12097653 0 16777213 EPSG:3857:25 0 24195306 0 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11 29 29 EPSG:4326:5 21 22 58 58 EPSG:4326:6 43 44 117 117 EPSG:4326:7 87 89 234 235 EPSG:4326:8 174 179 468 470 EPSG:4326:9 348 359 937 941 EPSG:4326:10 696 718 1875 1882 EPSG:4326:11 1393 1436 3750 3765 EPSG:4326:12 2787 2872 7501 7531 EPSG:4326:13 5574 5744 15003 15063 EPSG:4326:14 11149 11488 30006 30126 EPSG:4326:15 22299 22976 60013 60252 EPSG:4326:16 44599 45953 120026 120504 EPSG:4326:17 89199 91906 240053 241008 EPSG:4326:18 178398 183812 480107 482016 EPSG:4326:19 356797 367625 960215 964033 EPSG:4326:20 713595 735251 1920431 1928067 EPSG:4326:21 1427191 1470503 3840862 3856135 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 152 155 234 235 EPSG:3857:9 304 311 468 470 EPSG:3857:10 609 622 937 941 EPSG:3857:11 1219 1245 1875 1882 EPSG:3857:12 2439 2490 3750 3765 EPSG:3857:13 4878 4981 7501 7531 EPSG:3857:14 9757 9962 15003 15063 EPSG:3857:15 19514 19924 30006 30126 EPSG:3857:16 39029 39849 60013 60252 EPSG:3857:17 78058 79698 120026 120504 EPSG:3857:18 156116 159396 240053 241008 EPSG:3857:19 312233 318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 EPSG:3857:22 2497869 2550351 3840862 3856135 EPSG:3857:23 4995738 5100703 7681724 7712271 EPSG:3857:24 9991476 10201407 15363449 15424542 EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 Travel_time_final_CIV_opt -8.58395416756133 4.361274354409544 -2.4925843424414804 10.745411290664995 AccessMod:Travel_time_final_CIV_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 31 30 31 EPSG:3857:7 60 62 60 63 EPSG:3857:8 120 124 121 126 EPSG:3857:9 240 249 243 252 EPSG:3857:10 481 499 487 504 EPSG:3857:11 962 999 975 1009 EPSG:3857:12 1925 1998 1950 2019 EPSG:3857:13 3850 3996 3900 4039 EPSG:3857:14 7700 7993 7801 8078 EPSG:3857:15 15400 15986 15602 16157 EPSG:3857:16 30800 31973 31205 32314 EPSG:3857:17 61600 63946 62410 64628 EPSG:3857:18 123201 127893 124821 129256 EPSG:3857:19 246402 255786 249642 258513 EPSG:3857:20 492804 511572 499285 517027 EPSG:3857:21 985609 1023145 998570 1034055 EPSG:3857:22 1971218 2046290 1997141 2068111 EPSG:3857:23 3942436 4092580 3994283 4136222 EPSG:3857:24 7884873 8185161 7988566 8272445 EPSG:3857:25 15769747 16370322 15977133 16544890 EPSG:3857:26 31539495 32740645 31954266 33089780 EPSG:3857:27 63078991 65481290 63908533 66179561 EPSG:3857:28 126157982 130962581 127817067 132359122 EPSG:3857:29 252315964 261925162 255634135 264718244 EPSG:3857:30 504631929 523850324 511268271 529436489 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 15 30 31 EPSG:4326:6 28 30 60 63 EPSG:4326:7 56 60 121 126 EPSG:4326:8 112 121 243 252 EPSG:4326:9 225 243 487 504 EPSG:4326:10 450 487 975 1009 EPSG:4326:11 901 974 1950 2019 EPSG:4326:12 1803 1948 3900 4039 EPSG:4326:13 3606 3897 7801 8078 EPSG:4326:14 7213 7795 15602 16157 EPSG:4326:15 14427 15590 31205 32314 EPSG:4326:16 28855 31180 62410 64628 EPSG:4326:17 57711 62360 124821 129256 EPSG:4326:18 115422 124720 249642 258513 EPSG:4326:19 230845 249440 499285 517027 EPSG:4326:20 461691 498881 998570 1034055 EPSG:4326:21 923382 997763 1997141 2068111 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 31 30 31 EPSG:3857:7 60 62 60 63 EPSG:3857:8 120 124 121 126 EPSG:3857:9 240 249 243 252 EPSG:3857:10 481 499 487 504 EPSG:3857:11 962 999 975 1009 EPSG:3857:12 1925 1998 1950 2019 EPSG:3857:13 3850 3996 3900 4039 EPSG:3857:14 7700 7993 7801 8078 EPSG:3857:15 15400 15986 15602 16157 EPSG:3857:16 30800 31973 31205 32314 EPSG:3857:17 61600 63946 62410 64628 EPSG:3857:18 123201 127893 124821 129256 EPSG:3857:19 246402 255786 249642 258513 EPSG:3857:20 492804 511572 499285 517027 EPSG:3857:21 985609 1023145 998570 1034055 EPSG:3857:22 1971218 2046290 1997141 2068111 EPSG:3857:23 3942436 4092580 3994283 4136222 EPSG:3857:24 7884873 8185161 7988566 8272445 EPSG:3857:25 15769747 16370322 15977133 16544890 EPSG:3857:26 31539495 32740645 31954266 33089780 EPSG:3857:27 63078991 65481290 63908533 66179561 EPSG:3857:28 126157982 130962581 127817067 132359122 EPSG:3857:29 252315964 261925162 255634135 264718244 EPSG:3857:30 504631929 523850324 511268271 529436489 Yearly emissions of CH4 - 2010 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -85.59999999999002 179.99999999997954 90.0 wesr_climat:v60_CH4_2010_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 62 0 127 EPSG:4326:7 0 124 0 255 EPSG:4326:8 0 249 0 511 EPSG:4326:9 0 499 0 1023 EPSG:4326:10 0 998 0 2047 EPSG:4326:11 0 1997 0 4095 EPSG:4326:12 0 3995 0 8191 EPSG:4326:13 0 7991 0 16383 EPSG:4326:14 0 15983 0 32767 EPSG:4326:15 0 31967 0 65535 EPSG:4326:16 0 63934 0 131071 EPSG:4326:17 0 127868 0 262143 EPSG:4326:18 0 255736 0 524287 EPSG:4326:19 0 511472 0 1048575 EPSG:4326:20 0 1022944 0 2097151 EPSG:4326:21 0 2045888 0 4194303 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone surge/ Sea grasses at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_sea6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Year precipitations 2000 - Central African Republic Total precipitations observed in 2000 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2000_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 World Database of Key Biodiversity Areas (KBA) Key Biodiversity Areas (KBA) are 'sites contributing significantly to the global persistence of biodiversity’, in terrestrial, freshwater and marine ecosystems. <br> The Global Standard for the Identification of Key Biodiversity Areas (IUCN 2016) sets out globally agreed criteria for the identification of KBAs worldwide. The KBA Standard establishes a consultative, science-based process for KBA identification, founded on the consistent application of global criteria with quantitative thresholds that have been developed through an extensive consultation exercise spanning several years. The Standard is also available in French and Spanish. <br> Sites qualify as global KBAs if they meet one or more of 11 criteria, clustered into five categories: threatened biodiversity; geographically restricted biodiversity; ecological integrity; biological processes; and, irreplaceability. The KBA criteria can be applied to species and ecosystems in terrestrial, inland water and marine environments. Although not all KBA criteria may be relevant to all elements of biodiversity, the thresholds associated with each of the criteria may be applied across all taxonomic groups (other than micro-organisms) and ecosystems. <br> The KBA identification process is a highly inclusive, consultative and bottom-up exercise. Although anyone with appropriate scientific data may propose a site to qualify as a KBA, consultation with stakeholders at the national level (both non-governmental and governmental organizations) is required during the proposal process. KBA identification should build off the existing network of KBAs (including Important Bird and Biodiversity Areas and Alliance for Zero Extinction sites) and new data should seek to strengthen and expand the network of these sites. Any site proposal must undergo independent scientific review. This is followed by the official site nomination with full documentation meeting the Documentation Standards for KBAs. Sites confirmed by the KBA Secretariat to qualify as KBAs then appear on this website. <br> The consultation process to develop A Global Standard for the Identification of Key Biodiversity Areas was led by the IUCN WCPA-SSC Joint Task Force on Biodiversity and Protected Areas. It involved a Framing workshop; technical workshops on Criteria and Delineation, quantitative Thresholds, and Governance of the process to identify KBAs; a second Governance meeting; 14 separate regional consultations held around the world; and interviews with end users of KBA data. A first public consultation draft was posted in 2014, generating more than 1200 comments and responses. The second consultation draft on the Standard was posted in 2015, generating an additional 600 comments and responses. More information on the consultation process to develop the KBA Standard can be found on the Joint Task Force website. -180.0 -87.90113898196397 180.0 90.0 MapX_UNDP_nd:KBA_GeoTiff_clear v2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 126 0 255 EPSG:4326:8 0 253 0 511 EPSG:4326:9 0 506 0 1023 EPSG:4326:10 0 1012 0 2047 EPSG:4326:11 0 2024 0 4095 EPSG:4326:12 0 4048 0 8191 EPSG:4326:13 0 8096 0 16383 EPSG:4326:14 0 16192 0 32767 EPSG:4326:15 0 32385 0 65535 EPSG:4326:16 0 64771 0 131071 EPSG:4326:17 0 129543 0 262143 EPSG:4326:18 0 259087 0 524287 EPSG:4326:19 0 518174 0 1048575 EPSG:4326:20 0 1036349 0 2097151 EPSG:4326:21 0 2072698 0 4194303 EPSG:900913 EPSG:3857_512 Helsinki UA2012 - Warsa 24.126390699633447 59.903163910578456 25.525388499641736 60.84077849941336 unep_storymap:HELSINKI_UA2012_WGS84_Warsaw image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 0 0 4 4 EPSG:4326:3 1 1 9 9 EPSG:4326:4 2 2 18 18 EPSG:4326:5 5 5 36 36 EPSG:4326:6 10 10 72 73 EPSG:4326:7 20 21 145 146 EPSG:4326:8 41 42 290 292 EPSG:4326:9 82 85 580 584 EPSG:4326:10 165 171 1161 1169 EPSG:4326:11 331 342 2322 2338 EPSG:4326:12 663 684 4645 4676 EPSG:4326:13 1327 1369 9290 9353 EPSG:4326:14 2654 2739 18580 18707 EPSG:4326:15 5308 5478 37160 37414 EPSG:4326:16 10616 10957 74320 74829 EPSG:4326:17 21233 21915 148640 149659 EPSG:4326:18 42466 43831 297280 299318 EPSG:4326:19 84932 87663 594561 598636 EPSG:4326:20 169864 175326 1189122 1197272 EPSG:4326:21 339729 350653 2378244 2394544 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 2 2 4 4 EPSG:900913:4 4 4 9 9 EPSG:900913:5 9 9 18 18 EPSG:900913:6 18 18 36 36 EPSG:900913:7 36 37 72 73 EPSG:900913:8 73 74 145 146 EPSG:900913:9 146 148 290 292 EPSG:900913:10 292 297 580 584 EPSG:900913:11 585 595 1161 1169 EPSG:900913:12 1170 1191 2322 2338 EPSG:900913:13 2340 2383 4645 4676 EPSG:900913:14 4680 4766 9290 9353 EPSG:900913:15 9360 9533 18580 18707 EPSG:900913:16 18721 19066 37160 37414 EPSG:900913:17 37443 38133 74320 74829 EPSG:900913:18 74886 76267 148640 149659 EPSG:900913:19 149772 152534 297280 299318 EPSG:900913:20 299544 305069 594561 598636 EPSG:900913:21 599089 610138 1189122 1197272 EPSG:900913:22 1198178 1220277 2378244 2394544 EPSG:900913:23 2396357 2440555 4756489 4789088 EPSG:900913:24 4792715 4881110 9512979 9578177 EPSG:900913:25 9585430 9762220 19025958 19156354 EPSG:900913:26 19170860 19524440 38051917 38312709 EPSG:900913:27 38341721 39048880 76103834 76625418 EPSG:900913:28 76683443 78097761 152207668 153250837 EPSG:900913:29 153366887 156195523 304415337 306501674 EPSG:900913:30 306733775 312391046 608830675 613003348 Forest Condition - 2015 (CAFI) The layer shows the status of forested areas in the Congo Basin. Data produced in the frame of the project "Assessing deforestation and forest degradation trends and associated current and historical direct drivers in the six CAFI partner countries". Credits: CAFI. Central African Forest Initiative 5.602366924286013 -13.455401562813996 31.305988384304207 13.078121459231383 peatlands:CAFI_Congo_Basin_Condition image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 14 17 16 18 EPSG:3857:6 29 34 32 37 EPSG:3857:7 59 68 65 75 EPSG:3857:8 118 137 131 150 EPSG:3857:9 237 275 263 300 EPSG:3857:10 474 550 527 601 EPSG:3857:11 948 1101 1055 1202 EPSG:3857:12 1897 2202 2111 2404 EPSG:3857:13 3795 4405 4223 4808 EPSG:3857:14 7591 8810 8446 9616 EPSG:3857:15 15183 17620 16893 19233 EPSG:3857:16 30366 35240 33787 38467 EPSG:3857:17 60732 70480 67575 76934 EPSG:3857:18 121465 140961 135151 153868 EPSG:3857:19 242930 281922 270303 307736 EPSG:3857:20 485860 563844 540606 615473 EPSG:3857:21 971720 1127689 1081212 1230946 EPSG:3857:22 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EPSG:3857:26 31095043 36086079 34598788 39390291 EPSG:3857:27 62190087 72172158 69197577 78780582 EPSG:3857:28 124380174 144344316 138395155 157561164 EPSG:3857:29 248760349 288688632 276790311 315122329 EPSG:3857:30 497520698 577377264 553580622 630244659 Testing a layer for training 149.66386433258654 -36.214355797728665 150.97478007537504 -32.49681353198739 wesr_swipe:20190927_843_mergedQG_to_delete image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 152 155 234 235 EPSG:3857:9 304 311 468 470 EPSG:3857:10 609 622 937 941 EPSG:3857:11 1219 1245 1875 1882 EPSG:3857:12 2439 2490 3750 3765 EPSG:3857:13 4878 4981 7501 7531 EPSG:3857:14 9757 9962 15003 15063 EPSG:3857:15 19514 19924 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318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 EPSG:3857:22 2497869 2550351 3840862 3856135 EPSG:3857:23 4995738 5100703 7681724 7712271 EPSG:3857:24 9991476 10201407 15363449 15424542 EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 Year precipitations 2015 - Central African Republic Total precipitations observed in 2015 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2015_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 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240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Central Congo Basin water probability (2022) Metadata for files in the zip archive: Crezee_2022_Central_Congo_Peat_Probability_Layers.zip This folder contains 5 probability layers, the output of 1000 classification runs using a random 2/3 subset of training data, that was used to produce the peatland extent estimates and probability map (Figure 1b) in: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This folder contains 5 layers: - Probability_2022_HardwoodDominatedPeatSwamp.tif - Probability_2022_PalmDominatedPeatSwamp.tif - Probability_2022_NonPeatFormingForest.tif - Probability_2022_Savanna.tif - Probability_2022_Water.tif Each layer has pixel values from 0-1000, representing the number of times that class was given as the most likely class for that pixel in 1000 Maximum Likelihood classifications using a random 2/3 subset of the training data. For example, a value of 995 in the Probability_2022_Water.tif file means that in 995 of the 1000 runs this pixel was mapped as 'water'. Conversely, a value of 4 in the Probability_2022_Savanna.tif would mean that that pixel was only mapped as savanna 4 times in the 1000 runs. As an approximation, dividing these values by 1000 gives the probability that that pixel contains a majority of vegetation of that class. Total peat swamp forest probability is obtained by summing the probabilities of the hardwood and palm-dominated peat swamp forest files. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 15.0 -4.999916949999999 25.72744828 3.30533333 peatlands:Crezee_2022_Probability_Water image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 8 17 18 EPSG:4326:5 15 16 34 36 EPSG:4326:6 30 33 69 73 EPSG:4326:7 61 67 138 146 EPSG:4326:8 123 135 277 292 EPSG:4326:9 246 270 554 585 EPSG:4326:10 493 540 1109 1170 EPSG:4326:11 986 1080 2218 2340 EPSG:4326:12 1972 2161 4437 4681 EPSG:4326:13 3945 4323 8874 9362 EPSG:4326:14 7891 8647 17749 18725 EPSG:4326:15 15782 17294 35498 37451 EPSG:4326:16 31564 34588 70997 74903 EPSG:4326:17 63129 69176 141994 149806 EPSG:4326:18 126258 138353 283989 299612 EPSG:4326:19 252516 276707 567978 599224 EPSG:4326:20 505033 553414 1135957 1198449 EPSG:4326:21 1010066 1106829 2271914 2396898 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 Precipitation seasonality [coefficient of variation] (2041-2060) RCP4.5 - CIMP5 The Coefficient of Variation is the standard deviation of the monthly precipitation estimates expressed as a percentage of the mean of those estimates (i.e. the annual mean) for the period 2041-2060 based on RCP4.5. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_bio_mon_ACCESS1-0_rcp45_r1i1p1_g025.nc_15_2041-2060_V1.2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 Flood Hazard 1000 Years (cm) The GAR Atlas global flood hazard assessment uses a probabilistic approach for modelling riverine flood major river basins around the globe. This has been possible after compiling a global database of stream-flow data, merging different sources and gathering more than 8000 stations over the globe in order to calculate the range of possible discharges from very low to the maximum possible scales at different locations along the rivers. The calculated discharges were introduced in the river sections to model water levels downstream. This procedure allowed for the determination of stochastic event-sets of riverine floods from which hazard maps for several return periods (25, 50, 100, 200, 500, 1000 years) were obtained. The hazard maps are developed at 1kmx1km resolution and have been validated against satellite flood footprints from different sources (DFO archive, UNOSAT flood portal) performing well especially for big events For smaller events (lower return periods), the GAR Atlas flood hazard maps tend to overestimate with respect to similar maps produced locally (hazard maps where available for some countries and were used as benchmark). The main issue being that, due to the resolution, the GAR Atlas flood hazard maps do not take into account flood defenses that are normally present to preserve the value exposed to floods. 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EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185582 187500 EPSG:4326:18 112368 119051 371164 375001 EPSG:4326:19 224736 238103 742329 750002 EPSG:4326:20 449472 476206 1484659 1500004 EPSG:4326:21 898945 952412 2969319 3000009 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 h200ic 0.1675000015994978 11.697500041616369 16.000833334932196 23.52416670828256 risk_niger_undp:h200ic image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 3 8 8 EPSG:4326:4 5 6 16 17 EPSG:4326:5 11 13 32 34 EPSG:4326:6 23 27 64 69 EPSG:4326:7 47 55 128 139 EPSG:4326:8 94 111 256 278 EPSG:4326:9 189 222 512 557 EPSG:4326:10 378 445 1024 1115 EPSG:4326:11 756 890 2049 2230 EPSG:4326:12 1512 1781 4099 4460 EPSG:4326:13 3025 3563 8199 8920 EPSG:4326:14 6050 7127 16399 17840 EPSG:4326:15 12101 14254 32798 35680 EPSG:4326:16 24203 28509 65596 71361 EPSG:4326:17 48406 57018 131193 142723 EPSG:4326:18 96812 114036 262387 285446 EPSG:4326:19 193624 228072 524775 570893 EPSG:4326:20 387249 456145 1049551 1141787 EPSG:4326:21 774499 912290 2099103 2283575 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 3 3 4 4 EPSG:900913:4 6 7 8 8 EPSG:900913:5 13 14 16 17 EPSG:900913:6 27 29 32 34 EPSG:900913:7 55 59 64 69 EPSG:900913:8 110 119 128 139 EPSG:900913:9 221 239 256 278 EPSG:900913:10 443 478 512 557 EPSG:900913:11 886 956 1024 1115 EPSG:900913:12 1772 1913 2049 2230 EPSG:900913:13 3544 3827 4099 4460 EPSG:900913:14 7089 7655 8199 8920 EPSG:900913:15 14179 15311 16399 17840 EPSG:900913:16 28359 30623 32798 35680 EPSG:900913:17 56719 61247 65596 71361 EPSG:900913:18 113439 122494 131193 142723 EPSG:900913:19 226879 244988 262387 285446 EPSG:900913:20 453758 489977 524775 570893 EPSG:900913:21 907517 979954 1049551 1141787 EPSG:900913:22 1815034 1959909 2099103 2283575 EPSG:900913:23 3630068 3919818 4198207 4567150 EPSG:900913:24 7260136 7839637 8396414 9134300 EPSG:900913:25 14520272 15679275 16792828 18268601 EPSG:900913:26 29040545 31358551 33585656 36537203 EPSG:900913:27 58081090 62717103 67171312 73074407 EPSG:900913:28 116162180 125434207 134342625 146148814 EPSG:900913:29 232324360 250868415 268685250 292297628 EPSG:900913:30 464648721 501736831 537370500 584595256 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 Kerala Flood 10 Years RP - RCP85 Kerala State flood hazard map - RCP 8.5 scenario. Maximum expected flood event water height in a 10 years return period, expressed in cm. 74.85958333333333 8.25375 77.49208333333334 12.842916666666673 ECO-DRR:Kerala_Flood_10_Yrs_RCP85 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185583 187500 EPSG:4326:18 112368 119051 371166 375000 EPSG:4326:19 224736 238103 742332 750000 EPSG:4326:20 449472 476206 1484664 1500000 EPSG:4326:21 898945 952412 2969329 3000000 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 Combination Tropical cyclone surge/ Sea grasses at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_sea6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 total_strong_events_Automn_output_opt -17.999999999999943 -1.4999999999999432 75.00000000000006 45.00000000000006 grid_data_core:total_strong_events_Automn_output_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 230 362 EPSG:3857:10 368 516 460 725 EPSG:3857:11 736 1032 921 1450 EPSG:3857:12 1473 2065 1843 2901 EPSG:3857:13 2946 4130 3686 5802 EPSG:3857:14 5893 8260 7372 11605 EPSG:3857:15 11787 16520 14745 23210 EPSG:3857:16 23574 33041 29491 46421 EPSG:3857:17 47149 66082 58982 92842 EPSG:3857:18 94299 132164 117964 185685 EPSG:3857:19 188599 264328 235929 371370 EPSG:3857:20 377199 528657 471859 742741 EPSG:3857:21 754398 1057315 943718 1485482 EPSG:3857:22 1508796 2114630 1887436 2970965 EPSG:3857:23 3017592 4229260 3774873 5941930 EPSG:3857:24 6035184 8458521 7549747 11883861 EPSG:3857:25 12070369 16917042 15099494 23767722 EPSG:3857:26 24140738 33834084 30198988 47535445 EPSG:3857:27 48281477 67668168 60397977 95070890 EPSG:3857:28 96562954 135336336 120795955 190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 7 11 EPSG:4326:4 3 8 14 22 EPSG:4326:5 7 16 28 45 EPSG:4326:6 15 32 57 90 EPSG:4326:7 31 65 115 181 EPSG:4326:8 63 130 230 362 EPSG:4326:9 127 260 460 725 EPSG:4326:10 255 520 921 1450 EPSG:4326:11 511 1041 1843 2901 EPSG:4326:12 1023 2082 3686 5802 EPSG:4326:13 2047 4164 7372 11605 EPSG:4326:14 4095 8328 14745 23210 EPSG:4326:15 8191 16657 29491 46421 EPSG:4326:16 16383 33314 58982 92842 EPSG:4326:17 32767 66628 117964 185685 EPSG:4326:18 65535 133256 235929 371370 EPSG:4326:19 131071 266513 471859 742741 EPSG:4326:20 262143 533026 943718 1485482 EPSG:4326:21 524287 1066052 1887436 2970965 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 230 362 EPSG:3857:10 368 516 460 725 EPSG:3857:11 736 1032 921 1450 EPSG:3857:12 1473 2065 1843 2901 EPSG:3857:13 2946 4130 3686 5802 EPSG:3857:14 5893 8260 7372 11605 EPSG:3857:15 11787 16520 14745 23210 EPSG:3857:16 23574 33041 29491 46421 EPSG:3857:17 47149 66082 58982 92842 EPSG:3857:18 94299 132164 117964 185685 EPSG:3857:19 188599 264328 235929 371370 EPSG:3857:20 377199 528657 471859 742741 EPSG:3857:21 754398 1057315 943718 1485482 EPSG:3857:22 1508796 2114630 1887436 2970965 EPSG:3857:23 3017592 4229260 3774873 5941930 EPSG:3857:24 6035184 8458521 7549747 11883861 EPSG:3857:25 12070369 16917042 15099494 23767722 EPSG:3857:26 24140738 33834084 30198988 47535445 EPSG:3857:27 48281477 67668168 60397977 95070890 EPSG:3857:28 96562954 135336336 120795955 190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 WDPA Marine Protected Areas Global Ocean Units 2024 This layer presents globally distributed marine protected areas (MPAs) from the World Database on Protected Areas (WDPA). It includes designated zones across all ocean basins, highlighting conservation efforts aimed at safeguarding biodiversity, regulating resource use, and supporting climate resilience. The dataset is essential for assessing overlaps between protected zones and industrial activities such as sand dredging, fishing, and offshore development. -179.9999999999 -85.41188720023403 180.0 86.45371110997979 sand:WDPA_2024_MPA image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 62 0 127 EPSG:4326:7 2 124 0 255 EPSG:4326:8 5 249 0 511 EPSG:4326:9 10 498 0 1023 EPSG:4326:10 20 997 0 2047 EPSG:4326:11 40 1995 0 4095 EPSG:4326:12 80 3991 0 8191 EPSG:4326:13 161 7983 0 16383 EPSG:4326:14 322 15966 0 32767 EPSG:4326:15 645 31932 0 65535 EPSG:4326:16 1291 63865 0 131071 EPSG:4326:17 2582 127731 0 262143 EPSG:4326:18 5164 255462 0 524287 EPSG:4326:19 10329 510924 0 1048575 EPSG:4326:20 20658 1021848 0 2097151 EPSG:4326:21 41317 2043696 0 4194303 EPSG:900913 EPSG:3857_512 Mean predicted temperatures 2021 - Central African Republic Mean predicted temperatures in 2021 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_predict_2021_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Coral reefs total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:coralkm2a_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Tree Cover Loss (2001-2024) Forest loss during the period 2001-2024, defined as a stand-replacement disturbance, or a change from a forest to non-forest state. Encoded as either 0 (no loss) or else a value in the range 1-24, representing loss detected primarily in the year 2001-2024, respectively. 10.960797274810812 -13.500019913075064 31.421883855574613 5.46454493380093 peatlands:tree_cover_loss_2001_2024 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 17 16 18 EPSG:3857:6 31 34 33 37 EPSG:3857:7 62 68 67 75 EPSG:3857:8 124 137 135 150 EPSG:3857:9 248 275 271 300 EPSG:3857:10 496 550 543 601 EPSG:3857:11 992 1101 1086 1202 EPSG:3857:12 1985 2203 2172 2405 EPSG:3857:13 3971 4406 4345 4811 EPSG:3857:14 7942 8812 8690 9622 EPSG:3857:15 15885 17624 17381 19244 EPSG:3857:16 31771 35248 34763 38488 EPSG:3857:17 63543 70497 69526 76976 EPSG:3857:18 127086 140994 139053 153952 EPSG:3857:19 254173 281989 278106 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4926486 EPSG:3857:24 8133554 9023658 8899418 9852973 EPSG:3857:25 16267109 18047316 17798836 19705947 EPSG:3857:26 32534219 36094632 35597672 39411895 EPSG:3857:27 65068438 72189264 71195345 78823791 EPSG:3857:28 130136876 144378528 142390690 157647582 EPSG:3857:29 260273753 288757056 284781381 315295165 EPSG:3857:30 520547506 577514112 569562763 630590331 frac_cats_transition_2016_2017_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_transition_2016_2017_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 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EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 h50ic 0.1675000015994978 11.697500041616369 16.000833334932196 23.52416670828256 risk_niger_undp:h50ic image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 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155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 Central Congo Basin palm-dominated peat swamp forest probability (2022) Metadata for files in the zip archive: Crezee_2022_Central_Congo_Peat_Probability_Layers.zip This folder contains 5 probability layers, the output of 1000 classification runs using a random 2/3 subset of training data, that was used to produce the peatland extent estimates and probability map (Figure 1b) in: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This folder contains 5 layers: - Probability_2022_HardwoodDominatedPeatSwamp.tif - Probability_2022_PalmDominatedPeatSwamp.tif - Probability_2022_NonPeatFormingForest.tif - Probability_2022_Savanna.tif - Probability_2022_Water.tif Each layer has pixel values from 0-1000, representing the number of times that class was given as the most likely class for that pixel in 1000 Maximum Likelihood classifications using a random 2/3 subset of the training data. For example, a value of 995 in the Probability_2022_Water.tif file means that in 995 of the 1000 runs this pixel was mapped as 'water'. Conversely, a value of 4 in the Probability_2022_Savanna.tif would mean that that pixel was only mapped as savanna 4 times in the 1000 runs. As an approximation, dividing these values by 1000 gives the probability that that pixel contains a majority of vegetation of that class. Total peat swamp forest probability is obtained by summing the probabilities of the hardwood and palm-dominated peat swamp forest files. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 15.0 -4.999916949999999 25.72744828 3.30533333 peatlands:Crezee_2022_Probability_PalmDominatedPeatSwamp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 8 17 18 EPSG:4326:5 15 16 34 36 EPSG:4326:6 30 33 69 73 EPSG:4326:7 61 67 138 146 EPSG:4326:8 123 135 277 292 EPSG:4326:9 246 270 554 585 EPSG:4326:10 493 540 1109 1170 EPSG:4326:11 986 1080 2218 2340 EPSG:4326:12 1972 2161 4437 4681 EPSG:4326:13 3945 4323 8874 9362 EPSG:4326:14 7891 8647 17749 18725 EPSG:4326:15 15782 17294 35498 37451 EPSG:4326:16 31564 34588 70997 74903 EPSG:4326:17 63129 69176 141994 149806 EPSG:4326:18 126258 138353 283989 299612 EPSG:4326:19 252516 276707 567978 599224 EPSG:4326:20 505033 553414 1135957 1198449 EPSG:4326:21 1010066 1106829 2271914 2396898 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 Nutrient Pollution (fertilizers) 2013 - KNB Input data are from 2007-2010 FAO statistics, the most recent available. FAO data on annual country-level fertilizer were used were available, averaged over the time periods. Missing values were filled using a linear regression model of fertilizers as a function of pesticides (gaps: N=4; regression: R2 = 0.72) when pesticide data were available or agricultural GDP (gaps: N=22; regression: R2 = 0.62) when not. These country-level average fertilizer values were then dasymetrically distributed over a country’s landscape using global land cover data from 2009, derived from the Moderate Resolution imaging Spectroradiometer (MODIS) instrument at ~500m resolution. Finally, spread of the driver values into coastal waters at each pour point was modelled with a cost-path surface on the basis of a decay function that assigns a fixed amount of the driver (0.5% of the value in the previous cell) in the initial cell and then evenly distributes the remaining amount of driver in all adjacent and ‘unvisited’ cells, repeated until a minimum threshold (0.05% of global maximum) is reached. This approach to modelling river plumes is diffusive and so allows drivers to wrap around headlands and islands. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS." -179.99999869409874 -57.96420981377538 179.9994455075789 84.9958245860871 unea_pollution:13_plumes_fert_halpern_KNB_WGS84 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 44 0 63 EPSG:3857:7 0 89 0 127 EPSG:3857:8 0 178 0 255 EPSG:3857:9 0 357 0 511 EPSG:3857:10 1 715 0 1023 EPSG:3857:11 3 1430 0 2047 EPSG:3857:12 7 2861 0 4095 EPSG:3857:13 14 5723 0 8191 EPSG:3857:14 29 11446 0 16383 EPSG:3857:15 58 22892 0 32767 EPSG:3857:16 116 45784 0 65535 EPSG:3857:17 232 91569 0 131071 EPSG:3857:18 464 183139 0 262143 EPSG:3857:19 928 366279 0 524287 EPSG:3857:20 1856 732558 0 1048574 EPSG:3857:21 3713 1465117 0 2097148 EPSG:3857:22 7427 2930235 0 4194297 EPSG:3857:23 14855 5860470 0 8388595 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127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 Biodiversity Intactness Index The Biodiversity Intactness Index is the modeled average abundance of originally-present species, relative to their abundance in an intact ecosystem. Please refer to Newbold et al. (2016) for all details. Citations: Article: Newbold T, Hudson LN, Arnell AP, Contu S, De Palma A, Ferrier S, Hill SL, Hoskins AJ, Lysenko I, Phillips HR, Burton VJ, Chng CW, Emerson S, Gao D, Pask-Hale G, Hutton J, Jung M, Sanchez-Ortiz K, Simmons BI, Whitmee S, Zhang H, Scharlemann JP, Purvis A. Has land use pushed terrestrial biodiversity beyond the planetary boundary? A global assessment. Science. 2016 Jul 15;353(6296):288-91. doi: 10.1126/science.aaf2201. PMID: 27418509. Dataset Tim Newbold; Lawrence Hudson; Andy Arnell; Sara Contu et al. (2016). Global map of the Biodiversity Intactness Index, from Newbold et al. (2016) Science [Data set]. 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These data is one version of the GIS global mangrove database (MFW). The database is 30 m pixel with global coverage annually for 2000 to 2014. This layer shows the information concerning the year 2000. Data are mangrove loss in the mangrove biome since 2000 as defined by MFW. CGMFC-21 provides high resolution local, regional, national, and global estimates of annual mangrove forest levels using continuous data from 2000 through to 2012 with the goal of driving mangrove research questions pertaining to biodiversity, climate change, food security, livelihoods, fisheries support, and conservation that have been hindered until now by a lack of suitable data. CGMFC-21 provides the required spatiotemporal resolutions to not only set REDD baseline measures globally in a systematic manner, but also to account for forest degradation as well as deforestation on an annual basis. Countries showing relatively high levels of 21st Century mangrove loss include Myanmar, Guatemala, Malaysia, Cambodia, and Indonesia. Many nations that have reported mangrove deforestation in earlier periods such as Ecuador, Bangladesh and Nigeria, have stabilized their mangrove levels during this period. Indonesia remains by far the largest mangrove holding nation containing between 26.16% and 28.50% of the global mangrove area with a deforestation rate of between 0.26% and 0.63% annually. Global mangrove deforestation continues but at a much reduced rate of between 0.16% and 0.39% annually. Annual mangrove deforestation is now close to zero in the Americas, Africa, and Australia as well as in selected Ramsar sites and protected areas. The global mangrove deforestation pattern during the 21st Century is one of decreasing rates of deforestation, with many nations essentially stable, with the exception of the largest mangrove holding region of Southeast Asia. (2015-09-01) Hamilton, S. E., & Casey, D. (2016). Creation of a high spatio-temporal resolution global database of continuous mangrove forest cover for the 21st century (CGMFC-21). 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Unit is estimated risk index from 1 (low) to 5 (extreme). This product was designed by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. 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(2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This is a raster file representing relative uncertainty (in %) around the median peat thickness estimate (Fig. 3a of the paper). For each pixel, the width of the 95% confidence interval was calculated from 100 peat thickness estimates by substracting the 2.5th from the 97.5th percentile. Relative uncertainty was then calculated as ± half the width of the 95% confidence interval, expressed as percentage of the median peat thickness estimate. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. 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EPSG:4326:11 604 754 2740 2905 EPSG:4326:12 1208 1508 5481 5811 EPSG:4326:13 2416 3016 10962 11622 EPSG:4326:14 4833 6033 21925 23245 EPSG:4326:15 9666 12067 43850 46490 EPSG:4326:16 19333 24135 87701 92981 EPSG:4326:17 38666 48270 175403 185962 EPSG:4326:18 77332 96541 350806 371924 EPSG:4326:19 154664 193083 701613 743848 EPSG:4326:20 309329 386167 1403227 1487696 EPSG:4326:21 618659 772334 2806455 2975392 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 10 11 EPSG:3857:5 12 13 21 22 EPSG:3857:6 24 27 42 45 EPSG:3857:7 49 55 85 90 EPSG:3857:8 99 110 171 181 EPSG:3857:9 199 221 342 363 EPSG:3857:10 398 442 685 726 EPSG:3857:11 797 885 1370 1452 EPSG:3857:12 1595 1770 2740 2905 EPSG:3857:13 3191 3540 5481 5811 EPSG:3857:14 6382 7080 10962 11622 EPSG:3857:15 12765 14161 21925 23245 EPSG:3857:16 25531 28322 43850 46490 EPSG:3857:17 51062 56645 87701 92981 EPSG:3857:18 102125 113291 175403 185962 EPSG:3857:19 204250 226583 350806 371924 EPSG:3857:20 408501 453167 701613 743848 EPSG:3857:21 817003 906335 1403227 1487696 EPSG:3857:22 1634007 1812671 2806455 2975392 EPSG:3857:23 3268014 3625342 5612910 5950785 EPSG:3857:24 6536028 7250684 11225821 11901570 EPSG:3857:25 13072057 14501368 22451643 23803141 EPSG:3857:26 26144114 29002736 44903286 47606282 EPSG:3857:27 52288228 58005473 89806573 95212564 EPSG:3857:28 104576456 116010946 179613146 190425129 EPSG:3857:29 209152912 232021892 359226292 380850259 EPSG:3857:30 418305824 464043784 718452584 761700519 Frequency of Landslides Triggered By Earthquakes This dataset includes an estimate of the annual frequency of landslide triggered by earthquakes. It depends on the combination of trigger and susceptibility defined by six parameters: slope factor, lithological (or geological) conditions, soil moisture condition, vegetation cover, precipitation and seismic conditions. Unit is expected annual probability and percentage of pixel of occurrence of a potentially destructive landslide event x 1000000. This product was designed by International Centre for Geohazards (NGI) for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards (NGI). -180.0 -56.01339243789985 179.9916666666665 89.99494089543342 wesr_risk:ls_eq image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 44 0 63 EPSG:3857:7 0 88 0 127 EPSG:3857:8 0 176 0 255 EPSG:3857:9 0 352 0 511 EPSG:3857:10 0 705 0 1023 EPSG:3857:11 0 1410 0 2047 EPSG:3857:12 0 2820 0 4095 EPSG:3857:13 0 5641 0 8191 EPSG:3857:14 0 11283 0 16383 EPSG:3857:15 0 22566 0 32767 EPSG:3857:16 0 45132 0 65534 EPSG:3857:17 0 90265 0 131068 EPSG:3857:18 0 180531 0 262137 EPSG:3857:19 0 361063 0 524275 EPSG:3857:20 0 722126 0 1048551 EPSG:3857:21 0 1444252 0 2097103 EPSG:3857:22 -1 2888504 0 4194206 EPSG:3857:23 -1 5777009 0 8388413 EPSG:3857:24 0 11554019 0 16776827 EPSG:3857:25 0 23108038 0 33553655 EPSG:3857:26 0 46216077 0 67107310 EPSG:3857:27 0 92432154 0 134214621 EPSG:3857:28 -1 184864308 0 268429242 EPSG:3857:29 0 369728616 0 536858484 EPSG:3857:30 0 739457232 0 1073716968 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 0 25 0 63 EPSG:4326:6 0 51 0 127 EPSG:4326:7 0 103 0 255 EPSG:4326:8 0 207 0 511 EPSG:4326:9 0 415 0 1023 EPSG:4326:10 0 830 0 2047 EPSG:4326:11 0 1661 0 4095 EPSG:4326:12 0 3322 0 8191 EPSG:4326:13 0 6645 0 16383 EPSG:4326:14 0 13290 0 32767 EPSG:4326:15 0 26580 0 65534 EPSG:4326:16 1 53161 0 131068 EPSG:4326:17 3 106323 0 262137 EPSG:4326:18 7 212647 0 524275 EPSG:4326:19 14 425294 0 1048551 EPSG:4326:20 29 850589 0 2097103 EPSG:4326:21 58 1701179 0 4194206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 44 0 63 EPSG:3857:7 0 88 0 127 EPSG:3857:8 0 176 0 255 EPSG:3857:9 0 352 0 511 EPSG:3857:10 0 705 0 1023 EPSG:3857:11 0 1410 0 2047 EPSG:3857:12 0 2820 0 4095 EPSG:3857:13 0 5641 0 8191 EPSG:3857:14 0 11283 0 16383 EPSG:3857:15 0 22566 0 32767 EPSG:3857:16 0 45132 0 65534 EPSG:3857:17 0 90265 0 131068 EPSG:3857:18 0 180531 0 262137 EPSG:3857:19 0 361063 0 524275 EPSG:3857:20 0 722126 0 1048551 EPSG:3857:21 -1 1444252 0 2097103 EPSG:3857:22 -1 2888504 0 4194206 EPSG:3857:23 0 5777009 0 8388413 EPSG:3857:24 0 11554019 0 16776827 EPSG:3857:25 0 23108038 0 33553655 EPSG:3857:26 0 46216077 0 67107310 EPSG:3857:27 -1 92432154 0 134214621 EPSG:3857:28 0 184864308 0 268429242 EPSG:3857:29 0 369728616 0 536858484 EPSG:3857:30 -1 739457232 0 1073716968 Physical Exposition To Landslides Triggered By Precipitations This dataset includes an estimate of the annual frequency of landslide triggered by precipitations. It depends on the combination of trigger and susceptibility defined by six parameters: slope factor, lithological (or geological) conditions, soil moisture condition, vegetation cover, precipitation and seismic conditions. Unit is expected annual probability and percentage of pixel of occurrence of a potentially destructive landslide event x 1000000. This product was designed by International Centre for Geohazards (NGI) for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards (NGI). -180.0 -90.0 180.0 90.0 wesr_risk:ls_physexp2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Illegal Dumping Susceptibility in Keur Massar Senegal in 2025 (weighted) This map shows the weighted illegal dumping susceptibility across the three communes of Keur Massar (Malika, Keur Massar, and Yeumbeul Nord) in Dakar, Senegal. The map was produced in 2025 as part of a research project using multi-criteria analysis at UNEP/GRID Geneva. The map represents a weighted combination of several positively correlated criteria with illegal dumping: proximity to water edges, vegetation areas, bare soil areas, population density (2025), land surface temperature, market areas, areas around PRNs, and a social perception criterion derived from a survey of students living in the three communes. Waste collection routes, which are negatively correlated with illegal dumping, are also included. Weights for each criterion were determined using the Analytic Hierarchy Process (AHP). The relative importance of the criteria was established based on the student surveys and scientific literature. A pairwise comparison matrix was then created to calculate the weights. Each criterion raster was multiplied by its corresponding weight, and the weighted rasters were summed to produce the final map. All criteria were rasterized when necessary and normalized before weighting. The Focal Statistics tool was applied with a radius of 7 pixels to smooth the results and reduce local noise. The susceptibility levels are visualized using a color scale: dark green (very low, ≤ 0.19), light green (low, ≤ 0.24), beige (medium, ≤ 0.27), orange (high, ≤ 0.31), and red (very high, ≤ 0.42). This output provides a comprehensive overview of spatial susceptibility patterns for illegal dumping, supporting targeted interventions and planning. -17.36716999545483 14.763385550148119 -17.286595649628648 14.822825777160343 dakar_waste:carte_ponderee image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7509 7512 7401 7405 EPSG:3857:15 15019 15025 14803 14810 EPSG:3857:16 30038 30050 29606 29621 EPSG:3857:17 60077 60100 59212 59242 EPSG:3857:18 120155 120200 118425 118484 EPSG:3857:19 240311 240401 236851 236968 EPSG:3857:20 480623 480802 473702 473937 EPSG:3857:21 961247 961605 947404 947874 EPSG:3857:22 1922494 1923210 1894809 1895748 EPSG:3857:23 3844988 3846421 3789619 3791497 EPSG:3857:24 7689977 7692842 7579239 7582994 EPSG:3857:25 15379954 15385684 15158478 15165988 EPSG:3857:26 30759908 30771368 30316956 30331977 EPSG:3857:27 61519816 61542736 60633913 60663954 EPSG:3857:28 123039632 123085473 121267827 121327908 EPSG:3857:29 246079264 246170947 242535654 242655816 EPSG:3857:30 492158529 492341894 485071309 485311632 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 462 EPSG:4326:10 427 428 925 925 EPSG:4326:11 855 856 1850 1851 EPSG:4326:12 1710 1712 3700 3702 EPSG:4326:13 3421 3424 7401 7405 EPSG:4326:14 6842 6848 14803 14810 EPSG:4326:15 13685 13696 29606 29621 EPSG:4326:16 27371 27392 59212 59242 EPSG:4326:17 54742 54785 118425 118484 EPSG:4326:18 109484 109571 236851 236968 EPSG:4326:19 218969 219142 473702 473937 EPSG:4326:20 437938 438285 947404 947874 EPSG:4326:21 875877 876570 1894809 1895748 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7509 7512 7401 7405 EPSG:3857:15 15019 15025 14803 14810 EPSG:3857:16 30038 30050 29606 29621 EPSG:3857:17 60077 60100 59212 59242 EPSG:3857:18 120155 120200 118425 118484 EPSG:3857:19 240311 240401 236851 236968 EPSG:3857:20 480623 480802 473702 473937 EPSG:3857:21 961247 961605 947404 947874 EPSG:3857:22 1922494 1923210 1894809 1895748 EPSG:3857:23 3844988 3846421 3789619 3791497 EPSG:3857:24 7689977 7692842 7579239 7582994 EPSG:3857:25 15379954 15385684 15158478 15165988 EPSG:3857:26 30759908 30771368 30316956 30331977 EPSG:3857:27 61519816 61542736 60633913 60663954 EPSG:3857:28 123039632 123085473 121267827 121327908 EPSG:3857:29 246079264 246170947 242535654 242655816 EPSG:3857:30 492158529 492341894 485071309 485311632 Forest Structual Condition Index (SCI) The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> -81.70875583396088 -20.582447168229265 153.4280138820783 25.91760211162399 MapX_UNDP:forest_struct_cond_ind_19 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 871 1143 559 1896 EPSG:3857:12 1742 2287 1118 3793 EPSG:3857:13 3485 4574 2236 7587 EPSG:3857:14 6970 9149 4473 15174 EPSG:3857:15 13940 18299 8946 30349 EPSG:3857:16 27880 36598 17893 60698 EPSG:3857:17 55760 73196 35786 121397 EPSG:3857:18 111520 146392 71573 242794 EPSG:3857:19 223041 292785 143146 485589 EPSG:3857:20 446082 585571 286293 971179 EPSG:3857:21 892165 1171142 572587 1942358 EPSG:3857:22 1784331 2342285 1145175 3884717 EPSG:3857:23 3568663 4684570 2290351 7769435 EPSG:3857:24 7137327 9369141 4580703 15538871 EPSG:3857:25 14274655 18738283 9161407 31077743 EPSG:3857:26 28549311 37476567 18322815 62155486 EPSG:3857:27 57098623 74953134 36645631 124310973 EPSG:3857:28 114197246 149906268 73291263 248621947 EPSG:3857:29 228394492 299812536 146582527 497243894 EPSG:3857:30 456788984 599625072 293165054 994487788 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 91 157 139 474 EPSG:4326:9 182 314 279 948 EPSG:4326:10 364 629 559 1896 EPSG:4326:11 729 1258 1118 3793 EPSG:4326:12 1458 2516 2236 7587 EPSG:4326:13 2916 5032 4473 15174 EPSG:4326:14 5832 10065 8946 30349 EPSG:4326:15 11665 20130 17893 60698 EPSG:4326:16 23331 40261 35786 121397 EPSG:4326:17 46663 80523 71573 242794 EPSG:4326:18 93326 161047 143146 485589 EPSG:4326:19 186653 322094 286293 971179 EPSG:4326:20 373307 644189 572587 1942358 EPSG:4326:21 746614 1288378 1145175 3884717 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 871 1143 559 1896 EPSG:3857:12 1742 2287 1118 3793 EPSG:3857:13 3485 4574 2236 7587 EPSG:3857:14 6970 9149 4473 15174 EPSG:3857:15 13940 18299 8946 30349 EPSG:3857:16 27880 36598 17893 60698 EPSG:3857:17 55760 73196 35786 121397 EPSG:3857:18 111520 146392 71573 242794 EPSG:3857:19 223041 292785 143146 485589 EPSG:3857:20 446082 585571 286293 971179 EPSG:3857:21 892165 1171142 572587 1942358 EPSG:3857:22 1784331 2342285 1145175 3884717 EPSG:3857:23 3568663 4684570 2290351 7769435 EPSG:3857:24 7137327 9369141 4580703 15538871 EPSG:3857:25 14274655 18738283 9161407 31077743 EPSG:3857:26 28549311 37476567 18322815 62155486 EPSG:3857:27 57098623 74953134 36645631 124310973 EPSG:3857:28 114197246 149906268 73291263 248621947 EPSG:3857:29 228394492 299812536 146582527 497243894 EPSG:3857:30 456788984 599625072 293165054 994487788 Yearly emissions of CO2 (short cycle organic Carbon) - 2018 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -55.89999999999222 179.99999999997954 81.19999999999999 wesr_climat:v60_CO2_org_short-cycle_C_2018_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 2 22 0 31 EPSG:3857:6 5 44 0 63 EPSG:3857:7 11 88 0 127 EPSG:3857:8 23 176 0 255 EPSG:3857:9 47 352 0 511 EPSG:3857:10 94 704 0 1023 EPSG:3857:11 188 1409 0 2047 EPSG:3857:12 376 2818 0 4095 EPSG:3857:13 752 5637 0 8191 EPSG:3857:14 1504 11274 0 16383 EPSG:3857:15 3008 22548 0 32767 EPSG:3857:16 6017 45096 0 65535 EPSG:3857:17 12035 90192 0 131071 EPSG:3857:18 24070 180384 0 262143 EPSG:3857:19 48141 360768 0 524287 EPSG:3857:20 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49296910 369426548 0 536870911 EPSG:3857:30 98593821 738853097 0 1073741824 wayport_2020 -13.302697292288268 8.485153978191043 -13.28362142178019 8.49912097880625 sand:wayport_2020 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 14 14 EPSG:3857:6 30 30 29 29 EPSG:3857:7 60 60 59 59 EPSG:3857:8 121 121 118 118 EPSG:3857:9 243 243 237 237 EPSG:3857:10 487 487 474 474 EPSG:3857:11 975 975 948 948 EPSG:3857:12 1950 1951 1896 1896 EPSG:3857:13 3901 3902 3793 3793 EPSG:3857:14 7803 7804 7586 7587 EPSG:3857:15 15607 15608 15173 15174 EPSG:3857:16 31215 31217 30346 30349 EPSG:3857:17 62430 62435 60692 60699 EPSG:3857:18 124860 124870 121385 121399 EPSG:3857:19 249720 249741 242770 242798 EPSG:3857:20 499441 499482 485541 485596 EPSG:3857:21 998882 998964 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242770 242798 EPSG:4326:19 237388 237429 485541 485596 EPSG:4326:20 474777 474858 971082 971193 EPSG:4326:21 949554 949716 1942164 1942386 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 14 14 EPSG:3857:6 30 30 29 29 EPSG:3857:7 60 60 59 59 EPSG:3857:8 121 121 118 118 EPSG:3857:9 243 243 237 237 EPSG:3857:10 487 487 474 474 EPSG:3857:11 975 975 948 948 EPSG:3857:12 1950 1951 1896 1896 EPSG:3857:13 3901 3902 3793 3793 EPSG:3857:14 7803 7804 7586 7587 EPSG:3857:15 15607 15608 15173 15174 EPSG:3857:16 31215 31217 30346 30349 EPSG:3857:17 62430 62435 60692 60699 EPSG:3857:18 124860 124870 121385 121399 EPSG:3857:19 249720 249741 242770 242798 EPSG:3857:20 499441 499482 485541 485596 EPSG:3857:21 998882 998964 971082 971193 EPSG:3857:22 1997764 1997929 1942164 1942386 EPSG:3857:23 3995529 3995858 3884328 3884773 EPSG:3857:24 7991059 7991717 7768657 7769546 EPSG:3857:25 15982119 15983435 15537314 15539092 EPSG:3857:26 31964238 31966870 31074629 31078185 EPSG:3857:27 63928476 63933741 62149258 62156370 EPSG:3857:28 127856953 127867483 124298517 124312741 EPSG:3857:29 255713907 255734967 248597035 248625483 EPSG:3857:30 511427815 511469935 497194071 497250967 Self-calibrating Palmer Drought Severity Index (scPDSI) 1971-1980 (CRU) This layer shows the average values over the 1971 to 1980 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_71_80_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combined map of natural hazards The multi-risk assessment integrates risks related to drought, flooding, wildfires, and extreme heat through a multi-criteria analysis by AHP, weighted by participatory surveys with local institutions such as the CSE, the DPGI, the ANAT, and the DGPRE. This approach makes it possible to prioritize risks according to their perceived impact and frequency of occurrence. Densely populated areas and areas with rich ecosystems have medium to high multi-risk levels. These areas are systematically characterized by medium to high levels of risk related to flooding, wildfires, and extreme heat. -13.239460488881921 12.307817707721565 -11.342398271878315 13.461074869474206 risk_southeast_senegal:multirisk image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242357 244079 242862 245625 EPSG:3857:20 484714 488159 485725 491250 EPSG:3857:21 969428 976319 971450 982501 EPSG:3857:22 1938856 1952639 1942901 1965003 EPSG:3857:23 3877712 3905279 3885802 3930006 EPSG:3857:24 7755424 7810559 7771604 7860013 EPSG:3857:25 15510848 15621118 15543208 15720027 EPSG:3857:26 31021697 31242237 31086417 31440055 EPSG:3857:27 62043395 62484474 62172835 62880111 EPSG:3857:28 124086790 124968948 124345670 125760222 EPSG:3857:29 248173580 249937896 248691341 251520445 EPSG:3857:30 496347160 499875793 497382682 503040891 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491250 EPSG:4326:20 445871 452589 971450 982501 EPSG:4326:21 891743 905179 1942901 1965003 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242357 244079 242862 245625 EPSG:3857:20 484714 488159 485725 491250 EPSG:3857:21 969428 976319 971450 982501 EPSG:3857:22 1938856 1952639 1942901 1965003 EPSG:3857:23 3877712 3905279 3885802 3930006 EPSG:3857:24 7755424 7810559 7771604 7860013 EPSG:3857:25 15510848 15621118 15543208 15720027 EPSG:3857:26 31021697 31242237 31086417 31440055 EPSG:3857:27 62043395 62484474 62172835 62880111 EPSG:3857:28 124086790 124968948 124345670 125760222 EPSG:3857:29 248173580 249937896 248691341 251520445 EPSG:3857:30 496347160 499875793 497382682 503040891 Self-calibrating Palmer Drought Severity Index (scPDSI) 2013 (CRU) This layer shows the average values for 2013 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_13_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 mosaic_2020_kamituga_west 28.166978184291047 -3.075687270143314 28.181206954060514 -3.0642747063483102 rs_for_asgm:mosaic_2020_kamituga_west image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 520 592 592 EPSG:3857:11 1041 1041 1184 1184 EPSG:3857:12 2082 2083 2368 2368 EPSG:3857:13 4165 4166 4736 4737 EPSG:3857:14 8331 8332 9473 9474 EPSG:3857:15 16663 16664 18947 18949 EPSG:3857:16 33326 33328 37895 37898 EPSG:3857:17 66652 66656 75791 75796 EPSG:3857:18 133304 133312 151582 151592 EPSG:3857:19 266608 266625 303165 303185 EPSG:3857:20 533217 533250 606330 606371 EPSG:3857:21 1066435 1066501 1212660 1212743 EPSG:3857:22 2132870 2133003 2425321 2425486 EPSG:3857:23 4265740 4266007 4850642 4850973 EPSG:3857:24 8531481 8532014 9701284 9701947 EPSG:3857:25 17062963 17064028 19402568 19403894 EPSG:3857:26 34125926 34128057 38805137 38807789 EPSG:3857:27 68251853 68256114 77610274 77615579 EPSG:3857:28 136503706 136512228 155220549 155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 264 592 592 EPSG:4326:10 529 529 1184 1184 EPSG:4326:11 1058 1058 2368 2368 EPSG:4326:12 2117 2117 4736 4737 EPSG:4326:13 4235 4235 9473 9474 EPSG:4326:14 8470 8471 18947 18949 EPSG:4326:15 16941 16943 37895 37898 EPSG:4326:16 33883 33887 75791 75796 EPSG:4326:17 67767 67775 151582 151592 EPSG:4326:18 135534 135551 303165 303185 EPSG:4326:19 271069 271102 606330 606371 EPSG:4326:20 542138 542205 1212660 1212743 EPSG:4326:21 1084277 1084410 2425321 2425486 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 520 592 592 EPSG:3857:11 1041 1041 1184 1184 EPSG:3857:12 2082 2083 2368 2368 EPSG:3857:13 4165 4166 4736 4737 EPSG:3857:14 8331 8332 9473 9474 EPSG:3857:15 16663 16664 18947 18949 EPSG:3857:16 33326 33328 37895 37898 EPSG:3857:17 66652 66656 75791 75796 EPSG:3857:18 133304 133312 151582 151592 EPSG:3857:19 266608 266625 303165 303185 EPSG:3857:20 533217 533250 606330 606371 EPSG:3857:21 1066435 1066501 1212660 1212743 EPSG:3857:22 2132870 2133003 2425321 2425486 EPSG:3857:23 4265740 4266007 4850642 4850973 EPSG:3857:24 8531481 8532014 9701284 9701947 EPSG:3857:25 17062963 17064028 19402568 19403894 EPSG:3857:26 34125926 34128057 38805137 38807789 EPSG:3857:27 68251853 68256114 77610274 77615579 EPSG:3857:28 136503706 136512228 155220549 155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 Summer precipitations change (%) for the period 2020 - 2039 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_jja_NEARREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Flood Population Exposure (People/Year) -180.0 -90.0 179.99999999985602 83.99999999993042 wesr_risk:fl1010ipey image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097151 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388608 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217727 EPSG:3857:28 8240909 268435455 0 268435456 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34952 1048575 0 2097151 EPSG:4326:21 69905 2097151 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097152 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388607 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217728 EPSG:3857:28 8240909 268435455 0 268435455 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741824 SDG 15.3.1 Land Degradation - Sahel This dataset is clipped for the Sahel region from the original SDG15.3.1 Land Degradation global dataset.<br> The original dataset has been generated using the Trends.Earth model to asses Land Degradation according to the UN Metadata Guideline for SDG. <br><br> More information on <a href= "http://trends.earth/docs/en/" target="_blank">Trends.Earth</a>. <br> More information on <a href="https://knowledge.unccd.int/topics/sustainable-development-goals-sdgs/sdg-indicator-1531" target= "_blank">Land Degradation</a>. <br> More information on <a href="https://unstats.un.org/sdgs/metadata/files/Metadata-15-03-01.pdf" target="_blank">SDG15.3.1</a>. <br> <br> Generated using the GEOEssential VLab -25.357194800661915 -0.0336866878891016 51.4128293216946 37.54284158619938 UN_Sahel:sdg1531_sahel_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 3 4 3 5 EPSG:3857:4 6 8 6 10 EPSG:3857:5 12 16 13 20 EPSG:3857:6 24 32 27 41 EPSG:3857:7 49 64 54 82 EPSG:3857:8 99 128 109 164 EPSG:3857:9 198 256 219 329 EPSG:3857:10 396 512 439 658 EPSG:3857:11 793 1024 879 1316 EPSG:3857:12 1586 2048 1759 2632 EPSG:3857:13 3173 4096 3518 5265 EPSG:3857:14 6346 8193 7037 10531 EPSG:3857:15 12692 16387 14075 21063 EPSG:3857:16 25384 32774 28151 42127 EPSG:3857:17 50768 65548 56303 84254 EPSG:3857:18 101537 131096 112607 168509 EPSG:3857:19 203075 262193 225214 337019 EPSG:3857:20 406150 524386 450429 674038 EPSG:3857:21 812300 1048772 900859 1348077 EPSG:3857:22 1624601 2097544 1801719 2696154 EPSG:3857:23 3249203 4195088 3603438 5392309 EPSG:3857:24 6498406 8390177 7206877 10784619 EPSG:3857:25 12996812 16780355 14413754 21569239 EPSG:3857:26 25993624 33560711 28827508 43138478 EPSG:3857:27 51987248 67121423 57655016 86276956 EPSG:3857:28 103974496 134242846 115310033 172553912 EPSG:3857:29 207948992 268485693 230620066 345107824 EPSG:3857:30 415897985 536971386 461240132 690215648 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 1 2 3 5 EPSG:4326:3 2 4 6 10 EPSG:4326:4 4 8 13 20 EPSG:4326:5 9 16 27 41 EPSG:4326:6 18 32 54 82 EPSG:4326:7 37 64 109 164 EPSG:4326:8 74 128 219 329 EPSG:4326:9 149 256 439 658 EPSG:4326:10 298 512 879 1316 EPSG:4326:11 596 1024 1759 2632 EPSG:4326:12 1193 2048 3518 5265 EPSG:4326:13 2387 4097 7037 10531 EPSG:4326:14 4774 8195 14075 21063 EPSG:4326:15 9549 16390 28151 42127 EPSG:4326:16 19099 32780 56303 84254 EPSG:4326:17 38198 65560 112607 168509 EPSG:4326:18 76396 131121 225214 337019 EPSG:4326:19 152792 262242 450429 674038 EPSG:4326:20 305585 524484 900859 1348077 EPSG:4326:21 611170 1048968 1801719 2696154 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 3 4 3 5 EPSG:3857:4 6 8 6 10 EPSG:3857:5 12 16 13 20 EPSG:3857:6 24 32 27 41 EPSG:3857:7 49 64 54 82 EPSG:3857:8 99 128 109 164 EPSG:3857:9 198 256 219 329 EPSG:3857:10 396 512 439 658 EPSG:3857:11 793 1024 879 1316 EPSG:3857:12 1586 2048 1759 2632 EPSG:3857:13 3173 4096 3518 5265 EPSG:3857:14 6346 8193 7037 10531 EPSG:3857:15 12692 16387 14075 21063 EPSG:3857:16 25384 32774 28151 42127 EPSG:3857:17 50768 65548 56303 84254 EPSG:3857:18 101537 131096 112607 168509 EPSG:3857:19 203075 262193 225214 337019 EPSG:3857:20 406150 524386 450429 674038 EPSG:3857:21 812300 1048772 900859 1348077 EPSG:3857:22 1624601 2097544 1801719 2696154 EPSG:3857:23 3249203 4195088 3603438 5392309 EPSG:3857:24 6498406 8390177 7206877 10784619 EPSG:3857:25 12996812 16780355 14413754 21569239 EPSG:3857:26 25993624 33560711 28827508 43138478 EPSG:3857:27 51987248 67121423 57655016 86276956 EPSG:3857:28 103974496 134242846 115310033 172553912 EPSG:3857:29 207948992 268485693 230620066 345107824 EPSG:3857:30 415897985 536971386 461240132 690215648 20160708Classes Classification of a Sentinel-2 image with post-processing using field knowledge. This research was funded by the Copernicus RawMatCop programme, through funding from EIT RawMaterials and the European Commission DG Internal Market, Industry, Entrepreneurship and SMEs (DG GROW). https://eitrawmaterials.eu/eit-rm-academy/rawmatcop/, in the scope of project CopX: "Geospatial mining transparency through Copernicus and MapX" -74.86103149540197 7.565680150087606 -74.77551708391071 7.624603274629289 UNILIEGE:20160708Classes image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125503 125546 76559 76622 EPSG:3857:19 251006 251093 153119 153244 EPSG:3857:20 502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7497 7503 9569 9577 EPSG:4326:15 14995 15006 19139 19155 EPSG:4326:16 29991 30013 38279 38311 EPSG:4326:17 59983 60026 76559 76622 EPSG:4326:18 119967 120053 153119 153244 EPSG:4326:19 239935 240107 306239 306488 EPSG:4326:20 479871 480214 612478 612977 EPSG:4326:21 959742 960429 1224957 1225954 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 0 0 EPSG:900913:2 1 1 1 1 EPSG:900913:3 3 3 2 2 EPSG:900913:4 7 7 4 4 EPSG:900913:5 15 15 9 9 EPSG:900913:6 30 30 18 18 EPSG:900913:7 61 61 37 37 EPSG:900913:8 122 122 74 74 EPSG:900913:9 245 245 149 149 EPSG:900913:10 490 490 299 299 EPSG:900913:11 980 980 598 598 EPSG:900913:12 1960 1961 1196 1197 EPSG:900913:13 3921 3923 2392 2394 EPSG:900913:14 7843 7846 4784 4788 EPSG:900913:15 15687 15693 9569 9577 EPSG:900913:16 31375 31386 19139 19155 EPSG:900913:17 62751 62773 38279 38311 EPSG:900913:18 125503 125546 76559 76622 EPSG:900913:19 251006 251093 153119 153244 EPSG:900913:20 502013 502187 306239 306488 EPSG:900913:21 1004027 1004374 612478 612977 EPSG:900913:22 2008055 2008748 1224957 1225954 EPSG:900913:23 4016111 4017496 2449915 2451908 EPSG:900913:24 8032222 8034992 4899831 4903816 EPSG:900913:25 16064444 16069985 9799662 9807632 EPSG:900913:26 32128889 32139970 19599324 19615265 EPSG:900913:27 64257778 64279941 39198648 39230530 EPSG:900913:28 128515557 128559882 78397297 78461061 EPSG:900913:29 257031114 257119764 156794594 156922122 EPSG:900913:30 514062228 514239528 313589188 313844245 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125503 125546 76559 76622 EPSG:3857:19 251006 251093 153119 153244 EPSG:3857:20 502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 Global Emissions CO 1990 - EDGARD Global Emissions CO 1990 - EDGARD Global Emissions EDGAR v4.3.1 (January 2016) In EDGARv4.3.1 emissions are calculated for gaseous and particulate air pollutants per sector and country. For the energy related sectors the activity data are mainly based on the energy balance statistics of IEA (2014) Emission gridmaps are expressed in ton substance / 0.1degree x 0.1degree / year -180.0 -77.95 179.95 88.15000000000002 grid_data_core:edg90_co image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 Spectral Acceleration 0.5 Sec 1500 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_05_s_1500_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 site_0060_Landsat_tom -10.858176899138206 8.079534492312552 -10.189521743955197 8.79879002262406 test_imagemosaic_tom:site_0060_Landsat_tom image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 30 30 EPSG:4326:6 28 29 60 60 EPSG:4326:7 57 58 120 120 EPSG:4326:8 115 116 240 241 EPSG:4326:9 230 233 481 483 EPSG:4326:10 461 466 962 966 EPSG:4326:11 923 932 1924 1932 EPSG:4326:12 1847 1864 3848 3864 EPSG:4326:13 3695 3728 7697 7728 EPSG:4326:14 7391 7456 15395 15456 EPSG:4326:15 14782 14913 30791 30913 EPSG:4326:16 29564 29826 61582 61826 EPSG:4326:17 59128 59652 123165 123652 EPSG:4326:18 118257 119305 246330 247304 EPSG:4326:19 236515 238610 492661 494608 EPSG:4326:20 473031 477221 985322 989217 EPSG:4326:21 946062 954442 1970645 1978435 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 Precipitation trend (% of change) 2008-2018 in Somalia (ICPAC) Seasonal trends expressed as percentage of change of rainfall time series (2008-2018) reconstructed from station observations, remote sensing and other proxies. The rainfall data were created by combining quality-controlled station observations with satellite rainfall estimates and were reconstructed over land areas on a 0.05 x 0.05 lat/lon grid. Data downloaded from http://digilib.icpac.net/maproom/Climatology/Climate_Analysis/Seasonal_Trend.html.en 40.93000030517578 -1.7000011578202248 51.43000124394894 11.999999046325684 wesr_cca:SOM_ICPAC_prec_trend_perc_Jan_Dec_2008_2018_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 7 8 9 10 EPSG:3857:5 14 16 19 20 EPSG:3857:6 29 32 39 41 EPSG:3857:7 59 64 78 82 EPSG:3857:8 119 129 157 164 EPSG:3857:9 238 258 314 329 EPSG:3857:10 477 516 628 658 EPSG:3857:11 955 1033 1256 1316 EPSG:3857:12 1910 2067 2513 2633 EPSG:3857:13 3820 4134 5027 5266 EPSG:3857:14 7641 8269 10054 10532 EPSG:3857:15 15283 16538 20109 21065 EPSG:3857:16 30567 33077 40219 42130 EPSG:3857:17 61134 66155 80438 84261 EPSG:3857:18 122269 132310 160876 168522 EPSG:3857:19 244538 264620 321752 337044 EPSG:3857:20 489077 529240 643505 674088 EPSG:3857:21 978154 1058480 1287010 1348177 EPSG:3857:22 1956308 2116961 2574021 2696354 EPSG:3857:23 3912616 4233922 5148042 5392709 EPSG:3857:24 7825233 8467845 10296084 10785419 EPSG:3857:25 15650467 16935690 20592168 21570839 EPSG:3857:26 31300934 33871381 41184337 43141679 EPSG:3857:27 62601868 67742763 82368674 86283358 EPSG:3857:28 125203737 135485526 164737348 172566716 EPSG:3857:29 250407474 270971053 329474696 345133432 EPSG:3857:30 500814949 541942107 658949393 690266865 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 5 EPSG:4326:3 3 4 9 10 EPSG:4326:4 6 8 19 20 EPSG:4326:5 13 16 39 41 EPSG:4326:6 27 32 78 82 EPSG:4326:7 55 65 157 164 EPSG:4326:8 110 130 314 329 EPSG:4326:9 221 260 628 658 EPSG:4326:10 443 521 1256 1316 EPSG:4326:11 887 1043 2513 2633 EPSG:4326:12 1774 2086 5027 5266 EPSG:4326:13 3549 4173 10054 10532 EPSG:4326:14 7099 8346 20109 21065 EPSG:4326:15 14199 16693 40219 42130 EPSG:4326:16 28398 33386 80438 84261 EPSG:4326:17 56797 66773 160876 168522 EPSG:4326:18 113595 133547 321752 337044 EPSG:4326:19 227191 267095 643505 674088 EPSG:4326:20 454382 534191 1287010 1348177 EPSG:4326:21 908765 1068382 2574021 2696354 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 7 8 9 10 EPSG:3857:5 14 16 19 20 EPSG:3857:6 29 32 39 41 EPSG:3857:7 59 64 78 82 EPSG:3857:8 119 129 157 164 EPSG:3857:9 238 258 314 329 EPSG:3857:10 477 516 628 658 EPSG:3857:11 955 1033 1256 1316 EPSG:3857:12 1910 2067 2513 2633 EPSG:3857:13 3820 4134 5027 5266 EPSG:3857:14 7641 8269 10054 10532 EPSG:3857:15 15283 16538 20109 21065 EPSG:3857:16 30567 33077 40219 42130 EPSG:3857:17 61134 66155 80438 84261 EPSG:3857:18 122269 132310 160876 168522 EPSG:3857:19 244538 264620 321752 337044 EPSG:3857:20 489077 529240 643505 674088 EPSG:3857:21 978154 1058480 1287010 1348177 EPSG:3857:22 1956308 2116961 2574021 2696354 EPSG:3857:23 3912616 4233922 5148042 5392709 EPSG:3857:24 7825233 8467845 10296084 10785419 EPSG:3857:25 15650467 16935690 20592168 21570839 EPSG:3857:26 31300934 33871381 41184337 43141679 EPSG:3857:27 62601868 67742763 82368674 86283358 EPSG:3857:28 125203737 135485526 164737348 172566716 EPSG:3857:29 250407474 270971053 329474696 345133432 EPSG:3857:30 500814949 541942107 658949393 690266865 site_0336_19860908_visual_nearest 21.804453393351142 2.163950346428799 22.972377367092143 3.360478793316272 hotspots:site_0336_19860908_visual_nearest image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 15 15 35 36 EPSG:4326:6 30 31 71 72 EPSG:4326:7 61 62 143 144 EPSG:4326:8 123 124 287 288 EPSG:4326:9 246 249 574 577 EPSG:4326:10 492 499 1148 1154 EPSG:4326:11 985 999 2296 2309 EPSG:4326:12 1971 1998 4592 4618 EPSG:4326:13 3943 3997 9184 9237 EPSG:4326:14 7886 7995 18368 18474 EPSG:4326:15 15772 15990 36737 36949 EPSG:4326:16 31544 31980 73474 73899 EPSG:4326:17 63088 63960 146949 147799 EPSG:4326:18 126177 127920 293899 295599 EPSG:4326:19 252355 255841 587798 591199 EPSG:4326:20 504711 511682 1175596 1182399 EPSG:4326:21 1009423 1023364 2351192 2364799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 Mean temperatures 2019 - Central African Republic Mean observed temperatures in 2019 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2019_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html 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Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_djf_MIDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 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3905853 3784334 3931693 EPSG:3857:24 7597882 7811707 7568669 7863387 EPSG:3857:25 15195765 15623414 15137338 15726775 EPSG:3857:26 30391530 31246829 30274677 31453550 EPSG:3857:27 60783061 62493658 60549355 62907100 EPSG:3857:28 121566123 124987316 121098711 125814200 EPSG:3857:29 243132247 249974633 242197423 251628400 EPSG:3857:30 486264495 499949266 484394847 503256800 Human Footprint 2009 (Terrestrial) Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11. 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4075444 4304766 4983585 5171069 EPSG:3857:24 8150888 8609532 9967170 10342138 EPSG:3857:25 16301776 17219065 19934341 20684277 EPSG:3857:26 32603552 34438131 39868683 41368555 EPSG:3857:27 65207104 68876263 79737367 82737111 EPSG:3857:28 130414208 137752526 159474735 165474223 EPSG:3857:29 260828416 275505053 318949470 330948446 EPSG:3857:30 521656833 551010106 637898940 661896892 npl_hillshadedd 84.41626247481628 26.911259226494117 86.72420414023092 28.75255357860686 MAPX_nd:npl_hillshadedd image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 11 11 EPSG:3857:5 13 13 23 23 EPSG:3857:6 26 27 47 47 EPSG:3857:7 53 54 94 94 EPSG:3857:8 106 108 188 189 EPSG:3857:9 213 216 376 379 EPSG:3857:10 426 432 752 758 EPSG:3857:11 853 864 1504 1517 EPSG:3857:12 1706 1729 3008 3034 EPSG:3857:13 3412 3459 6016 6069 EPSG:3857:14 6824 6919 12033 12138 EPSG:3857:15 13649 13839 24067 24277 EPSG:3857:16 27299 27678 48135 48555 EPSG:3857:17 54598 55356 96271 97111 EPSG:3857:18 109196 110712 192542 194222 EPSG:3857:19 218393 221425 385084 388445 EPSG:3857:20 436786 442851 770168 776890 EPSG:3857:21 873572 885702 1540336 1553781 EPSG:3857:22 1747144 1771405 3080672 3107562 EPSG:3857:23 3494289 3542810 6161345 6215124 EPSG:3857:24 6988579 7085621 12322690 12430248 EPSG:3857:25 13977158 14171242 24645381 24860497 EPSG:3857:26 27954316 28342484 49290763 49720995 EPSG:3857:27 55908632 56684968 98581527 99441990 EPSG:3857:28 111817264 113369936 197163055 198883981 EPSG:3857:29 223634528 226739872 394326111 397767963 EPSG:3857:30 447269057 453479745 788652222 795535926 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 2 2 11 11 EPSG:4326:4 5 5 23 23 EPSG:4326:5 10 11 47 47 EPSG:4326:6 21 22 94 94 EPSG:4326:7 43 44 188 189 EPSG:4326:8 87 89 376 379 EPSG:4326:9 174 179 752 758 EPSG:4326:10 348 358 1504 1517 EPSG:4326:11 696 717 3008 3034 EPSG:4326:12 1393 1435 6016 6069 EPSG:4326:13 2787 2871 12033 12138 EPSG:4326:14 5574 5742 24067 24277 EPSG:4326:15 11149 11484 48135 48555 EPSG:4326:16 22299 22969 96271 97111 EPSG:4326:17 44599 45939 192542 194222 EPSG:4326:18 89198 91879 385084 388445 EPSG:4326:19 178396 183759 770168 776890 EPSG:4326:20 356792 367518 1540336 1553781 EPSG:4326:21 713584 735037 3080672 3107562 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 3 3 5 5 EPSG:900913:4 6 6 11 11 EPSG:900913:5 13 13 23 23 EPSG:900913:6 26 27 47 47 EPSG:900913:7 53 54 94 94 EPSG:900913:8 106 108 188 189 EPSG:900913:9 213 216 376 379 EPSG:900913:10 426 432 752 758 EPSG:900913:11 853 864 1504 1517 EPSG:900913:12 1706 1729 3008 3034 EPSG:900913:13 3412 3459 6016 6069 EPSG:900913:14 6824 6919 12033 12138 EPSG:900913:15 13649 13839 24067 24277 EPSG:900913:16 27299 27678 48135 48555 EPSG:900913:17 54598 55356 96271 97111 EPSG:900913:18 109196 110712 192542 194222 EPSG:900913:19 218393 221425 385084 388445 EPSG:900913:20 436786 442851 770168 776890 EPSG:900913:21 873572 885702 1540336 1553781 EPSG:900913:22 1747144 1771405 3080672 3107562 EPSG:900913:23 3494289 3542810 6161345 6215124 EPSG:900913:24 6988579 7085621 12322690 12430248 EPSG:900913:25 13977158 14171242 24645381 24860497 EPSG:900913:26 27954316 28342484 49290763 49720995 EPSG:900913:27 55908632 56684968 98581527 99441990 EPSG:900913:28 111817264 113369936 197163055 198883981 EPSG:900913:29 223634528 226739872 394326111 397767963 EPSG:900913:30 447269057 453479745 788652222 795535926 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 11 11 EPSG:3857:5 13 13 23 23 EPSG:3857:6 26 27 47 47 EPSG:3857:7 53 54 94 94 EPSG:3857:8 106 108 188 189 EPSG:3857:9 213 216 376 379 EPSG:3857:10 426 432 752 758 EPSG:3857:11 853 864 1504 1517 EPSG:3857:12 1706 1729 3008 3034 EPSG:3857:13 3412 3459 6016 6069 EPSG:3857:14 6824 6919 12033 12138 EPSG:3857:15 13649 13839 24067 24277 EPSG:3857:16 27299 27678 48135 48555 EPSG:3857:17 54598 55356 96271 97111 EPSG:3857:18 109196 110712 192542 194222 EPSG:3857:19 218393 221425 385084 388445 EPSG:3857:20 436786 442851 770168 776890 EPSG:3857:21 873572 885702 1540336 1553781 EPSG:3857:22 1747144 1771405 3080672 3107562 EPSG:3857:23 3494289 3542810 6161345 6215124 EPSG:3857:24 6988579 7085621 12322690 12430248 EPSG:3857:25 13977158 14171242 24645381 24860497 EPSG:3857:26 27954316 28342484 49290763 49720995 EPSG:3857:27 55908632 56684968 98581527 99441990 EPSG:3857:28 111817264 113369936 197163055 198883981 EPSG:3857:29 223634528 226739872 394326111 397767963 EPSG:3857:30 447269057 453479745 788652222 795535926 Summer temperature change (°C) for the period 2040 - 2059 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_jja_MIDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Combination Tropical cyclone surge/ Sea grasses at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_sea6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average year precipitations anomalies (2011-2020) over 1991-2020 climatology Average year precipitations anomalies in mm across the period 2011-2020 calculated over the average precipitations per year in the period 1991-2020 (climatology). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_11_20_anom9120 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Total built-up surface in 2015 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_2015 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Automn temperature change (°C) for the period 2020 - 2039 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_son_NEARREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Total built-up surface in 2010 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_2010 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Flooded areas in Kedougou between 2015 and 2024 Flood zone mapping is based on the analysis of Landsat satellite images (series 5, 7 and 8) covering the three decadal periods of the study (1995-2024). These data, available on GEE, offer spectral bands suitable for water detection. The green and short-wave infrared spectral bands were selected to calculate the Modified Normalized Difference Water Index (MNDWI), while the red and near-infrared (NIR) bands were used in the case of another hazard to calculate the NDVI to eliminate false detections linked to vegetation. -13.243723483393213 12.296539942972935 -11.335952171241116 13.472448719878967 risk_southeast_senegal:flood_2015_2024 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60584 61024 60714 61408 EPSG:3857:18 121169 122048 121428 122817 EPSG:3857:19 242339 244096 242856 245634 EPSG:3857:20 484679 488193 485712 491269 EPSG:3857:21 969359 976387 971425 982539 EPSG:3857:22 1938719 1952774 1942851 1965078 EPSG:3857:23 3877439 3905548 3885702 3930157 EPSG:3857:24 7754879 7811097 7771405 7860314 EPSG:3857:25 15509758 15622194 15542811 15720628 EPSG:3857:26 31019517 31244388 31085623 31441257 EPSG:3857:27 62039034 62488777 62171246 62882514 EPSG:3857:28 124078069 124977555 124342492 125765029 EPSG:3857:29 248156138 249955110 248684984 251530058 EPSG:3857:30 496312277 499910220 497369968 503060117 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 221 474 479 EPSG:4326:10 435 442 948 959 EPSG:4326:11 870 884 1897 1919 EPSG:4326:12 1741 1768 3794 3838 EPSG:4326:13 3482 3536 7589 7676 EPSG:4326:14 6965 7072 15178 15352 EPSG:4326:15 13931 14145 30357 30704 EPSG:4326:16 27862 28290 60714 61408 EPSG:4326:17 55725 56581 121428 122817 EPSG:4326:18 111451 113163 242856 245634 EPSG:4326:19 222902 226327 485712 491269 EPSG:4326:20 445805 452655 971425 982539 EPSG:4326:21 891610 905310 1942851 1965078 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60584 61024 60714 61408 EPSG:3857:18 121169 122048 121428 122817 EPSG:3857:19 242339 244096 242856 245634 EPSG:3857:20 484679 488193 485712 491269 EPSG:3857:21 969359 976387 971425 982539 EPSG:3857:22 1938719 1952774 1942851 1965078 EPSG:3857:23 3877439 3905548 3885702 3930157 EPSG:3857:24 7754879 7811097 7771405 7860314 EPSG:3857:25 15509758 15622194 15542811 15720628 EPSG:3857:26 31019517 31244388 31085623 31441257 EPSG:3857:27 62039034 62488777 62171246 62882514 EPSG:3857:28 124078069 124977555 124342492 125765029 EPSG:3857:29 248156138 249955110 248684984 251530058 EPSG:3857:30 496312277 499910220 497369968 503060117 tsm_mambo_bado_20200116 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20200116 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 Ruminant livestock density (2010) - FAO The layer shows the density of livestock in LSU/km2 for the year 2010. It is derived from the Land and Water Resources theme of the GAEZv4 database of FAO. Livestock distribution data contained in GAEZ v4 were provided by the 30 arc-second resolution raster maps of the Gridded Livestock of the World database (GLW 2.01; released in May 2014). The GLW includes separate layers with the number of cattle, sheep, goats, pigs and poultry. The example included in the portal refers to ruminant (cattle, sheep, goats) livestock density and can, for instance, be used to compute land requirements for grazing livestock and to estimate the amount of grass/shrub land that may be available for other uses. -180.0 -90.0 180.0 90.0 unccd:TLU30s_AD_2010_v2_1_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tsunami/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_for6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_mambo_bado_20201201 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20201201 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 Human footprint 2005 Brooke A. Williams, Oscar Venter, James R. Allan, Scott C. Atkinson, Jose A. Rehbein, Michelle S. Ward, Moreno Di Marco, Hedley S. Grantham, Jamison Ervin, Scott Goetz, Andrew J. Hansen, Patrick Jantz, Rajeev Pillay, Susana Rodríguez-Buriticá, Christina Supples, Anne L. S. Virnig, James E.M. Watson. (2020). Change in terrestrial human footprint drives continued loss of intact ecosystems. OneEarth. http://dx.doi.org/10.2139/ssrn.3600547 -179.99999995447251 -65.25013301721049 179.99661098079287 89.89762321520959 wesr_biodiversity:hfp2005_merisINT image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12147 0 16383 EPSG:3857:15 0 24294 0 32767 EPSG:3857:16 0 48589 0 65535 EPSG:3857:17 0 97178 0 131070 EPSG:3857:18 0 194356 0 262141 EPSG:3857:19 0 388713 0 524283 EPSG:3857:20 0 777426 0 1048566 EPSG:3857:21 0 1554852 0 2097132 EPSG:3857:22 -1 3109705 0 4194264 EPSG:3857:23 -1 6219410 0 8388529 EPSG:3857:24 0 12438820 0 16777058 EPSG:3857:25 0 24877640 0 33554116 EPSG:3857:26 0 49755280 0 67108232 EPSG:3857:27 0 99510561 0 134216464 EPSG:3857:28 -1 199021122 0 268432928 EPSG:3857:29 0 398042245 0 536865857 EPSG:3857:30 0 796084491 0 1073731715 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 55 0 127 EPSG:4326:7 0 110 0 255 EPSG:4326:8 0 220 0 511 EPSG:4326:9 0 441 0 1023 EPSG:4326:10 0 883 0 2047 EPSG:4326:11 1 1766 0 4095 EPSG:4326:12 2 3532 0 8191 EPSG:4326:13 4 7065 0 16383 EPSG:4326:14 9 14131 0 32767 EPSG:4326:15 18 28262 0 65535 EPSG:4326:16 37 56524 0 131070 EPSG:4326:17 74 113049 0 262141 EPSG:4326:18 149 226099 0 524283 EPSG:4326:19 298 452198 0 1048566 EPSG:4326:20 596 904397 0 2097132 EPSG:4326:21 1192 1808795 0 4194264 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12147 0 16383 EPSG:3857:15 0 24294 0 32767 EPSG:3857:16 0 48589 0 65535 EPSG:3857:17 0 97178 0 131070 EPSG:3857:18 0 194356 0 262141 EPSG:3857:19 0 388713 0 524283 EPSG:3857:20 0 777426 0 1048566 EPSG:3857:21 -1 1554852 0 2097132 EPSG:3857:22 -1 3109705 0 4194264 EPSG:3857:23 0 6219410 0 8388529 EPSG:3857:24 0 12438820 0 16777058 EPSG:3857:25 0 24877640 0 33554116 EPSG:3857:26 0 49755280 0 67108232 EPSG:3857:27 -1 99510561 0 134216464 EPSG:3857:28 0 199021122 0 268432928 EPSG:3857:29 0 398042245 0 536865857 EPSG:3857:30 -1 796084491 0 1073731715 Yearly emissions of CH4 - 1990 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -88.79999999998984 179.99999999997954 90.0 wesr_climat:v60_CH4_1990_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 254 0 511 EPSG:4326:9 0 508 0 1023 EPSG:4326:10 0 1017 0 2047 EPSG:4326:11 0 2034 0 4095 EPSG:4326:12 0 4068 0 8191 EPSG:4326:13 0 8137 0 16383 EPSG:4326:14 0 16274 0 32767 EPSG:4326:15 0 32549 0 65535 EPSG:4326:16 0 65099 0 131071 EPSG:4326:17 0 130198 0 262143 EPSG:4326:18 0 260396 0 524287 EPSG:4326:19 0 520792 0 1048575 EPSG:4326:20 0 1041585 0 2097151 EPSG:4326:21 0 2083170 0 4194303 EPSG:900913 EPSG:3857_512 Ocean Pollution (Shipping Lanes, Ports) 2013 - KNB This data layer combines estimates of pollution coming from commercial shipping and from ports. As such, it is a combination of the shipping and port volume data layers, with the port volume data plumed to estimate pollution from commercial ports (with exponential decline in intensity from the port). Ocean-based pollution is assumed to derive from commercial and recreational ship activity. No data on global recreational ship activity currently exist, and therefore we modelled this driver to oceans using a combination of the commercial shipping traffic data and port data. The shipping data provide an estimate of the occurrence of ships at a particular location, and therefore an estimate of the amount of pollution they produce (via fuel leaks, oil discharge, waste disposal, etc.) that is unique from their contribution to ship strikes, etc. described above. We recognize that ocean currents can disperse this pollution into untraveled regions, but small-scale oceanography is known for only a few select locations around the world, and pollutants are likely to be most concentrated in high traffic areas. The dispersal of port-derived pollution was modelled as a diffusive plume with a maximum distance of 100 km. These plumes were not clipped to shallow regions as was done for Invasive Species. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS." -179.9999992159167 -89.94351550779915 179.99646810995122 89.94750143086456 unea_pollution:13_ocean_pollution_halpern_KNB_WGS84 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131070 EPSG:3857:18 0 262143 0 262141 EPSG:3857:19 0 524287 0 524282 EPSG:3857:20 0 1048575 0 1048565 EPSG:3857:21 0 2097151 0 2097131 EPSG:3857:22 -1 4194303 0 4194262 EPSG:3857:23 -1 8388607 0 8388525 EPSG:3857:24 0 16777215 0 16777051 EPSG:3857:25 0 33554431 0 33554102 EPSG:3857:26 0 67108863 0 67108205 EPSG:3857:27 0 134217727 0 134216411 EPSG:3857:28 -1 268435455 0 268432822 EPSG:3857:29 0 536870911 1 536865644 EPSG:3857:30 0 1073741823 2 1073731289 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 255 0 511 EPSG:4326:9 0 511 0 1023 EPSG:4326:10 0 1023 0 2047 EPSG:4326:11 0 2047 0 4095 EPSG:4326:12 1 4094 0 8191 EPSG:4326:13 2 8189 0 16383 EPSG:4326:14 4 16378 0 32767 EPSG:4326:15 9 32757 0 65535 EPSG:4326:16 19 65515 0 131070 EPSG:4326:17 38 131030 0 262141 EPSG:4326:18 76 262061 0 524282 EPSG:4326:19 152 524123 0 1048565 EPSG:4326:20 305 1048246 0 2097131 EPSG:4326:21 611 2096493 0 4194262 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 0 31 0 31 EPSG:900913:6 0 63 0 63 EPSG:900913:7 0 127 0 127 EPSG:900913:8 0 255 0 255 EPSG:900913:9 0 511 0 511 EPSG:900913:10 0 1023 0 1023 EPSG:900913:11 0 2047 0 2047 EPSG:900913:12 0 4095 0 4095 EPSG:900913:13 0 8191 0 8191 EPSG:900913:14 0 16383 0 16383 EPSG:900913:15 0 32767 0 32767 EPSG:900913:16 0 65535 0 65535 EPSG:900913:17 0 131071 0 131070 EPSG:900913:18 0 262143 0 262141 EPSG:900913:19 0 524287 0 524282 EPSG:900913:20 0 1048575 0 1048565 EPSG:900913:21 0 2097151 0 2097131 EPSG:900913:22 0 4194303 0 4194262 EPSG:900913:23 0 8388607 0 8388525 EPSG:900913:24 0 16777215 0 16777051 EPSG:900913:25 0 33554431 0 33554102 EPSG:900913:26 0 67108863 0 67108205 EPSG:900913:27 0 134217727 0 134216411 EPSG:900913:28 0 268435455 0 268432822 EPSG:900913:29 0 536870911 1 536865644 EPSG:900913:30 0 1073741823 2 1073731289 Phospate (spring) - WOA13 World Ocean Atlas 2013 (WOA13) is a long-term set of objectively analyzed climatologies of temperature, salinity, oxygen, phosphate, silicate, and nitrate for annual, seasonal, and monthly periods for the World Ocean. Data (at surface) are expressed in µmol/l -180.0 -78.0 180.0 90.0 unea_pollution:ph_spr image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 0 119 0 255 EPSG:4326:8 0 238 0 511 EPSG:4326:9 0 477 0 1023 EPSG:4326:10 0 955 0 2047 EPSG:4326:11 0 1911 0 4095 EPSG:4326:12 0 3822 0 8191 EPSG:4326:13 0 7645 0 16383 EPSG:4326:14 0 15291 0 32767 EPSG:4326:15 0 30583 0 65535 EPSG:4326:16 0 61166 0 131071 EPSG:4326:17 0 122333 0 262143 EPSG:4326:18 0 244667 0 524287 EPSG:4326:19 0 489335 0 1048575 EPSG:4326:20 0 978670 0 2097151 EPSG:4326:21 0 1957341 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 13 0 15 EPSG:900913:5 0 27 0 31 EPSG:900913:6 0 54 0 63 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31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 30 30 EPSG:4326:6 28 29 60 60 EPSG:4326:7 57 58 120 120 EPSG:4326:8 115 116 240 241 EPSG:4326:9 230 233 481 483 EPSG:4326:10 461 466 962 966 EPSG:4326:11 923 932 1924 1932 EPSG:4326:12 1847 1864 3848 3864 EPSG:4326:13 3695 3728 7697 7728 EPSG:4326:14 7391 7456 15395 15456 EPSG:4326:15 14782 14913 30791 30913 EPSG:4326:16 29564 29826 61582 61826 EPSG:4326:17 59128 59652 123165 123652 EPSG:4326:18 118257 119305 246330 247304 EPSG:4326:19 236515 238610 492661 494608 EPSG:4326:20 473031 477221 985322 989217 EPSG:4326:21 946062 954442 1970645 1978435 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 POP_FACEBOOK_Sangha_2019_Agg3km_UTM_opt 13.123883469599216 0.03537250815162562 16.999368548094683 2.7229136601610766 AccessMod:POP_FACEBOOK_Sangha_2019_Agg3km_UTM_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 15 15 17 17 EPSG:3857:6 31 31 34 35 EPSG:3857:7 63 63 68 70 EPSG:3857:8 126 127 137 140 EPSG:3857:9 252 255 274 280 EPSG:3857:10 504 511 549 560 EPSG:3857:11 1008 1023 1098 1120 EPSG:3857:12 2017 2047 2197 2241 EPSG:3857:13 4034 4095 4394 4482 EPSG:3857:14 8068 8190 8789 8965 EPSG:3857:15 16136 16380 17578 17931 EPSG:3857:16 32272 32761 35157 35862 EPSG:3857:17 64544 65523 70314 71725 EPSG:3857:18 129088 131046 140628 143450 EPSG:3857:19 258176 262092 281257 286901 EPSG:3857:20 516353 524184 562514 573802 EPSG:3857:21 1032707 1048369 1125028 1147604 EPSG:3857:22 2065415 2096739 2250056 2295208 EPSG:3857:23 4130831 4193479 4500112 4590417 EPSG:3857:24 8261663 8386959 9000225 9180835 EPSG:3857:25 16523326 16773919 18000450 18361671 EPSG:3857:26 33046652 33547838 36000901 36723343 EPSG:3857:27 66093305 67095676 72001802 73446687 EPSG:3857:28 132186611 134191352 144003604 146893375 EPSG:3857:29 264373223 268382704 288007209 293786751 EPSG:3857:30 528746446 536765409 576014419 587573503 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 7 7 17 17 EPSG:4326:5 15 15 34 35 EPSG:4326:6 31 31 68 70 EPSG:4326:7 62 63 137 140 EPSG:4326:8 124 127 274 280 EPSG:4326:9 248 255 549 560 EPSG:4326:10 496 511 1098 1120 EPSG:4326:11 993 1023 2197 2241 EPSG:4326:12 1986 2047 4394 4482 EPSG:4326:13 3972 4094 8789 8965 EPSG:4326:14 7944 8188 17578 17931 EPSG:4326:15 15888 16377 35157 35862 EPSG:4326:16 31776 32755 70314 71725 EPSG:4326:17 63553 65510 140628 143450 EPSG:4326:18 127106 131020 281257 286901 EPSG:4326:19 254212 262040 562514 573802 EPSG:4326:20 508425 524081 1125028 1147604 EPSG:4326:21 1016851 1048163 2250056 2295208 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 15 15 17 17 EPSG:3857:6 31 31 34 35 EPSG:3857:7 63 63 68 70 EPSG:3857:8 126 127 137 140 EPSG:3857:9 252 255 274 280 EPSG:3857:10 504 511 549 560 EPSG:3857:11 1008 1023 1098 1120 EPSG:3857:12 2017 2047 2197 2241 EPSG:3857:13 4034 4095 4394 4482 EPSG:3857:14 8068 8190 8789 8965 EPSG:3857:15 16136 16380 17578 17931 EPSG:3857:16 32272 32761 35157 35862 EPSG:3857:17 64544 65523 70314 71725 EPSG:3857:18 129088 131046 140628 143450 EPSG:3857:19 258176 262092 281257 286901 EPSG:3857:20 516353 524184 562514 573802 EPSG:3857:21 1032707 1048369 1125028 1147604 EPSG:3857:22 2065415 2096739 2250056 2295208 EPSG:3857:23 4130831 4193479 4500112 4590417 EPSG:3857:24 8261663 8386959 9000225 9180835 EPSG:3857:25 16523326 16773919 18000450 18361671 EPSG:3857:26 33046652 33547838 36000901 36723343 EPSG:3857:27 66093305 67095676 72001802 73446687 EPSG:3857:28 132186611 134191352 144003604 146893375 EPSG:3857:29 264373223 268382704 288007209 293786751 EPSG:3857:30 528746446 536765409 576014419 587573503 Average year temperature anomalies (1991-2000) against 1901-1920 Average year temperature anomalies in °Celsius across the period 1991-2000 calculated over the average temperatures per year in the period 1901-1920 (as close as possible to the pre-industrial era). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_00_anom_1901_1920 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Albedo Autumn 2019 (Copernicus) Unit: ratio of the solar radiation reflected by a surface to the total incoming solar radiation, usually measured between 0 (all incident radiation absorbed) and 1 (all incident radiation refleted). Surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. The present layer represents the black-sky albedo (directional albedo), which is considered as an Essential Climate Variable by the Global Climate Observing System (GCOS). Surface albedo is a sensitive indicator of environmental vulnerability making it a key element required by climate, biogeochemical, hydrological, and weather forecast models. It has a spatial resolution of 1km and is available from the Copernicus Global Land Service (https://land.copernicus.eu/global/products/sa) as netCDF files (technical documentation available at https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_PUM_SA1km-V1_I1.40.pdf. The present raster is the broadband directional albedo over full spectrum [0.3-4µm]. It is the average of the various albedo files available in autumn 2019 (3 September 2019, 13 September 2019, 23 September 2019, 3 October 2019, 13 October 2019, 24 October 2019, 3 November 2019, 13 November 2019 and 23 November 2019), then transformed into a geotiff in order to display and example of albedo reflectance in autumn. -180.0 -59.995535714253904 179.9955357142039 80.00446428571429 wesr_mountains:c_gls_ALDH_2019_automne_raster_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 3 53 0 127 EPSG:4326:7 7 106 0 255 EPSG:4326:8 14 213 0 511 EPSG:4326:9 28 426 0 1023 EPSG:4326:10 56 853 0 2047 EPSG:4326:11 113 1706 0 4095 EPSG:4326:12 227 3413 0 8191 EPSG:4326:13 454 6826 0 16383 EPSG:4326:14 909 13652 0 32767 EPSG:4326:15 1819 27305 0 65535 EPSG:4326:16 3639 54611 0 131070 EPSG:4326:17 7278 109223 0 262140 EPSG:4326:18 14557 218446 0 524281 EPSG:4326:19 29114 436893 0 1048562 EPSG:4326:20 58228 873787 0 2097125 EPSG:4326:21 116456 1747574 0 4194251 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 GHA_Stream_Profile -2.942754639 9.62256316 -1.420219031 11.034631553 MAPX:GHA_Stream_Profile image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30746 31007 32232 32509 EPSG:3857:17 61493 62015 64464 65018 EPSG:3857:18 122986 124031 128929 130037 EPSG:3857:19 245973 248063 257858 260075 EPSG:3857:20 491946 496127 515716 520151 EPSG:3857:21 983893 992255 1031433 1040302 EPSG:3857:22 1967787 1984510 2062866 2080605 EPSG:3857:23 3935574 3969020 4125732 4161210 EPSG:3857:24 7871148 7938040 8251465 8322420 EPSG:3857:25 15742296 15876081 16502931 16644841 EPSG:3857:26 31484592 31752163 33005862 33289683 EPSG:3857:27 62969184 63504327 66011725 66579367 EPSG:3857:28 125938369 127008655 132023451 133158735 EPSG:3857:29 251876738 254017310 264046902 266317471 EPSG:3857:30 503753476 508034621 528093804 532634943 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1829 4029 4063 EPSG:4326:13 3593 3658 8058 8127 EPSG:4326:14 7187 7316 16116 16254 EPSG:4326:15 14375 14632 32232 32509 EPSG:4326:16 28750 29264 64464 65018 EPSG:4326:17 57500 58529 128929 130037 EPSG:4326:18 115001 117058 257858 260075 EPSG:4326:19 230003 234116 515716 520151 EPSG:4326:20 460006 468232 1031433 1040302 EPSG:4326:21 920013 936465 2062866 2080605 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30746 31007 32232 32509 EPSG:3857:17 61493 62015 64464 65018 EPSG:3857:18 122986 124031 128929 130037 EPSG:3857:19 245973 248063 257858 260075 EPSG:3857:20 491946 496127 515716 520151 EPSG:3857:21 983893 992255 1031433 1040302 EPSG:3857:22 1967787 1984510 2062866 2080605 EPSG:3857:23 3935574 3969020 4125732 4161210 EPSG:3857:24 7871148 7938040 8251465 8322420 EPSG:3857:25 15742296 15876081 16502931 16644841 EPSG:3857:26 31484592 31752163 33005862 33289683 EPSG:3857:27 62969184 63504327 66011725 66579367 EPSG:3857:28 125938369 127008655 132023451 133158735 EPSG:3857:29 251876738 254017310 264046902 266317471 EPSG:3857:30 503753476 508034621 528093804 532634943 Mean predicted temperatures 2020 - Central African Republic Mean predicted temperatures in 2020 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_predict_2020_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 ecu_forint100 The forest integrrity index is derived by overlaying the human footprint (Venter et al. 2016) on the forest structural condition. The name is consistent with the concept of ecological integrity. Ecological integrity has been defined as, “the system’s capacity to maintain structure and ecosystem functions using processes and elements characteristic for its ecoregion.” (Parks Canada 2008). This capacity is a result of the climate, soil, topography, biota and other biophysical properties of the ecoregion and the extent to which these properties are not altered by modern human pressures. Consistent with this definition, the forest integrity index is based on on the structural complexity of a stand relative to the natural potential of the ecoregion and level of human pressure. Thus, forest of high integrity are relatively tall, high in canopy cover, older, and with relatively low human pressure. An increasing number of studies have shown that human pressure in various forms can have negative effects on native species. Thus, high integrity forests may be uniquely important for conservation because they support species and processes that are require well-developed forests and are sensitive to human activities. Such forests often also have high economic value and have likely been preferentially converted to more intense human land uses. Thus, identifying remaining areas of high forest integrity is important for conservation planning.<br><br>Data is provided by Montana State University.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> -81.007003784197 -5.015087128068 -75.189781557321 1.4260239881959995 wesr_biodiversity:ecu_forint100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 16 8 9 EPSG:3857:6 31 32 17 18 EPSG:3857:7 63 65 35 37 EPSG:3857:8 126 131 70 74 EPSG:3857:9 253 263 140 149 EPSG:3857:10 507 526 281 298 EPSG:3857:11 1015 1052 563 596 EPSG:3857:12 2031 2105 1126 1192 EPSG:3857:13 4063 4210 2252 2385 EPSG:3857:14 8127 8420 4505 4770 EPSG:3857:15 16254 16841 9010 9540 EPSG:3857:16 32508 33682 18021 19080 EPSG:3857:17 65016 67364 36042 38160 EPSG:3857:18 130033 134728 72084 76320 EPSG:3857:19 260066 269457 144168 152640 EPSG:3857:20 520133 538914 288337 305281 EPSG:3857:21 1040267 1077828 576675 610563 EPSG:3857:22 2080535 2155656 1153351 1221127 EPSG:3857:23 4161071 4311313 2306703 2442255 EPSG:3857:24 8322143 8622627 4613407 4884510 EPSG:3857:25 16644287 17245254 9226815 9769020 EPSG:3857:26 33288574 34490508 18453631 19538040 EPSG:3857:27 66577148 68981016 36907263 39076081 EPSG:3857:28 133154297 137962032 73814527 78152163 EPSG:3857:29 266308595 275924064 147629055 156304326 EPSG:3857:30 532617190 551848128 295258111 312608653 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 1 1 1 EPSG:4326:2 1 2 2 2 EPSG:4326:3 3 4 4 4 EPSG:4326:4 7 8 8 9 EPSG:4326:5 15 16 17 18 EPSG:4326:6 31 33 35 37 EPSG:4326:7 62 67 70 74 EPSG:4326:8 125 135 140 149 EPSG:4326:9 251 270 281 298 EPSG:4326:10 503 540 563 596 EPSG:4326:11 1007 1081 1126 1192 EPSG:4326:12 2015 2162 2252 2385 EPSG:4326:13 4031 4324 4505 4770 EPSG:4326:14 8062 8648 9010 9540 EPSG:4326:15 16124 17296 18021 19080 EPSG:4326:16 32248 34593 36042 38160 EPSG:4326:17 64497 69187 72084 76320 EPSG:4326:18 128995 138375 144168 152640 EPSG:4326:19 257990 276751 288337 305281 EPSG:4326:20 515980 553503 576675 610563 EPSG:4326:21 1031961 1107006 1153351 1221127 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 16 8 9 EPSG:3857:6 31 32 17 18 EPSG:3857:7 63 65 35 37 EPSG:3857:8 126 131 70 74 EPSG:3857:9 253 263 140 149 EPSG:3857:10 507 526 281 298 EPSG:3857:11 1015 1052 563 596 EPSG:3857:12 2031 2105 1126 1192 EPSG:3857:13 4063 4210 2252 2385 EPSG:3857:14 8127 8420 4505 4770 EPSG:3857:15 16254 16841 9010 9540 EPSG:3857:16 32508 33682 18021 19080 EPSG:3857:17 65016 67364 36042 38160 EPSG:3857:18 130033 134728 72084 76320 EPSG:3857:19 260066 269457 144168 152640 EPSG:3857:20 520133 538914 288337 305281 EPSG:3857:21 1040267 1077828 576675 610563 EPSG:3857:22 2080535 2155656 1153351 1221127 EPSG:3857:23 4161071 4311313 2306703 2442255 EPSG:3857:24 8322143 8622627 4613407 4884510 EPSG:3857:25 16644287 17245254 9226815 9769020 EPSG:3857:26 33288574 34490508 18453631 19538040 EPSG:3857:27 66577148 68981016 36907263 39076081 EPSG:3857:28 133154297 137962032 73814527 78152163 EPSG:3857:29 266308595 275924064 147629055 156304326 EPSG:3857:30 532617190 551848128 295258111 312608653 Increase in SOC on Croplands After 20 Yr - High Scenario This dataset provides estimate of the potential increase in soil organic carbon within the top 30 cm of soil in croplands after 20 years, following implementation of better land managment practices under a high sequestration scenario. The per pixel values here take in to consideration the percent of each pixel which is classified as cropland (from the GLC-Share/GLC-02 dataset), and values have been converted to total tonnes of carbon (x 100) per pixel.<br/><br>See: <a href="https://doi.org/10.1038/s41598-017-15794-8">Zomer, R.J., Bossio, D.A., Sommer, R., Verchot, L.V., 2017. Global Sequestration Potential of Increased Organic Carbon in Cropland Soils. Scientific Reports 7, 15554</a>.<br/>For descriptions of sequrestion scenarions see: <a href="https://doi.org/10.1016/j.jenvman.2014.05.017">Sommer, R., Bossio, D., 2014. Dynamics and climate change mitigation potential of soil organic carbon sequestration. Journal of Environmental Management 144, 83–87</a>.<br/> -180.0 -62.002087813 179.9999424 87.37080495400002 MapX_UNDP:soc_dif_hi image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 46 0 63 EPSG:3857:7 0 92 0 127 EPSG:3857:8 0 184 0 255 EPSG:3857:9 0 369 0 511 EPSG:3857:10 0 738 0 1023 EPSG:3857:11 0 1476 0 2047 EPSG:3857:12 0 2953 0 4095 EPSG:3857:13 0 5907 0 8191 EPSG:3857:14 0 11814 0 16383 EPSG:3857:15 0 23628 0 32767 EPSG:3857:16 0 47256 0 65535 EPSG:3857:17 0 94512 0 131071 EPSG:3857:18 0 189025 0 262143 EPSG:3857:19 0 378051 0 524287 EPSG:3857:20 0 756103 0 1048575 EPSG:3857:21 0 1512206 0 2097151 EPSG:3857:22 -1 3024413 0 4194303 EPSG:3857:23 -1 6048826 0 8388606 EPSG:3857:24 0 12097653 0 16777213 EPSG:3857:25 0 24195306 0 33554426 EPSG:3857:26 0 48390613 0 67108853 EPSG:3857:27 0 96781227 0 134217706 EPSG:3857:28 -1 193562455 0 268435413 EPSG:3857:29 0 387124910 0 536870826 EPSG:3857:30 0 774249820 0 1073741652 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 54 0 127 EPSG:4326:7 1 108 0 255 EPSG:4326:8 3 216 0 511 EPSG:4326:9 7 432 0 1023 EPSG:4326:10 14 864 0 2047 EPSG:4326:11 29 1729 0 4095 EPSG:4326:12 59 3458 0 8191 EPSG:4326:13 119 6917 0 16383 EPSG:4326:14 239 13835 0 32767 EPSG:4326:15 478 27671 0 65535 EPSG:4326:16 957 55342 0 131071 EPSG:4326:17 1914 110684 0 262143 EPSG:4326:18 3829 221369 0 524287 EPSG:4326:19 7658 442738 0 1048575 EPSG:4326:20 15316 885476 0 2097151 EPSG:4326:21 30632 1770952 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 46 0 63 EPSG:3857:7 0 92 0 127 EPSG:3857:8 0 184 0 255 EPSG:3857:9 0 369 0 511 EPSG:3857:10 0 738 0 1023 EPSG:3857:11 0 1476 0 2047 EPSG:3857:12 0 2953 0 4095 EPSG:3857:13 0 5907 0 8191 EPSG:3857:14 0 11814 0 16383 EPSG:3857:15 0 23628 0 32767 EPSG:3857:16 0 47256 0 65535 EPSG:3857:17 0 94512 0 131071 EPSG:3857:18 0 189025 0 262143 EPSG:3857:19 0 378051 0 524287 EPSG:3857:20 0 756103 0 1048575 EPSG:3857:21 -1 1512206 0 2097151 EPSG:3857:22 -1 3024413 0 4194303 EPSG:3857:23 0 6048826 0 8388606 EPSG:3857:24 0 12097653 0 16777213 EPSG:3857:25 0 24195306 0 33554426 EPSG:3857:26 0 48390613 0 67108853 EPSG:3857:27 -1 96781227 0 134217706 EPSG:3857:28 0 193562455 0 268435413 EPSG:3857:29 0 387124910 0 536870826 EPSG:3857:30 -1 774249820 0 1073741652 Total built-up surface in 2025 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_2025 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Average year temperature anomalies (1991-2000) over 1991-2020 climatology Average year temperature anomalies in °Celsius across the period 1991-2000 calculated over the average temperatures per year in the period 1991-2020 (climatology). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_00_anom9120 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone surge/ Mangroves at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_man6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Total built-up surface in 2020 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_2020 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Tropical cyclone hazard frequency -180.0 -90.0 180.0 90.0 ECO-DRR:cy_freqaf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Dogondoutchi_Duration_78_T250 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Duration_78_T250 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 6 6 16 16 EPSG:4326:5 13 13 32 33 EPSG:4326:6 26 27 64 66 EPSG:4326:7 52 55 129 132 EPSG:4326:8 105 111 259 264 EPSG:4326:9 211 222 518 529 EPSG:4326:10 423 444 1037 1058 EPSG:4326:11 846 888 2075 2117 EPSG:4326:12 1693 1776 4151 4234 EPSG:4326:13 3387 3552 8302 8468 EPSG:4326:14 6774 7105 16605 16936 EPSG:4326:15 13549 14211 33210 33872 EPSG:4326:16 27099 28423 66421 67745 EPSG:4326:17 54199 56847 132842 135490 EPSG:4326:18 108399 113695 265685 270981 EPSG:4326:19 216798 227390 531371 541962 EPSG:4326:20 433596 454780 1062742 1083925 EPSG:4326:21 867193 909560 2125484 2167851 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 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489854857 501022824 544124092 554969969 Satellite Mogadisho Urban Growth 2007 Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2007-03-09. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov. 45.195394649846214 1.955229029551538 45.47923060483454 2.141476613353127 MAPX:Mogadisho_Landsat7_20070309-531 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 10 10 EPSG:3857:5 15 15 20 20 EPSG:3857:6 31 31 40 40 EPSG:3857:7 63 63 80 80 EPSG:3857:8 126 126 160 160 EPSG:3857:9 252 253 320 320 EPSG:3857:10 505 506 640 641 EPSG:3857:11 1011 1012 1281 1282 EPSG:3857:12 2023 2025 2562 2565 EPSG:3857:13 4047 4051 5124 5130 EPSG:3857:14 8094 8102 10248 10261 EPSG:3857:15 16189 16205 20497 20523 EPSG:3857:16 32378 32411 40995 41047 EPSG:3857:17 64756 64823 81991 82094 EPSG:3857:18 129512 129647 163982 164188 EPSG:3857:19 259024 259295 327964 328377 EPSG:3857:20 518049 518591 655929 656755 EPSG:3857:21 1036098 1037183 1311858 1313511 EPSG:3857:22 2072196 2074367 2623716 2627023 EPSG:3857:23 4144392 4148735 5247433 5254046 EPSG:3857:24 8288784 8297470 10494866 10508093 EPSG:3857:25 16577569 16594940 20989732 21016187 EPSG:3857:26 33155138 33189880 41979464 42032375 EPSG:3857:27 66310277 66379760 83958928 84064750 EPSG:3857:28 132620555 132759520 167917856 168129500 EPSG:3857:29 265241110 265519041 335835713 336259000 EPSG:3857:30 530482221 531038082 671671427 672518000 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 10 10 EPSG:4326:4 7 7 20 20 EPSG:4326:5 15 15 40 40 EPSG:4326:6 31 31 80 80 EPSG:4326:7 62 62 160 160 EPSG:4326:8 124 125 320 320 EPSG:4326:9 249 250 640 641 EPSG:4326:10 499 500 1281 1282 EPSG:4326:11 999 1001 2562 2565 EPSG:4326:12 1999 2003 5124 5130 EPSG:4326:13 3998 4007 10248 10261 EPSG:4326:14 7997 8014 20497 20523 EPSG:4326:15 15994 16028 40995 41047 EPSG:4326:16 31988 32056 81991 82094 EPSG:4326:17 63976 64112 163982 164188 EPSG:4326:18 127953 128224 327964 328377 EPSG:4326:19 255906 256448 655929 656755 EPSG:4326:20 511812 512897 1311858 1313511 EPSG:4326:21 1023625 1025795 2623716 2627023 EPSG:900913 Economical Exposition To Landslides Triggered By Precipitations This dataset includes an estimate of the annual frequency of landslide triggered by precipitations. It depends on the combination of trigger and susceptibility defined by six parameters: slope factor, lithological (or geological) conditions, soil moisture condition, vegetation cover, precipitation and seismic conditions. Unit is expected annual probability and percentage of pixel of occurrence of a potentially destructive landslide event x 1000000. This product was designed by International Centre for Geohazards (NGI) for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards (NGI). -180.0 -90.0 180.0 90.0 wesr_risk:ls_ecoexp2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Spectral Acceleration 0.2 Sec 1500 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_02_s_1500_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Forest Fragmentation (2012) 1000m The fragmentation dataset classifies forested areas into several fragmentation classes using spatial pattern analysis, and includes effects of both deforestation and regrowth on forest fragmentation. Multiple variations of this dataset are available for the years 2000 and 2012, each making different assumptions about: the distance that fragmentation effects extend into forests (500 metres or 1000 metres); the canopy cover (%) that defines forest area (25 or 50%); and the minimum area (in hectares) of a fragment to be be considered a forest fragment (0, 1 or 5 ha). The map presented here shows effects extending 500 metres into forest interiors. This dataset has a 30-metre spatial resolution. Data derived from: Hansen, M.C., et al. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342, 850–853. 10.1126/science.1244693 Created as part of the GEF-funded Global Support to Sixth National Report Project in collaboration with the NASA-funded Forest Integrity Project. -119.36170706306382 -34.213866389533806 179.99995545035347 30.001378 MapX_UNDP_nd:frag_2012_1000_25_0 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 13 19 5 31 EPSG:3857:6 26 38 10 63 EPSG:3857:7 52 76 21 127 EPSG:3857:8 105 153 43 255 EPSG:3857:9 211 307 86 511 EPSG:3857:10 422 615 172 1023 EPSG:3857:11 844 1231 344 2047 EPSG:3857:12 1689 2462 689 4095 EPSG:3857:13 3379 4925 1379 8191 EPSG:3857:14 6759 9850 2759 16383 EPSG:3857:15 13519 19701 5519 32767 EPSG:3857:16 27038 39403 11038 65535 EPSG:3857:17 54076 78806 22077 131071 EPSG:3857:18 108152 157613 44155 262143 EPSG:3857:19 216305 315227 88310 524287 EPSG:3857:20 432611 630455 176621 1048575 EPSG:3857:21 865223 1260910 353243 2097151 EPSG:3857:22 1730447 2521821 706487 4194303 EPSG:3857:23 3460894 5043642 1412974 8388606 EPSG:3857:24 6921789 10087284 2825949 16777213 EPSG:3857:25 13843578 20174568 5651898 33554427 EPSG:3857:26 27687157 40349137 11303797 67108855 EPSG:3857:27 55374314 80698274 22607594 134217711 EPSG:3857:28 110748628 161396549 45215188 268435422 EPSG:3857:29 221497257 322793098 90430376 536870845 EPSG:3857:30 442994514 645586197 180860753 1073741691 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 1 2 1 7 EPSG:4326:3 2 5 2 15 EPSG:4326:4 5 11 5 31 EPSG:4326:5 10 22 10 63 EPSG:4326:6 21 44 21 127 EPSG:4326:7 42 88 43 255 EPSG:4326:8 85 176 86 511 EPSG:4326:9 170 353 172 1023 EPSG:4326:10 341 706 344 2047 EPSG:4326:11 682 1413 689 4095 EPSG:4326:12 1365 2826 1379 8191 EPSG:4326:13 2730 5653 2759 16383 EPSG:4326:14 5461 11306 5519 32767 EPSG:4326:15 10922 22612 11038 65535 EPSG:4326:16 21844 45224 22077 131071 EPSG:4326:17 43689 90449 44155 262143 EPSG:4326:18 87379 180899 88310 524287 EPSG:4326:19 174758 361799 176621 1048575 EPSG:4326:20 349517 723598 353243 2097151 EPSG:4326:21 699034 1447196 706487 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 13 19 5 31 EPSG:3857:6 26 38 10 63 EPSG:3857:7 52 76 21 127 EPSG:3857:8 105 153 43 255 EPSG:3857:9 211 307 86 511 EPSG:3857:10 422 615 172 1023 EPSG:3857:11 844 1231 344 2047 EPSG:3857:12 1689 2462 689 4095 EPSG:3857:13 3379 4925 1379 8191 EPSG:3857:14 6759 9850 2759 16383 EPSG:3857:15 13519 19701 5519 32767 EPSG:3857:16 27038 39403 11038 65535 EPSG:3857:17 54076 78806 22077 131071 EPSG:3857:18 108152 157613 44155 262143 EPSG:3857:19 216305 315227 88310 524287 EPSG:3857:20 432611 630455 176621 1048575 EPSG:3857:21 865223 1260910 353243 2097151 EPSG:3857:22 1730447 2521821 706487 4194303 EPSG:3857:23 3460894 5043642 1412974 8388606 EPSG:3857:24 6921789 10087284 2825949 16777213 EPSG:3857:25 13843578 20174568 5651898 33554427 EPSG:3857:26 27687157 40349137 11303797 67108855 EPSG:3857:27 55374314 80698274 22607594 134217711 EPSG:3857:28 110748628 161396549 45215188 268435422 EPSG:3857:29 221497257 322793098 90430376 536870845 EPSG:3857:30 442994514 645586197 180860753 1073741691 Global Emissions NOx 1970 - EDGARD Global Emissions EDGAR v4.3.1 (January 2016) In EDGARv4.3.1 emissions are calculated for gaseous and particulate air pollutants per sector and country. For the energy related sectors the activity data are mainly based on the energy balance statistics of IEA (2014) Emission gridmaps are expressed in ton substance / 0.1degree x 0.1degree / year -180.0 -77.95 179.95 88.15000000000002 unea_pollution:edg70_nx image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 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EPSG:4326:13 3885 4309 9734 10099 EPSG:4326:14 7770 8618 19469 20198 EPSG:4326:15 15540 17236 38938 40397 EPSG:4326:16 31081 34472 77876 80795 EPSG:4326:17 62162 68944 155752 161590 EPSG:4326:18 124325 137888 311504 323181 EPSG:4326:19 248651 275776 623009 646362 EPSG:4326:20 497302 551552 1246019 1292725 EPSG:4326:21 994604 1103105 2492039 2585451 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 9 9 EPSG:3857:5 15 16 19 19 EPSG:3857:6 31 32 38 39 EPSG:3857:7 62 65 76 78 EPSG:3857:8 124 131 152 157 EPSG:3857:9 249 262 304 315 EPSG:3857:10 498 525 608 631 EPSG:3857:11 997 1050 1216 1262 EPSG:3857:12 1995 2101 2433 2524 EPSG:3857:13 3990 4202 4867 5049 EPSG:3857:14 7980 8405 9734 10099 EPSG:3857:15 15961 16810 19469 20198 EPSG:3857:16 31923 33620 38938 40397 EPSG:3857:17 63847 67241 77876 80795 EPSG:3857:18 127695 134483 155752 161590 EPSG:3857:19 255390 268967 311504 323181 EPSG:3857:20 510780 537935 623009 646362 EPSG:3857:21 1021560 1075871 1246019 1292725 EPSG:3857:22 2043121 2151742 2492039 2585451 EPSG:3857:23 4086242 4303484 4984079 5170903 EPSG:3857:24 8172484 8606969 9968159 10341806 EPSG:3857:25 16344969 17213938 19936318 20683613 EPSG:3857:26 32689938 34427876 39872637 41367226 EPSG:3857:27 65379877 68855753 79745274 82734452 EPSG:3857:28 130759755 137711507 159490548 165468905 EPSG:3857:29 261519511 275423014 318981097 330937811 EPSG:3857:30 523039023 550846028 637962194 661875622 Summer temperature change (°C) for the period 2020 - 2039 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_jja_NEARREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Coral reefs total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:coralkm2a image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Winter temperature change (°C) for the period 2020 - 2039 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_djf_NEARREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 asiaSCI3 90.32175330967124 -11.847003516704188 153.42828368100916 26.038457275126742 MapX_UNDP:asiaSCI3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 3 3 EPSG:3857:3 3 4 6 7 EPSG:3857:4 6 8 12 14 EPSG:3857:5 13 17 24 29 EPSG:3857:6 27 34 48 59 EPSG:3857:7 54 68 96 118 EPSG:3857:8 108 136 192 237 EPSG:3857:9 217 272 384 474 EPSG:3857:10 435 545 768 948 EPSG:3857:11 870 1091 1537 1896 EPSG:3857:12 1740 2183 3075 3793 EPSG:3857:13 3481 4367 6151 7587 EPSG:3857:14 6963 8735 12302 15174 EPSG:3857:15 13927 17470 24605 30349 EPSG:3857:16 27855 34940 49210 60698 EPSG:3857:17 55711 69880 98421 121397 EPSG:3857:18 111422 139760 196842 242795 EPSG:3857:19 222845 279521 393684 485590 EPSG:3857:20 445691 559043 787369 971180 EPSG:3857:21 891382 1118086 1574738 1942360 EPSG:3857:22 1782765 2236173 3149476 3884721 EPSG:3857:23 3565531 4472347 6298953 7769442 EPSG:3857:24 7131062 8944695 12597906 15538884 EPSG:3857:25 14262125 17889390 25195813 31077768 EPSG:3857:26 28524250 35778780 50391627 62155537 EPSG:3857:27 57048500 71557560 100783254 124311074 EPSG:3857:28 114097001 143115121 201566508 248622148 EPSG:3857:29 228194002 286230242 403133017 497244296 EPSG:3857:30 456388005 572460484 806266034 994488593 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 3 3 EPSG:4326:2 1 2 6 7 EPSG:4326:3 2 4 12 14 EPSG:4326:4 5 9 24 29 EPSG:4326:5 11 18 48 59 EPSG:4326:6 22 36 96 118 EPSG:4326:7 45 72 192 237 EPSG:4326:8 90 144 384 474 EPSG:4326:9 181 289 768 948 EPSG:4326:10 363 579 1537 1896 EPSG:4326:11 727 1158 3075 3793 EPSG:4326:12 1455 2317 6151 7587 EPSG:4326:13 2910 4635 12302 15174 EPSG:4326:14 5821 9270 24605 30349 EPSG:4326:15 11643 18540 49210 60698 EPSG:4326:16 23287 37081 98421 121397 EPSG:4326:17 46575 74162 196842 242795 EPSG:4326:18 93150 148325 393684 485590 EPSG:4326:19 186301 296650 787369 971180 EPSG:4326:20 372602 593301 1574738 1942360 EPSG:4326:21 745205 1186603 3149476 3884721 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 3 3 EPSG:3857:3 3 4 6 7 EPSG:3857:4 6 8 12 14 EPSG:3857:5 13 17 24 29 EPSG:3857:6 27 34 48 59 EPSG:3857:7 54 68 96 118 EPSG:3857:8 108 136 192 237 EPSG:3857:9 217 272 384 474 EPSG:3857:10 435 545 768 948 EPSG:3857:11 870 1091 1537 1896 EPSG:3857:12 1740 2183 3075 3793 EPSG:3857:13 3481 4367 6151 7587 EPSG:3857:14 6963 8735 12302 15174 EPSG:3857:15 13927 17470 24605 30349 EPSG:3857:16 27855 34940 49210 60698 EPSG:3857:17 55711 69880 98421 121397 EPSG:3857:18 111422 139760 196842 242795 EPSG:3857:19 222845 279521 393684 485590 EPSG:3857:20 445691 559043 787369 971180 EPSG:3857:21 891382 1118086 1574738 1942360 EPSG:3857:22 1782765 2236173 3149476 3884721 EPSG:3857:23 3565531 4472347 6298953 7769442 EPSG:3857:24 7131062 8944695 12597906 15538884 EPSG:3857:25 14262125 17889390 25195813 31077768 EPSG:3857:26 28524250 35778780 50391627 62155537 EPSG:3857:27 57048500 71557560 100783254 124311074 EPSG:3857:28 114097001 143115121 201566508 248622148 EPSG:3857:29 228194002 286230242 403133017 497244296 EPSG:3857:30 456388005 572460484 806266034 994488593 Species Richness This raster layer represents the number of species of mammals, amphibians and birds potentially occurring in each ~300m grid cell.<br><br>Species range data were rasterised at 10 arc-seconds (approximately 300m at the equator) from IUCN Red List polygons (IUCN 2017) and raster layers for each species were summed together into a single layer with equal weighting. The species are used as a proxy to represent terrestrial biodiversity and are based on taxonomic groups that have been comprehensively assessed by IUCN Red List. Thus users should be aware of the taxonomic bias and and that marine values are based only on marine species of mammals and birds.<br/><br>Source: IUCN 2017. The IUCN Red List of Threatened Species. Version 2017-3 <a href="http://www.iucnredlist.org" target="_blank">IUCNRedList</a>.<br>Terms of Use: <a href="http://www.iucnredlist.org/info/terms-of-use" target="_blank">Commercial use is not permitted</a><br/> -179.995201157628 -84.69466806618583 179.8859620772232 85.91771612300938 MapX_UNDP:species_richness_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 126 0 127 EPSG:3857:8 0 253 0 255 EPSG:3857:9 0 506 0 511 EPSG:3857:10 0 1012 0 1023 EPSG:3857:11 0 2025 0 2047 EPSG:3857:12 0 4050 0 4094 EPSG:3857:13 0 8101 0 8189 EPSG:3857:14 0 16202 0 16378 EPSG:3857:15 0 32404 0 32757 EPSG:3857:16 0 64809 0 65515 EPSG:3857:17 0 129619 1 131030 EPSG:3857:18 0 259238 3 262060 EPSG:3857:19 0 518476 6 524121 EPSG:3857:20 0 1036953 13 1048243 EPSG:3857:21 0 2073906 27 2096487 EPSG:3857:22 -1 4147812 55 4192975 EPSG:3857:23 -1 8295624 111 8385950 EPSG:3857:24 0 16591249 223 16771901 EPSG:3857:25 0 33182499 447 33543802 EPSG:3857:26 0 66364998 894 67087605 EPSG:3857:27 0 132729997 1789 134175211 EPSG:3857:28 -1 265459994 3578 268350423 EPSG:3857:29 0 530919989 7156 536700846 EPSG:3857:30 0 1061839978 14313 1073401692 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 62 0 127 EPSG:4326:7 2 124 0 255 EPSG:4326:8 5 248 0 511 EPSG:4326:9 11 496 0 1023 EPSG:4326:10 23 993 0 2047 EPSG:4326:11 46 1987 0 4094 EPSG:4326:12 92 3975 0 8189 EPSG:4326:13 185 7950 0 16378 EPSG:4326:14 371 15901 0 32757 EPSG:4326:15 743 31802 0 65515 EPSG:4326:16 1486 63604 1 131030 EPSG:4326:17 2972 127208 3 262060 EPSG:4326:18 5945 254417 6 524121 EPSG:4326:19 11890 508835 13 1048243 EPSG:4326:20 23781 1017670 27 2096487 EPSG:4326:21 47562 2035340 55 4192975 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 126 0 127 EPSG:3857:8 0 253 0 255 EPSG:3857:9 0 506 0 511 EPSG:3857:10 0 1012 0 1023 EPSG:3857:11 0 2025 0 2047 EPSG:3857:12 0 4050 0 4094 EPSG:3857:13 0 8101 0 8189 EPSG:3857:14 0 16202 0 16378 EPSG:3857:15 0 32404 0 32757 EPSG:3857:16 0 64809 0 65515 EPSG:3857:17 0 129619 1 131030 EPSG:3857:18 0 259238 3 262060 EPSG:3857:19 0 518476 6 524121 EPSG:3857:20 0 1036953 13 1048243 EPSG:3857:21 -1 2073906 27 2096487 EPSG:3857:22 -1 4147812 55 4192975 EPSG:3857:23 0 8295624 111 8385950 EPSG:3857:24 0 16591249 223 16771901 EPSG:3857:25 0 33182499 447 33543802 EPSG:3857:26 0 66364998 894 67087605 EPSG:3857:27 -1 132729997 1789 134175211 EPSG:3857:28 0 265459994 3578 268350423 EPSG:3857:29 0 530919989 7156 536700846 EPSG:3857:30 -1 1061839978 14313 1073401692 Combination Tsunami/Mangroves at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_man9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_mambo_bado_20210130 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20210130 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 Population density map 2018 based on HRSL, GSHL and the World Population Prospect 2019 Population density map for 2018 at 30arcsec resolution. <br><br> The layer integrates data from the High Resolution Settlement Layer (HRSL) - META (originally Facebook), the Global Human Settlement Layer (GHSL) - JRC, and the national population count for 2018 reported on the World Population Prospects 2019. <br><br> Using the country borders (level 0) of the UN Cartographic Section 2020 (BNDA_CTY), countries with full data coverage from HRSL use it. Countries with missing or partial coverage from HRSL use GHSL. <br> Both the original layers of HRSL and GHSL were, first, recalculated at 30arcsec resolution (~1km) through an aggregation process (sum) and, then, integrated in Google Earth Engine. Pixel counts were then recalculated for 2018 based on the country population data reported for 2018 by the World Population Prospects 2019. <br><br> List of GIDs of polygons of the BNDA_CTY layer of the UNMap2020 at level 0 that uses population data from GSHL: [6, 203, 228, 111, 250, 203, 65, 22, 234, 146, 208, 77, 223, 157, 273, 81, 221, 116, 2, 51, 156, 191, 20, 101, 47, 266, 61, 62, 26, 286, 119, 197, 277, 189, 195, 213, 215, 214, 212, 35, 145, 232, 84, 56, 175, 239, 38, 222, 19, 27, 28, 196, 207, 206, 265, 274, 275, 276, 278, 279, 280, 281, 282, 283, 284, 285] <br><br> Source of data: <br> GHSL: GHS_POP_E2015_GLOBE_R2019A_4326_30SS_V1_0 (downloaded from <a href="https://ghsl.jrc.ec.europa.eu/download.php?ds=pop at 30arcsec resolution"target=_blank>JRC</a>)<br> Dataset:<br> Schiavina, Marcello; Freire, Sergio; MacManus, Kytt (2019): GHS population grid multitemporal (1975, 1990, 2000, 2015) R2019A. European Commission, Joint Research Centre (JRC) DOI: <a href="http://data.europa.eu/89h/0c6b9751-a71f-4062-830b-43c9f432370f"target=_blank>10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218</a> <br> Concept & Methodology: Freire, Sergio; MacManus, Kytt; Pesaresi, Martino; Doxsey-Whitfield, Erin; Mills, Jane (2016): Development of new open and free multi-temporal global population grids at 250 m resolution. Geospatial Data in a Changing World; Association of Geographic Information Laboratories in Europe (AGILE). AGILE 2016. <br><br>HRSL: ee.ImageCollection("projects/sat-io/open-datasets/hrsl/hrslpop") on Google Earth Engine at 30m resolution. <br> Facebook Connectivity Lab and Center for International Earth Science Information Network - CIESIN - Columbia University. 2016. High Resolution Settlement Layer (HRSL). Source imagery for HRSL © 2016 DigitalGlobe. <br><br><a href="https://population.un.org/wpp/"target=_blank>World Population Prospects 2019 (UN)</a> <br><br> -179.999999999928 -59.99999999424 179.999999999928 84.00833333903574 grid_data_core_pro:HRSL_wGHSL_pop_count_2018_wnodata_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 45 0 63 EPSG:3857:7 3 90 0 127 EPSG:3857:8 7 181 0 255 EPSG:3857:9 15 363 0 511 EPSG:3857:10 31 726 0 1023 EPSG:3857:11 62 1453 0 2047 EPSG:3857:12 124 2906 0 4095 EPSG:3857:13 249 5813 0 8191 EPSG:3857:14 499 11626 0 16383 EPSG:3857:15 998 23252 0 32767 EPSG:3857:16 1997 46504 0 65535 EPSG:3857:17 3994 93008 0 131071 EPSG:3857:18 7989 186017 0 262143 EPSG:3857:19 15979 372034 0 524287 EPSG:3857:20 31958 744069 0 1048575 EPSG:3857:21 63917 1488139 0 2097151 EPSG:3857:22 127834 2976279 0 4194304 EPSG:3857:23 255669 5952559 0 8388608 EPSG:3857:24 511338 11905118 0 16777215 EPSG:3857:25 1022677 23810236 0 33554431 EPSG:3857:26 2045355 47620473 0 67108863 EPSG:3857:27 4090711 95240947 0 134217727 EPSG:3857:28 8181422 190481895 0 268435456 EPSG:3857:29 16362845 380963791 0 536870911 EPSG:3857:30 32725690 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 8 213 0 511 EPSG:4326:9 17 426 0 1023 EPSG:4326:10 34 853 0 2047 EPSG:4326:11 68 1706 0 4095 EPSG:4326:12 136 3413 0 8191 EPSG:4326:13 272 6826 0 16383 EPSG:4326:14 545 13653 0 32767 EPSG:4326:15 1090 27306 0 65535 EPSG:4326:16 2181 54613 0 131071 EPSG:4326:17 4362 109226 0 262143 EPSG:4326:18 8725 218453 0 524287 EPSG:4326:19 17451 436906 0 1048575 EPSG:4326:20 34903 873813 0 2097151 EPSG:4326:21 69807 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 45 0 63 EPSG:3857:7 3 90 0 127 EPSG:3857:8 7 181 0 255 EPSG:3857:9 15 363 0 511 EPSG:3857:10 31 726 0 1023 EPSG:3857:11 62 1453 0 2047 EPSG:3857:12 124 2906 0 4095 EPSG:3857:13 249 5813 0 8191 EPSG:3857:14 499 11626 0 16383 EPSG:3857:15 998 23252 0 32767 EPSG:3857:16 1997 46504 0 65535 EPSG:3857:17 3994 93008 0 131071 EPSG:3857:18 7989 186017 0 262143 EPSG:3857:19 15979 372034 0 524287 EPSG:3857:20 31958 744069 0 1048575 EPSG:3857:21 63917 1488139 0 2097152 EPSG:3857:22 127834 2976279 0 4194304 EPSG:3857:23 255669 5952559 0 8388607 EPSG:3857:24 511338 11905118 0 16777215 EPSG:3857:25 1022677 23810236 0 33554431 EPSG:3857:26 2045355 47620473 0 67108863 EPSG:3857:27 4090711 95240947 0 134217728 EPSG:3857:28 8181422 190481895 0 268435455 EPSG:3857:29 16362845 380963791 0 536870911 EPSG:3857:30 32725690 761927583 0 1073741824 Global Aridity Index_ET0_CIGAR(1970-2000) Aridity is usually expressed as a generalized function of precipitation, temperature and reference evapo-transpiration (ET0). An Aridity Index (UNEP, 1997) can be used to quantify precipitation availability over atmospheric water demand. The Global-Aridity_ET0 surface shows moisture availability for potential growth of reference vegetation excluding the impact of soil mediating water runoff events. Aridity Index values increase for more humid conditions, and decrease with more arid conditions. Global-Aridity_ET0 is available as one grid layer representing the annual average over the 1970-2000 period. The Aridity Index values reported within the Global Aridity Index_ET0 geodataset have been multiplied by a factor of 10,000 to derive and distribute the data as integers (with 4 decimal accuracy). Generalized climate classification scheme for Aridity Index values (UNEP 1997). Aridity Index Value | Climate Class < 0.03 | Hyper Arid 0.03 – 0.2 | Arid 0.2 – 0.5 | Semi-Arid 0.5 – 0.65 | Dry sub-humid > 0.65 | Humid The Global Aridity Index (Global-Aridity_ET0) dataset provide high-resolution (30 arc-seconds) global raster climate data for the 1970-2000 period, related to evapo-transpiration processes and rainfall deficit for potential vegetative growth, based upon implementation of a Penman Montieth Reference Evapotranspiration (ET0) equation. The geo-spatial datasets has been produced by Antonio Trabucco and Robert Zomer, with the support of the CGIAR-CSI (funding from IFPRI Project No. 203008.000.002 515-01-01). These datasets have been downloaded and are available from the CGIAR-CSI GeoPortal (https://cgiarcsi.community). The Consortium for Spatial Information (CGIAR-CSI) is an initiative of the Consultative Group for International Agriculture Research (CGIAR), linking the international science, research and development communities, with CGIAR scientists, national and international partners, and others working to apply and advance geospatial science for sustainable development, conservation, and poverty alleviation in developing countries. The Global-Aridity_ET0 and Global-ET0 datasets are provided for non-commercial use in standard GeoTiff format, at 30 arc seconds or ~ 1km at the equator, to support studies contributing to sustainable development, biodiversity and environmental conservation, poverty alleviation, and adaption to climate change globally, and in particular in developing countries. Comments, feedback, suggestions or bug reports regarding downloading of the Global-ET0 and Global-Aridity datasets should be sent to: csi@cgiar.org. Technical questions regarding the Global-ET0 and Global-Aridity_ET0 datasets can be directed to Antonio Trabucco: antoniotrabucco@cmcc.it . Correct Citation: Trabucco, A., and Zomer, R.J. 2018. Global Aridity Index and Potential Evapo-Transpiration (ET0) Climate Database v2. CGIAR Consortium for Spatial Information (CGIAR-CSI). Published online, available from the CGIAR-CSI GeoPortal at https://cgiarcsi.community -180.0 -59.99999999999994 179.99999999999983 90.0 UN_Sahel:ai_et0_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Temperature anomalies (°C) 2081-2100 (RCP8.5) Temperature anomalies (°C) for the period 2081-2100 based on the climate scenario RCP8.5 (reference 1986-2005). -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:tas_85_81_00 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 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These data, available on GEE, offer spectral bands suitable for water detection. The green and short-wave infrared spectral bands were selected to calculate the Modified Normalized Difference Water Index (MNDWI), while the red and near-infrared (NIR) bands were used in the case of another hazard to calculate the NDVI to eliminate false detections linked to vegetation. -13.243723483393213 12.296539942972935 -11.335952171241116 13.472448719878967 risk_southeast_senegal:flood_1995_2004 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60584 61024 60714 61408 EPSG:3857:18 121169 122048 121428 122817 EPSG:3857:19 242339 244096 242856 245634 EPSG:3857:20 484679 488193 485712 491269 EPSG:3857:21 969359 976387 971425 982539 EPSG:3857:22 1938719 1952774 1942851 1965078 EPSG:3857:23 3877439 3905548 3885702 3930157 EPSG:3857:24 7754879 7811097 7771405 7860314 EPSG:3857:25 15509758 15622194 15542811 15720628 EPSG:3857:26 31019517 31244388 31085623 31441257 EPSG:3857:27 62039034 62488777 62171246 62882514 EPSG:3857:28 124078069 124977555 124342492 125765029 EPSG:3857:29 248156138 249955110 248684984 251530058 EPSG:3857:30 496312277 499910220 497369968 503060117 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 221 474 479 EPSG:4326:10 435 442 948 959 EPSG:4326:11 870 884 1897 1919 EPSG:4326:12 1741 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3 5 EPSG:4326:3 1 4 7 11 EPSG:4326:4 3 8 14 22 EPSG:4326:5 7 16 28 45 EPSG:4326:6 15 32 57 90 EPSG:4326:7 31 65 115 181 EPSG:4326:8 63 130 230 362 EPSG:4326:9 127 260 460 725 EPSG:4326:10 255 520 921 1450 EPSG:4326:11 511 1041 1843 2901 EPSG:4326:12 1023 2082 3686 5802 EPSG:4326:13 2047 4164 7372 11605 EPSG:4326:14 4095 8328 14745 23210 EPSG:4326:15 8191 16657 29491 46421 EPSG:4326:16 16383 33314 58982 92842 EPSG:4326:17 32767 66628 117964 185685 EPSG:4326:18 65535 133256 235929 371370 EPSG:4326:19 131071 266513 471859 742741 EPSG:4326:20 262143 533026 943718 1485482 EPSG:4326:21 524287 1066052 1887436 2970965 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 230 362 EPSG:3857:10 368 516 460 725 EPSG:3857:11 736 1032 921 1450 EPSG:3857:12 1473 2065 1843 2901 EPSG:3857:13 2946 4130 3686 5802 EPSG:3857:14 5893 8260 7372 11605 EPSG:3857:15 11787 16520 14745 23210 EPSG:3857:16 23574 33041 29491 46421 EPSG:3857:17 47149 66082 58982 92842 EPSG:3857:18 94299 132164 117964 185685 EPSG:3857:19 188599 264328 235929 371370 EPSG:3857:20 377199 528657 471859 742741 EPSG:3857:21 754398 1057315 943718 1485482 EPSG:3857:22 1508796 2114630 1887436 2970965 EPSG:3857:23 3017592 4229260 3774873 5941930 EPSG:3857:24 6035184 8458521 7549747 11883861 EPSG:3857:25 12070369 16917042 15099494 23767722 EPSG:3857:26 24140738 33834084 30198988 47535445 EPSG:3857:27 48281477 67668168 60397977 95070890 EPSG:3857:28 96562954 135336336 120795955 190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 Yearly emissions of CO2 (short cycle organic Carbon) - 1980 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -55.699999999992485 179.99999999997954 76.5 wesr_climat:v60_CO2_org_short-cycle_C_1980_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 10 0 15 EPSG:3857:5 5 21 0 31 EPSG:3857:6 10 43 0 63 EPSG:3857:7 20 87 0 127 EPSG:3857:8 41 175 0 255 EPSG:3857:9 82 351 0 511 EPSG:3857:10 164 703 0 1023 EPSG:3857:11 328 1407 0 2047 EPSG:3857:12 656 2814 0 4095 EPSG:3857:13 1313 5628 0 8191 EPSG:3857:14 2627 11257 0 16383 EPSG:3857:15 5254 22515 0 32767 EPSG:3857:16 10509 45031 0 65535 EPSG:3857:17 21018 90062 0 131071 EPSG:3857:18 42036 180124 0 262143 EPSG:3857:19 84072 360249 0 524287 EPSG:3857:20 168145 720499 0 1048575 EPSG:3857:21 336291 1440999 0 2097151 EPSG:3857:22 672583 2881999 0 4194304 EPSG:3857:23 1345167 5763998 0 8388608 EPSG:3857:24 2690335 11527997 0 16777215 EPSG:3857:25 5380671 23055994 0 33554431 EPSG:3857:26 10761342 46111988 0 67108863 EPSG:3857:27 21522685 92223977 0 134217727 EPSG:3857:28 43045370 184447955 0 268435456 EPSG:3857:29 86090740 368895911 0 536870911 EPSG:3857:30 172181481 737791822 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 0 31 EPSG:4326:5 2 25 0 63 EPSG:4326:6 4 51 0 127 EPSG:4326:7 9 103 0 255 EPSG:4326:8 19 207 0 511 EPSG:4326:9 38 414 0 1023 EPSG:4326:10 76 828 0 2047 EPSG:4326:11 153 1657 0 4095 EPSG:4326:12 307 3315 0 8191 EPSG:4326:13 614 6630 0 16383 EPSG:4326:14 1228 13261 0 32767 EPSG:4326:15 2457 26523 0 65535 EPSG:4326:16 4915 53047 0 131071 EPSG:4326:17 9830 106095 0 262143 EPSG:4326:18 19660 212191 0 524287 EPSG:4326:19 39321 424382 0 1048575 EPSG:4326:20 78643 848764 0 2097151 EPSG:4326:21 157286 1697528 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 10 0 15 EPSG:3857:5 5 21 0 31 EPSG:3857:6 10 43 0 63 EPSG:3857:7 20 87 0 127 EPSG:3857:8 41 175 0 255 EPSG:3857:9 82 351 0 511 EPSG:3857:10 164 703 0 1023 EPSG:3857:11 328 1407 0 2047 EPSG:3857:12 656 2814 0 4095 EPSG:3857:13 1313 5628 0 8191 EPSG:3857:14 2627 11257 0 16383 EPSG:3857:15 5254 22515 0 32767 EPSG:3857:16 10509 45031 0 65535 EPSG:3857:17 21018 90062 0 131071 EPSG:3857:18 42036 180124 0 262143 EPSG:3857:19 84072 360249 0 524287 EPSG:3857:20 168145 720499 0 1048575 EPSG:3857:21 336291 1440999 0 2097152 EPSG:3857:22 672583 2881999 0 4194304 EPSG:3857:23 1345167 5763998 0 8388607 EPSG:3857:24 2690335 11527997 0 16777215 EPSG:3857:25 5380671 23055994 0 33554431 EPSG:3857:26 10761342 46111988 0 67108863 EPSG:3857:27 21522685 92223977 0 134217728 EPSG:3857:28 43045370 184447955 0 268435455 EPSG:3857:29 86090740 368895911 0 536870911 EPSG:3857:30 172181481 737791822 0 1073741824 Physical Exposition to Drought Events in the GHA Region This dataset includes an estimation of the annual physical exposition to drought based on Standardized Precipitation Index. It is based on three sources: 1) A global monthly gridded precipitation dataset obtained from the Climatic Research Unit (University of East Anglia). 2) A GIS modelling of global Standardized Precipitation Index based on Brad Lyon (IRI, Columbia University) methodology. 3) A population grid for the year 2010, provided by LandScanTM Global Population Database (Oak Ridge, TN: Oak Ridge National Laboratory 21.838947 -11.745700000296004 51.440099935812 23.14286 wesr_cca:geonode_physical_exposition_to_drought_events image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 6 8 8 10 EPSG:3857:5 13 17 17 20 EPSG:3857:6 27 34 35 41 EPSG:3857:7 55 68 71 82 EPSG:3857:8 111 136 143 164 EPSG:3857:9 222 272 287 329 EPSG:3857:10 444 545 574 658 EPSG:3857:11 888 1091 1148 1316 EPSG:3857:12 1777 2182 2296 2633 EPSG:3857:13 3554 4365 4592 5266 EPSG:3857:14 7108 8730 9185 10533 EPSG:3857:15 14217 17460 18371 21066 EPSG:3857:16 28435 34921 36743 42132 EPSG:3857:17 56871 69842 73487 84264 EPSG:3857:18 113742 139685 146974 168529 EPSG:3857:19 227484 279371 293949 337059 EPSG:3857:20 454968 558742 587898 674118 EPSG:3857:21 909936 1117484 1175797 1348236 EPSG:3857:22 1819872 2234968 2351594 2696472 EPSG:3857:23 3639744 4469936 4703188 5392945 EPSG:3857:24 7279489 8939872 9406376 10785890 EPSG:3857:25 14558978 17879744 18812753 21571780 EPSG:3857:26 29117957 35759488 37625506 43143561 EPSG:3857:27 58235914 71518976 75251013 86287123 EPSG:3857:28 116471828 143037953 150502027 172574246 EPSG:3857:29 232943657 286075907 301004054 345148493 EPSG:3857:30 465887314 572151815 602008108 690296986 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 5 EPSG:4326:3 2 4 8 10 EPSG:4326:4 5 9 17 20 EPSG:4326:5 11 18 35 41 EPSG:4326:6 23 36 71 82 EPSG:4326:7 47 72 143 164 EPSG:4326:8 95 144 287 329 EPSG:4326:9 190 289 574 658 EPSG:4326:10 380 578 1148 1316 EPSG:4326:11 760 1157 2296 2633 EPSG:4326:12 1521 2315 4592 5266 EPSG:4326:13 3042 4630 9185 10533 EPSG:4326:14 6085 9261 18371 21066 EPSG:4326:15 12170 18522 36743 42132 EPSG:4326:16 24341 37044 73487 84264 EPSG:4326:17 48683 74088 146974 168529 EPSG:4326:18 97367 148177 293949 337059 EPSG:4326:19 194735 296355 587898 674118 EPSG:4326:20 389471 592711 1175797 1348236 EPSG:4326:21 778942 1185423 2351594 2696472 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 6 8 8 10 EPSG:3857:5 13 17 17 20 EPSG:3857:6 27 34 35 41 EPSG:3857:7 55 68 71 82 EPSG:3857:8 111 136 143 164 EPSG:3857:9 222 272 287 329 EPSG:3857:10 444 545 574 658 EPSG:3857:11 888 1091 1148 1316 EPSG:3857:12 1777 2182 2296 2633 EPSG:3857:13 3554 4365 4592 5266 EPSG:3857:14 7108 8730 9185 10533 EPSG:3857:15 14217 17460 18371 21066 EPSG:3857:16 28435 34921 36743 42132 EPSG:3857:17 56871 69842 73487 84264 EPSG:3857:18 113742 139685 146974 168529 EPSG:3857:19 227484 279371 293949 337059 EPSG:3857:20 454968 558742 587898 674118 EPSG:3857:21 909936 1117484 1175797 1348236 EPSG:3857:22 1819872 2234968 2351594 2696472 EPSG:3857:23 3639744 4469936 4703188 5392945 EPSG:3857:24 7279489 8939872 9406376 10785890 EPSG:3857:25 14558978 17879744 18812753 21571780 EPSG:3857:26 29117957 35759488 37625506 43143561 EPSG:3857:27 58235914 71518976 75251013 86287123 EPSG:3857:28 116471828 143037953 150502027 172574246 EPSG:3857:29 232943657 286075907 301004054 345148493 EPSG:3857:30 465887314 572151815 602008108 690296986 Economical Exposition To Landslides Triggered By Earthquakes This dataset includes an estimate of the annual economical exposition of landslide triggered by earthquakes. It depends on the combination of trigger and susceptibility defined by six parameters: slope factor, lithological (or geological) conditions, soil moisture condition, vegetation cover, precipitation and seismic conditions. A Global Domestic Product grid for the year 2010, provided by the World Bank, has also been used. Unit is expected average annual GDP (2010 as the year of reference) exposed in (US $, year 2000 equivalent). This product was designed by International Centre for Geohazards (NGI) for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards (NGI). -180.0 -90.0 180.0 90.0 wesr_risk:le1010ieey image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 UN Country Polygons 2018 United Nations map (known as UNmap) is a worldwide geospatial database consisting of country and geographic name information on a global scale. The data is designed for the production of cartographic documents and maps, including their dissemination via public electronic networks, for the Secretariat of the United Nations.The United Nations maintains the Data as a courtesy to those who may choose to access the Data. The Data is provided “as is”, without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose and non-infringement. Disclaimers: - The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations. - The designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. - Dotted line represents approximately the Line of Control in Jammu and Kashmir agreed upon by India and Pakistan. - The final status of Jammu and Kashmir has not yet been agreed upon by the parties. - Final boundary between the Republic of Sudan and the Republic of South Sudan has not yet been determined. - Final status of the Abyei area is not yet determined. - A dispute exists between the Governments of Argentina and the United Kingdom of Great Britain and Northern Ireland concerning sovereignty over the Falkland Islands (Malvinas). Generalization parametrisation for the data is developed based on the work of Douglas and Peucker (1973), Wang (1996) and the Polynomial Approximation with Exponential Kernel algorithm.The adequate generalized data should be used for the intended dissemination scale and not rely on software or platform-automated generalization as some specific geographic features are removed at scales. For instance, the region of Abyei is not included at the scale of 1:25 million but is included at lower scales. Maps produced using this layer should be featured with the appropriate disclaimer depending on the shown area. Source: United Nations International and Administrative Boundaries Resources -180.0 -89.90000152599998 180.0 83.62741851600008 grid_data_core_pro:UN0_administrative_boundaries_polygons_2018 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 41 1023 0 1023 EPSG:3857:11 82 2047 0 2047 EPSG:3857:12 165 4095 0 4095 EPSG:3857:13 330 8191 0 8191 EPSG:3857:14 660 16383 0 16383 EPSG:3857:15 1320 32767 0 32767 EPSG:3857:16 2641 65535 0 65535 EPSG:3857:17 5283 131071 0 131071 EPSG:3857:18 10566 262143 0 262143 EPSG:3857:19 21132 524287 0 524287 EPSG:3857:20 42264 1048575 0 1048575 EPSG:3857:21 84529 2097151 0 2097151 EPSG:3857:22 169058 4194303 0 4194304 EPSG:3857:23 338117 8388607 0 8388608 EPSG:3857:24 676235 16777215 0 16777215 EPSG:3857:25 1352470 33554431 0 33554431 EPSG:3857:26 2704940 67108863 0 67108863 EPSG:3857:27 5409880 134217727 0 134217727 EPSG:3857:28 10819760 268435455 0 268435456 EPSG:3857:29 21639520 536870911 0 536870911 EPSG:3857:30 43279041 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 9 255 0 511 EPSG:4326:9 18 511 0 1023 EPSG:4326:10 36 1023 0 2047 EPSG:4326:11 72 2046 0 4095 EPSG:4326:12 145 4093 0 8191 EPSG:4326:13 290 8187 0 16383 EPSG:4326:14 580 16374 0 32767 EPSG:4326:15 1160 32749 0 65535 EPSG:4326:16 2320 65499 0 131071 EPSG:4326:17 4640 130999 0 262143 EPSG:4326:18 9280 261998 0 524287 EPSG:4326:19 18561 523996 0 1048575 EPSG:4326:20 37122 1047993 0 2097151 EPSG:4326:21 74245 2095986 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 41 1023 0 1023 EPSG:3857:11 82 2047 0 2047 EPSG:3857:12 165 4095 0 4095 EPSG:3857:13 330 8191 0 8191 EPSG:3857:14 660 16383 0 16383 EPSG:3857:15 1320 32767 0 32767 EPSG:3857:16 2641 65535 0 65535 EPSG:3857:17 5283 131071 0 131071 EPSG:3857:18 10566 262143 0 262143 EPSG:3857:19 21132 524287 0 524287 EPSG:3857:20 42264 1048575 0 1048575 EPSG:3857:21 84529 2097151 0 2097152 EPSG:3857:22 169058 4194303 0 4194304 EPSG:3857:23 338117 8388607 0 8388607 EPSG:3857:24 676235 16777215 0 16777215 EPSG:3857:25 1352470 33554431 0 33554431 EPSG:3857:26 2704940 67108863 0 67108863 EPSG:3857:27 5409880 134217727 0 134217728 EPSG:3857:28 10819760 268435455 0 268435455 EPSG:3857:29 21639520 536870911 0 536870911 EPSG:3857:30 43279041 1073741823 0 1073741824 Crop Suitability Change 1981-2040 This dataset show general agricultural suitability at a spatial resolution of 30 arc-second (~1km), considering rainfed conditions and irrigation on currently irrigated areas. The agricultural suitability represents for each pixel the maximum suitability value of considered 16 plants, including: We show a subset of the data that covers three time periods (1981-2010, 2011-2040, 2071-2100), as well as changes in agricultural suitability over the same periods.<br><br>For futher details see: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107522">Zabel F., Putzenlechner B., Mauser W. (2014): Global agricultural land resources – a high resolution suitability evaluation and its perspectives until 2100 under climate change conditions</a><br/><br>Data can also be downloaded from <a href="http://geoportal-glues.ufz.de/stories/globalsuitability.html">here</a>.<br/> -180.0 -60.0 180.0 90.0 MapX_UNDP:overall_cropsuit_i_diff_19812010_20112040 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 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179.99999999998727 32.999190566 MapX_UNDP:mangroves_SOCS_0_100cm_30m_opt_deflate image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 0 7 EPSG:3857:4 6 9 0 15 EPSG:3857:5 12 19 0 31 EPSG:3857:6 25 39 0 63 EPSG:3857:7 51 79 0 127 EPSG:3857:8 103 158 0 255 EPSG:3857:9 206 316 0 511 EPSG:3857:10 412 632 0 1023 EPSG:3857:11 824 1265 0 2047 EPSG:3857:12 1649 2530 0 4095 EPSG:3857:13 3299 5061 0 8191 EPSG:3857:14 6599 10122 0 16383 EPSG:3857:15 13199 20244 0 32767 EPSG:3857:16 26398 40489 0 65535 EPSG:3857:17 52796 80979 0 131071 EPSG:3857:18 105592 161958 0 262143 EPSG:3857:19 211184 323917 0 524287 EPSG:3857:20 422368 647835 0 1048575 EPSG:3857:21 844737 1295670 0 2097151 EPSG:3857:22 1689475 2591340 0 4194304 EPSG:3857:23 3378951 5182680 0 8388608 EPSG:3857:24 6757902 10365361 0 16777215 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Acceleration 0.5 Sec 975 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_05_s_975_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Year precipitations 2014 - Central African Republic Total precipitations observed in 2014 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2014_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Global Reference Evapo-Transpiration (Global-ET0) CGIAR Potential Evapo-Transpiration (PET) is a measure of the ability of the atmosphere to remove water through Evapo-Transpiration (ET) processes. Among several equations to estimate PET, a FAO application of the Penman-Monteith equation (Allen et al. 1998), here referred as FAOPM, is currently widely considered as a standard method (Walter et al. 2000). The FAO introduced the definition of PET as the ET of a reference crop (ET0) under optimal conditions, having the characteristics of well-watered grass with an assumed height of 12 centimeters, a fixed surface resistance of 70 seconds per meter and an albedo of 0.23 (Allen et al. 1998). The FAO-PM is a predominately physically based approach, which can be used globally because it does not require estimations of additional site-specific parameters. However, a major drawback of the FAO-PM method is its relatively high need for specific data for a variety of parameters (i.e. windspeed, relative humidity, solar radiation, etc.). The Global Reference Evapo-Transpiration (Global-ET0) dataset provide high-resolution (30 arc-seconds) global raster climate data for the 1970-2000 period, related to evapo-transpiration processes and rainfall deficit for potential vegetative growth, based upon implementation of a Penman Montieth Reference Evapotranspiration (ET0) equation. The geo-spatial datasets has been produced by Antonio Trabucco and Robert Zomer, with the support of the CGIAR-CSI (funding from IFPRI Project No. 203008.000.002 515-01-01). These datasets have been downloaded and are available from the CGIAR-CSI GeoPortal (https://cgiarcsi.community). The Consortium for Spatial Information (CGIAR-CSI) is an initiative of the Consultative Group for International Agriculture Research (CGIAR), linking the international science, research and development communities, with CGIAR scientists, national and international partners, and others working to apply and advance geospatial science for sustainable development, conservation, and poverty alleviation in developing countries. The Global-Aridity_ET0 and Global-ET0 datasets are provided for non-commercial use in standard GeoTiff format, at 30 arc seconds or ~ 1km at the equator, to support studies contributing to sustainable development, biodiversity and environmental conservation, poverty alleviation, and adaption to climate change globally, and in particular in developing countries. Comments, feedback, suggestions or bug reports regarding downloading of the Global-ET0 and Global-Aridity datasets should be sent to: csi@cgiar.org. Technical questions regarding the Global-ET0 and Global-Aridity_ET0 datasets can be directed to Antonio Trabucco: antoniotrabucco@cmcc.it . Trabucco, A., and Zomer, R.J. 2018. Global Aridity Index and Potential Evapo-Transpiration (ET0) Climate Database v2. CGIAR Consortium for Spatial Information (CGIAR-CSI). Published online, available from the CGIAR-CSI GeoPortal at <a href="https://cgiarcsi.community"target="_blank">https://cgiarcsi.community</a> -180.0 -59.99999997599997 179.99999998616659 90.0 UN_Sahel:et0_yr_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 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105908314 185077547 190234988 EPSG:3857:29 203572203 211816629 370155095 380469976 EPSG:3857:30 407144406 423633259 740310191 760939952 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 2 2 11 11 EPSG:4326:4 4 4 22 22 EPSG:4326:5 8 9 44 45 EPSG:4326:6 17 19 88 90 EPSG:4326:7 35 38 176 181 EPSG:4326:8 71 77 353 362 EPSG:4326:9 142 155 706 725 EPSG:4326:10 285 310 1412 1451 EPSG:4326:11 570 620 2824 2902 EPSG:4326:12 1141 1241 5648 5805 EPSG:4326:13 2283 2482 11296 11611 EPSG:4326:14 4566 4964 22592 23222 EPSG:4326:15 9132 9929 45184 46444 EPSG:4326:16 18265 19858 90369 92888 EPSG:4326:17 36530 39716 180739 185776 EPSG:4326:18 73060 79432 361479 371552 EPSG:4326:19 146121 158864 722959 743105 EPSG:4326:20 292242 317728 1445918 1486210 EPSG:4326:21 584484 635456 2891836 2972421 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 11 11 EPSG:3857:5 12 12 22 22 EPSG:3857:6 24 25 44 45 EPSG:3857:7 48 50 88 90 EPSG:3857:8 97 101 176 181 EPSG:3857:9 194 202 353 362 EPSG:3857:10 388 404 706 725 EPSG:3857:11 776 808 1412 1451 EPSG:3857:12 1553 1616 2824 2902 EPSG:3857:13 3106 3232 5648 5805 EPSG:3857:14 6212 6464 11296 11611 EPSG:3857:15 12425 12928 22592 23222 EPSG:3857:16 24850 25856 45184 46444 EPSG:3857:17 49700 51713 90369 92888 EPSG:3857:18 99400 103426 180739 185776 EPSG:3857:19 198800 206852 361479 371552 EPSG:3857:20 397601 413704 722959 743105 EPSG:3857:21 795203 827408 1445918 1486210 EPSG:3857:22 1590407 1654817 2891836 2972421 EPSG:3857:23 3180815 3309634 5783673 5944843 EPSG:3857:24 6361631 6619269 11567346 11889686 EPSG:3857:25 12723262 13238539 23134693 23779373 EPSG:3857:26 25446525 26477078 46269386 47558747 EPSG:3857:27 50893050 52954157 92538773 95117494 EPSG:3857:28 101786101 105908314 185077547 190234988 EPSG:3857:29 203572203 211816629 370155095 380469976 EPSG:3857:30 407144406 423633259 740310191 760939952 afg_biodiversity_intactness_index 68.224999007 35.441666285 75.158332313 39.858332934 afg_transboundary:afg_biodiversity_intactness_index image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 11 11 EPSG:3857:5 12 12 22 22 EPSG:3857:6 24 25 44 45 EPSG:3857:7 48 50 88 90 EPSG:3857:8 97 101 176 181 EPSG:3857:9 194 202 353 362 EPSG:3857:10 388 404 706 725 EPSG:3857:11 776 808 1412 1451 EPSG:3857:12 1552 1616 2824 2903 EPSG:3857:13 3105 3232 5648 5806 EPSG:3857:14 6211 6465 11296 11612 EPSG:3857:15 12422 12930 22593 23225 EPSG:3857:16 24844 25860 45187 46450 EPSG:3857:17 49688 51720 90375 92900 EPSG:3857:18 99376 103440 180751 185800 EPSG:3857:19 198753 206881 361503 371601 EPSG:3857:20 397507 413763 723007 743202 EPSG:3857:21 795014 827527 1446015 1486405 EPSG:3857:22 1590028 1655055 2892030 2972810 EPSG:3857:23 3180056 3310111 5784061 5945620 EPSG:3857:24 6360113 6620223 11568123 11891240 EPSG:3857:25 12720227 13240446 23136246 23782480 EPSG:3857:26 25440455 26480892 46272493 47564960 EPSG:3857:27 50880911 52961785 92544987 95129921 EPSG:3857:28 101761822 105923571 185089974 190259842 EPSG:3857:29 203523644 211847142 370179948 380519684 EPSG:3857:30 407047289 423694284 740359897 761039369 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 2 2 11 11 EPSG:4326:4 4 4 22 22 EPSG:4326:5 8 9 44 45 EPSG:4326:6 17 19 88 90 EPSG:4326:7 35 38 176 181 EPSG:4326:8 71 77 353 362 EPSG:4326:9 142 155 706 725 EPSG:4326:10 285 310 1412 1451 EPSG:4326:11 570 620 2824 2903 EPSG:4326:12 1141 1241 5648 5806 EPSG:4326:13 2282 2483 11296 11612 EPSG:4326:14 4564 4966 22593 23225 EPSG:4326:15 9128 9932 45187 46450 EPSG:4326:16 18256 19864 90375 92900 EPSG:4326:17 36512 39728 180751 185800 EPSG:4326:18 73024 79456 361503 371601 EPSG:4326:19 146048 158912 723007 743202 EPSG:4326:20 292096 317825 1446015 1486405 EPSG:4326:21 584192 635650 2892030 2972810 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 11 11 EPSG:3857:5 12 12 22 22 EPSG:3857:6 24 25 44 45 EPSG:3857:7 48 50 88 90 EPSG:3857:8 97 101 176 181 EPSG:3857:9 194 202 353 362 EPSG:3857:10 388 404 706 725 EPSG:3857:11 776 808 1412 1451 EPSG:3857:12 1552 1616 2824 2903 EPSG:3857:13 3105 3232 5648 5806 EPSG:3857:14 6211 6465 11296 11612 EPSG:3857:15 12422 12930 22593 23225 EPSG:3857:16 24844 25860 45187 46450 EPSG:3857:17 49688 51720 90375 92900 EPSG:3857:18 99376 103440 180751 185800 EPSG:3857:19 198753 206881 361503 371601 EPSG:3857:20 397507 413763 723007 743202 EPSG:3857:21 795014 827527 1446015 1486405 EPSG:3857:22 1590028 1655055 2892030 2972810 EPSG:3857:23 3180056 3310111 5784061 5945620 EPSG:3857:24 6360113 6620223 11568123 11891240 EPSG:3857:25 12720227 13240446 23136246 23782480 EPSG:3857:26 25440455 26480892 46272493 47564960 EPSG:3857:27 50880911 52961785 92544987 95129921 EPSG:3857:28 101761822 105923571 185089974 190259842 EPSG:3857:29 203523644 211847142 370179948 380519684 EPSG:3857:30 407047289 423694284 740359897 761039369 Cities with more than 15'000 inhabitants -177.952224731445 -47.0626029968262 180.0 78.8466567993164 grid_data_core:city15k_gis image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 24 0 63 EPSG:4326:6 3 48 0 127 EPSG:4326:7 7 97 1 255 EPSG:4326:8 15 194 2 511 EPSG:4326:9 31 389 5 1023 EPSG:4326:10 63 779 11 2047 EPSG:4326:11 126 1559 23 4095 EPSG:4326:12 253 3118 46 8191 EPSG:4326:13 507 6237 93 16383 EPSG:4326:14 1015 12475 186 32767 EPSG:4326:15 2030 24951 372 65535 EPSG:4326:16 4060 49902 745 131071 EPSG:4326:17 8121 99805 1491 262143 EPSG:4326:18 16243 199611 2982 524287 EPSG:4326:19 32486 399223 5964 1048575 EPSG:4326:20 64972 798447 11929 2097151 EPSG:4326:21 129945 1596895 23858 4194303 EPSG:900913 Combination Tsunami/Coral reefs at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_cor6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Total built-up surface in 2000 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_2000 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Total built-up surface in 2005 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_2005 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Mean temperatures 2005 - Central African Republic Mean observed temperatures in 2005 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2005_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 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309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 TZA_kilombero_sequest_fut_SAGCOTint 34.553167266769464 -10.038048450490551 37.239835341004294 -7.663994368030097 TEEB:sequest_fut_SAGCOTint_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 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EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 Commercial Activity (Shipping Lanes) 2013 - KNB Vessel identity and location information was obtained using two approaches. (1) Over the past 20 years, 10-20% of the vessel fleet has voluntarily participated in collecting meteorological data for the open ocean, which includes location at the time of measurement, as part of the Volunteer Observing System (VOS). (2) In order to improve maritime safety, in 2002 the International Maritime Organization SOLAS agreement required all vessels over 300 gross tonnage (GT) and vessels carrying passengers to equip Automatic Identification System (AIS) transceivers, which use the Global Positioning System (GPS) to precisely locate vessels. Eight broad classes of vessels were taken into account separately: authority, cargo, fishing, high-speed, passenger, pleasure, support, tanker and an ‘other’ class. The vessel classes which move globally (cargo, tanker, and passenger) are required to carry AIS transceivers, and in these three classes 60-70% of the total vessel fleet was observed using AIS. The resulting data layer is primarily composed of these vessel classes in both the AIS and VOS data sources, and is almost exclusively these ship types in the open ocean. We used a simple linear average of the two data sources, producing a final model resolved for the whole ocean at a resolution of 0.1 decimal degrees (~11km). Data have limited observation frequency, leading to gaps that when directly interpolated with geodesic paths, create invalid routes which cross land masses. Routing model was used to create a visibility graph of the oceans, creating valid potential movement paths. These movement paths are based on the assumption that mariners will prefer great circle distances when possible. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). 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62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 greg_zonalstat_s5 5.908956119238116 45.78873284526699 10.558914252756068 47.813923579718775 sdc_test:greg_zonalstat_s5 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 2 4 4 EPSG:3857:4 5 5 8 8 EPSG:3857:5 11 11 16 16 EPSG:3857:6 22 22 33 33 EPSG:3857:7 44 45 66 67 EPSG:3857:8 89 91 132 135 EPSG:3857:9 178 182 264 271 EPSG:3857:10 356 365 528 542 EPSG:3857:11 713 730 1057 1084 EPSG:3857:12 1426 1460 2115 2168 EPSG:3857:13 2853 2921 4230 4336 EPSG:3857:14 5707 5842 8460 8672 EPSG:3857:15 11415 11685 16921 17345 EPSG:3857:16 22831 23370 33843 34690 EPSG:3857:17 45663 46740 67687 69380 EPSG:3857:18 91327 93481 135374 138760 EPSG:3857:19 182654 186963 270749 277521 EPSG:3857:20 365308 373927 541499 555043 EPSG:3857:21 730617 747854 1082998 1110086 EPSG:3857:22 1461234 1495709 2165996 2220172 EPSG:3857:23 2922469 2991419 4331992 4440344 EPSG:3857:24 5844938 5982838 8663985 8880689 EPSG:3857:25 11689877 11965677 17327970 17761378 EPSG:3857:26 23379754 23931354 34655941 35522756 EPSG:3857:27 46759509 47862709 69311882 71045512 EPSG:3857:28 93519018 95725419 138623765 142091025 EPSG:3857:29 187038036 191450839 277247530 284182050 EPSG:3857:30 374076072 382901679 554495060 568364100 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 0 0 4 4 EPSG:4326:3 1 1 8 8 EPSG:4326:4 3 3 16 16 EPSG:4326:5 7 7 33 33 EPSG:4326:6 14 15 66 67 EPSG:4326:7 29 31 132 135 EPSG:4326:8 59 62 264 271 EPSG:4326:9 119 125 528 542 EPSG:4326:10 239 251 1057 1084 EPSG:4326:11 479 503 2115 2168 EPSG:4326:12 959 1006 4230 4336 EPSG:4326:13 1919 2012 8460 8672 EPSG:4326:14 3839 4024 16921 17345 EPSG:4326:15 7679 8048 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2922469 2991419 4331992 4440344 EPSG:3857:24 5844938 5982838 8663985 8880689 EPSG:3857:25 11689877 11965677 17327970 17761378 EPSG:3857:26 23379754 23931354 34655941 35522756 EPSG:3857:27 46759509 47862709 69311882 71045512 EPSG:3857:28 93519018 95725419 138623765 142091025 EPSG:3857:29 187038036 191450839 277247530 284182050 EPSG:3857:30 374076072 382901679 554495060 568364100 TZA_kilombero_sequest_fut_SAGCOT_wgs84_opt 34.553167266769464 -10.038048450490551 37.239835341004294 -7.663994368030097 TEEB:sequest_fut_SAGCOT_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 19 19 EPSG:4326:5 17 17 38 38 EPSG:4326:6 34 35 76 77 EPSG:4326:7 69 71 152 154 EPSG:4326:8 138 142 305 308 EPSG:4326:9 277 284 610 617 EPSG:4326:10 555 569 1220 1235 EPSG:4326:11 1111 1138 2441 2471 EPSG:4326:12 2222 2276 4882 4943 EPSG:4326:13 4444 4552 9764 9886 EPSG:4326:14 8889 9105 19529 19773 EPSG:4326:15 17779 18211 39058 39547 EPSG:4326:16 35558 36422 78116 79094 EPSG:4326:17 71116 72845 156232 158189 EPSG:4326:18 142233 145690 312465 316378 EPSG:4326:19 284467 291381 624931 632756 EPSG:4326:20 568934 582763 1249862 1265513 EPSG:4326:21 1137868 1165527 2499725 2531027 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 Average year temperature (1991-2000) Average year temperature in °Celsius across the period 1991-2000. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_00_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Peak Ground Acceleration PGA 1500 Years (cm/s2) For the GAR Atlas, a fully probabilistic seismic hazard analysis at global level was developed by CIMNE and INGENIAR Ltda. This hazard model is a continuation and improvement of the one developed in the framework of GAR13 where a set of tectonic provinces were identified and characterized by means of a set of parameters that describe the future seismic activity on each of them based on historical records together with relationships to obtain hazard intensities as a function of magnitude and distance. The hazard analysis was performed using the program CRISIS2014, a state-of-the-art tool for these kinds of tasks and widely known and acknowledged by experts in the field across the world. The chosen hazard intensity measure for this case was spectral acceleration and to guarantee a good connection between the hazard and the exposure characteristics, results for several ordinates beteween 0.0 and 2.3 seconds were computed. More details about the probabilistic seismic hazard analysis can be found in Cardona et al. (2015). -180.0 -90.0 180.0 90.0 wesr_risk:pga_1500_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 mosaic_2017_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:mosaic_2017_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Kerala Flood 200 Years RP - Historical Kerala State flood hazard map - Historical. Maximum expected flood event water height in a 200 years return period, expressed in cm. 74.85875 8.25375 77.49291666666667 12.842916666666673 ECO-DRR:Kerala_Flood_200_Yrs_Historical image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185582 187500 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67101021 79265586 79377561 EPSG:3857:28 133956751 134202043 158531172 158755123 EPSG:3857:29 267913502 268404087 317062345 317510247 EPSG:3857:30 535827005 536808174 634124691 635020494 Forest Structual Condition Index (2019) (Montana State University) The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/>To download a subset of the FII data clipped to your country please click <a href="https://app.box.com/s/380mxwzhuqece2v9fy8ovhcv3s5cb82g/folder/71324508781"target="_blank">here</a>.<br/> -81.70887178141503 -20.58264894738855 153.42811827730736 25.91783325130279 MapX_UNDP:SCI_merged image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 871 1143 559 1896 EPSG:3857:12 1742 2287 1118 3793 EPSG:3857:13 3485 4574 2236 7587 EPSG:3857:14 6970 9149 4473 15174 EPSG:3857:15 13940 18299 8946 30349 EPSG:3857:16 27880 36598 17893 60698 EPSG:3857:17 55760 73196 35786 121397 EPSG:3857:18 111520 146392 71573 242794 EPSG:3857:19 223041 292785 143146 485589 EPSG:3857:20 446082 585571 286293 971179 EPSG:3857:21 892164 1171143 572587 1942359 EPSG:3857:22 1784328 2342287 1145174 3884719 EPSG:3857:23 3568657 4684575 2290349 7769438 EPSG:3857:24 7137315 9369151 4580698 15538876 EPSG:3857:25 14274631 18738303 9161397 31077753 EPSG:3857:26 28549263 37476607 18322794 62155506 EPSG:3857:27 57098527 74953214 36645588 124311012 EPSG:3857:28 114197054 149906428 73291177 248622024 EPSG:3857:29 228394108 299812857 146582354 497244049 EPSG:3857:30 456788217 599625715 293164709 994488099 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 91 157 139 474 EPSG:4326:9 182 314 279 948 EPSG:4326:10 364 629 559 1896 EPSG:4326:11 729 1258 1118 3793 EPSG:4326:12 1458 2516 2236 7587 EPSG:4326:13 2916 5032 4473 15174 EPSG:4326:14 5832 10065 8946 30349 EPSG:4326:15 11665 20130 17893 60698 EPSG:4326:16 23331 40261 35786 121397 EPSG:4326:17 46663 80523 71573 242794 EPSG:4326:18 93326 161047 143146 485589 EPSG:4326:19 186652 322095 286293 971179 EPSG:4326:20 373305 644190 572587 1942359 EPSG:4326:21 746611 1288381 1145174 3884719 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 871 1143 559 1896 EPSG:3857:12 1742 2287 1118 3793 EPSG:3857:13 3485 4574 2236 7587 EPSG:3857:14 6970 9149 4473 15174 EPSG:3857:15 13940 18299 8946 30349 EPSG:3857:16 27880 36598 17893 60698 EPSG:3857:17 55760 73196 35786 121397 EPSG:3857:18 111520 146392 71573 242794 EPSG:3857:19 223041 292785 143146 485589 EPSG:3857:20 446082 585571 286293 971179 EPSG:3857:21 892164 1171143 572587 1942359 EPSG:3857:22 1784328 2342287 1145174 3884719 EPSG:3857:23 3568657 4684575 2290349 7769438 EPSG:3857:24 7137315 9369151 4580698 15538876 EPSG:3857:25 14274631 18738303 9161397 31077753 EPSG:3857:26 28549263 37476607 18322794 62155506 EPSG:3857:27 57098527 74953214 36645588 124311012 EPSG:3857:28 114197054 149906428 73291177 248622024 EPSG:3857:29 228394108 299812857 146582354 497244049 EPSG:3857:30 456788217 599625715 293164709 994488099 Flood Hazard 500 Years (cm) The GAR Atlas global flood hazard assessment uses a probabilistic approach for modelling riverine flood major river basins around the globe. This has been possible after compiling a global database of stream-flow data, merging different sources and gathering more than 8000 stations over the globe in order to calculate the range of possible discharges from very low to the maximum possible scales at different locations along the rivers. The calculated discharges were introduced in the river sections to model water levels downstream. This procedure allowed for the determination of stochastic event-sets of riverine floods from which hazard maps for several return periods (25, 50, 100, 200, 500, 1000 years) were obtained. The hazard maps are developed at 1kmx1km resolution and have been validated against satellite flood footprints from different sources (DFO archive, UNOSAT flood portal) performing well especially for big events For smaller events (lower return periods), the GAR Atlas flood hazard maps tend to overestimate with respect to similar maps produced locally (hazard maps where available for some countries and were used as benchmark). The main issue being that, due to the resolution, the GAR Atlas flood hazard maps do not take into account flood defenses that are normally present to preserve the value exposed to floods. More information about the flood hazard assessment can be found in the background paper (Rudari et al., 2015). -141.09900045782885 -56.085762831133565 180.0 60.09233546603441 wesr_risk:fl_hazard_500_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 1 15 EPSG:3857:5 9 22 3 31 EPSG:3857:6 18 44 6 63 EPSG:3857:7 37 88 13 127 EPSG:3857:8 74 176 27 255 EPSG:3857:9 148 352 55 511 EPSG:3857:10 296 705 110 1023 EPSG:3857:11 593 1411 221 2047 EPSG:3857:12 1187 2822 442 4095 EPSG:3857:13 2374 5644 885 8191 EPSG:3857:14 4749 11289 1770 16383 EPSG:3857:15 9498 22578 3540 32767 EPSG:3857:16 18997 45156 7081 65535 EPSG:3857:17 37995 90312 14163 131071 EPSG:3857:18 75991 180625 28326 262143 EPSG:3857:19 151983 361251 56653 524287 EPSG:3857:20 303967 722503 113307 1048575 EPSG:3857:21 607934 1445007 226614 2097151 EPSG:3857:22 1215869 2890014 453229 4194304 EPSG:3857:23 2431739 5780029 906458 8388608 EPSG:3857:24 4863479 11560058 1812917 16777215 EPSG:3857:25 9726958 23120116 3625835 33554431 EPSG:3857:26 19453916 46240233 7251671 67108863 EPSG:3857:27 38907833 92480467 14503343 134217727 EPSG:3857:28 77815666 184960934 29006687 268435456 EPSG:3857:29 155631333 369921868 58013375 536870911 EPSG:3857:30 311262667 739843736 116026750 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 1 15 EPSG:4326:4 2 12 3 31 EPSG:4326:5 5 25 6 63 EPSG:4326:6 10 51 13 127 EPSG:4326:7 21 103 27 255 EPSG:4326:8 42 207 55 511 EPSG:4326:9 85 415 110 1023 EPSG:4326:10 170 831 221 2047 EPSG:4326:11 340 1662 442 4095 EPSG:4326:12 680 3324 885 8191 EPSG:4326:13 1361 6648 1770 16383 EPSG:4326:14 2722 13297 3540 32767 EPSG:4326:15 5444 26594 7081 65535 EPSG:4326:16 10889 53188 14163 131071 EPSG:4326:17 21778 106376 28326 262143 EPSG:4326:18 43556 212752 56653 524287 EPSG:4326:19 87112 425505 113307 1048575 EPSG:4326:20 174224 851011 226614 2097151 EPSG:4326:21 348449 1702022 453229 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 1 15 EPSG:3857:5 9 22 3 31 EPSG:3857:6 18 44 6 63 EPSG:3857:7 37 88 13 127 EPSG:3857:8 74 176 27 255 EPSG:3857:9 148 352 55 511 EPSG:3857:10 296 705 110 1023 EPSG:3857:11 593 1411 221 2047 EPSG:3857:12 1187 2822 442 4095 EPSG:3857:13 2374 5644 885 8191 EPSG:3857:14 4749 11289 1770 16383 EPSG:3857:15 9498 22578 3540 32767 EPSG:3857:16 18997 45156 7081 65535 EPSG:3857:17 37995 90312 14163 131071 EPSG:3857:18 75991 180625 28326 262143 EPSG:3857:19 151983 361251 56653 524287 EPSG:3857:20 303967 722503 113307 1048575 EPSG:3857:21 607934 1445007 226614 2097152 EPSG:3857:22 1215869 2890014 453229 4194304 EPSG:3857:23 2431739 5780029 906458 8388607 EPSG:3857:24 4863479 11560058 1812917 16777215 EPSG:3857:25 9726958 23120116 3625835 33554431 EPSG:3857:26 19453916 46240233 7251671 67108863 EPSG:3857:27 38907833 92480467 14503343 134217728 EPSG:3857:28 77815666 184960934 29006687 268435455 EPSG:3857:29 155631333 369921868 58013375 536870911 EPSG:3857:30 311262667 739843736 116026750 1073741824 MAPA_NACIONAL_DE_ECOSISTEMAS Layer provided by Ministry of Environment of Peru. This link has the documentation, definitions and methods of the national map of ecosystems. https://geoservidor.minam.gob.pe/wp-content/uploads/2017/06/MEMORIA-DESCRIPTIVA-MAPA-DE-ECOSISTEMAS.pdf -81.64209769673546 -18.407132990582912 -68.4732307911745 -0.03837091357564947 wesr_cca:MAPA_NACIONAL_DE_ECOSISTEMAS image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 0 0 EPSG:3857:2 2 2 1 1 EPSG:3857:3 4 4 2 2 EPSG:3857:4 8 8 4 4 EPSG:3857:5 16 17 8 9 EPSG:3857:6 32 35 17 19 EPSG:3857:7 64 70 34 39 EPSG:3857:8 128 141 69 79 EPSG:3857:9 256 282 139 158 EPSG:3857:10 512 565 279 317 EPSG:3857:11 1024 1130 559 634 EPSG:3857:12 2048 2261 1119 1268 EPSG:3857:13 4096 4522 2238 2537 EPSG:3857:14 8193 9044 4476 5075 EPSG:3857:15 16387 18089 8952 10151 EPSG:3857:16 32774 36178 17905 20302 EPSG:3857:17 65549 72356 35811 40605 EPSG:3857:18 131099 144712 71622 81211 EPSG:3857:19 262199 289424 143244 162422 EPSG:3857:20 524399 578849 286488 324845 EPSG:3857:21 1048799 1157698 572976 649690 EPSG:3857:22 2097599 2315397 1145952 1299381 EPSG:3857:23 4195198 4630795 2291905 2598762 EPSG:3857:24 8390396 9261591 4583810 5197524 EPSG:3857:25 16780792 18523182 9167620 10395048 EPSG:3857:26 33561584 37046365 18335241 20790096 EPSG:3857:27 67123169 74092731 36670483 41580193 EPSG:3857:28 134246339 148185463 73340967 83160386 EPSG:3857:29 268492678 296370927 146681935 166320773 EPSG:3857:30 536985357 592741855 293363870 332641546 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 1 1 1 1 EPSG:4326:2 2 2 2 2 EPSG:4326:3 4 4 4 4 EPSG:4326:4 8 9 8 9 EPSG:4326:5 16 19 17 19 EPSG:4326:6 32 38 34 39 EPSG:4326:7 64 77 69 79 EPSG:4326:8 128 154 139 158 EPSG:4326:9 256 308 279 317 EPSG:4326:10 512 616 559 634 EPSG:4326:11 1024 1233 1119 1268 EPSG:4326:12 2048 2466 2238 2537 EPSG:4326:13 4097 4933 4476 5075 EPSG:4326:14 8195 9867 8952 10151 EPSG:4326:15 16390 19734 17905 20302 EPSG:4326:16 32781 39469 35811 40605 EPSG:4326:17 65563 78939 71622 81211 EPSG:4326:18 131127 157879 143244 162422 EPSG:4326:19 262255 315758 286488 324845 EPSG:4326:20 524511 631517 572976 649690 EPSG:4326:21 1049023 1263034 1145952 1299381 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 0 0 EPSG:3857:2 2 2 1 1 EPSG:3857:3 4 4 2 2 EPSG:3857:4 8 8 4 4 EPSG:3857:5 16 17 8 9 EPSG:3857:6 32 35 17 19 EPSG:3857:7 64 70 34 39 EPSG:3857:8 128 141 69 79 EPSG:3857:9 256 282 139 158 EPSG:3857:10 512 565 279 317 EPSG:3857:11 1024 1130 559 634 EPSG:3857:12 2048 2261 1119 1268 EPSG:3857:13 4096 4522 2238 2537 EPSG:3857:14 8193 9044 4476 5075 EPSG:3857:15 16387 18089 8952 10151 EPSG:3857:16 32774 36178 17905 20302 EPSG:3857:17 65549 72356 35811 40605 EPSG:3857:18 131099 144712 71622 81211 EPSG:3857:19 262199 289424 143244 162422 EPSG:3857:20 524399 578849 286488 324845 EPSG:3857:21 1048799 1157698 572976 649690 EPSG:3857:22 2097599 2315397 1145952 1299381 EPSG:3857:23 4195198 4630795 2291905 2598762 EPSG:3857:24 8390396 9261591 4583810 5197524 EPSG:3857:25 16780792 18523182 9167620 10395048 EPSG:3857:26 33561584 37046365 18335241 20790096 EPSG:3857:27 67123169 74092731 36670483 41580193 EPSG:3857:28 134246339 148185463 73340967 83160386 EPSG:3857:29 268492678 296370927 146681935 166320773 EPSG:3857:30 536985357 592741855 293363870 332641546 GHS built-up volume grid (2020) The GHS-BUILT-V dataset depicts the distribution of the built-up (BU) volume estimates between 1975 and 2030 in 5 years intervals and two functional use components a) the total BU volume and b) the non-residential (NRES) BU volume. The data is made by projection of the assessment of the average building height in the year 2018 (GHS_BUILT_H_ANBH_E2018_GLOBE_R2023A_54009_100_V1_0) assumed as constant in the 100m resolution cell, to the multitemporal built-up surface estimates (GHS-BUILT-S_GLOBE_R2023A, GHS-BUILT-S_NRES_GLOBE_R2023A). The complete information about the GHSL main products can be found in the GHSL Data Package 2023 report. Publication: Schiavina, Marcello; Freire, Sergio; Alessandra Carioli; MacManus, Kytt (2023): GHS-POP R2023A - GHS population grid multitemporal (1975-2030). European Commission, Joint Research Centre (JRC) [Dataset] doi: 10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE PID: http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe Concept & Methodology: Freire S., MacManus K., Pesaresi M., Doxsey-Whitfield E., Mills J. (2016) Development of new open and free multi-temporal global population grids at 250 m resolution. 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4194303 EPSG:900913 EPSG:3857_512 Landslide hazard exposure 60.879999999999995 23.709999999999994 75.38 36.9 UNDAC-PAK:ls_phex_P3_pak_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 10 11 EPSG:3857:5 12 13 21 22 EPSG:3857:6 24 27 42 45 EPSG:3857:7 49 55 85 90 EPSG:3857:8 99 110 171 181 EPSG:3857:9 199 221 342 363 EPSG:3857:10 398 442 685 726 EPSG:3857:11 797 885 1370 1452 EPSG:3857:12 1595 1770 2740 2905 EPSG:3857:13 3191 3540 5481 5811 EPSG:3857:14 6382 7080 10962 11622 EPSG:3857:15 12765 14161 21925 23245 EPSG:3857:16 25531 28322 43850 46490 EPSG:3857:17 51062 56645 87701 92981 EPSG:3857:18 102125 113291 175403 185962 EPSG:3857:19 204250 226583 350806 371924 EPSG:3857:20 408501 453167 701613 743848 EPSG:3857:21 817003 906335 1403227 1487696 EPSG:3857:22 1634007 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587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 Global Terrestrial Human Footprint (HFP) - 2005 To come -81.71613498761286 -20.61982884080102 153.4232678403954 26.041652531903203 MapX_UNDP:hfp2005_meris_wgs_subset image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27855 36605 17892 60697 EPSG:3857:17 55710 73210 35784 121395 EPSG:3857:18 111420 146421 71568 242791 EPSG:3857:19 222840 292843 143136 485582 EPSG:3857:20 445681 585687 286272 971165 EPSG:3857:21 891362 1171375 572545 1942331 EPSG:3857:22 1782724 2342750 1145090 3884662 EPSG:3857:23 3565448 4685501 2290180 7769325 EPSG:3857:24 7130896 9371002 4580360 15538650 EPSG:3857:25 14261793 18742005 9160720 31077301 EPSG:3857:26 28523587 37484011 18321440 62154602 EPSG:3857:27 57047174 74968023 36642880 124309204 EPSG:3857:28 114094349 149936046 73285761 248618408 EPSG:3857:29 228188699 299872092 146571522 497236816 EPSG:3857:30 456377398 599744184 293143045 994473632 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 90 157 139 474 EPSG:4326:9 181 314 279 948 EPSG:4326:10 363 629 559 1896 EPSG:4326:11 727 1258 1118 3793 EPSG:4326:12 1455 2517 2236 7587 EPSG:4326:13 2910 5034 4473 15174 EPSG:4326:14 5821 10068 8946 30348 EPSG:4326:15 11643 20137 17892 60697 EPSG:4326:16 23286 40275 35784 121395 EPSG:4326:17 46573 80550 71568 242791 EPSG:4326:18 93146 161101 143136 485582 EPSG:4326:19 186292 322203 286272 971165 EPSG:4326:20 372584 644407 572545 1942331 EPSG:4326:21 745168 1288814 1145090 3884662 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 1 2 1 3 EPSG:900913:3 3 4 2 7 EPSG:900913:4 6 8 4 14 EPSG:900913:5 13 17 8 29 EPSG:900913:6 27 35 17 59 EPSG:900913:7 54 71 34 118 EPSG:900913:8 108 142 69 237 EPSG:900913:9 217 285 139 474 EPSG:900913:10 435 571 279 948 EPSG:900913:11 870 1143 559 1896 EPSG:900913:12 1740 2287 1118 3793 EPSG:900913:13 3481 4575 2236 7587 EPSG:900913:14 6963 9151 4473 15174 EPSG:900913:15 13927 18302 8946 30348 EPSG:900913:16 27855 36605 17892 60697 EPSG:900913:17 55710 73210 35784 121395 EPSG:900913:18 111420 146421 71568 242791 EPSG:900913:19 222840 292843 143136 485582 EPSG:900913:20 445681 585687 286272 971165 EPSG:900913:21 891362 1171375 572545 1942331 EPSG:900913:22 1782724 2342750 1145090 3884662 EPSG:900913:23 3565448 4685501 2290180 7769325 EPSG:900913:24 7130896 9371002 4580360 15538650 EPSG:900913:25 14261793 18742005 9160720 31077301 EPSG:900913:26 28523587 37484011 18321440 62154602 EPSG:900913:27 57047174 74968023 36642880 124309204 EPSG:900913:28 114094349 149936046 73285761 248618408 EPSG:900913:29 228188699 299872092 146571522 497236816 EPSG:900913:30 456377398 599744184 293143045 994473632 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27855 36605 17892 60697 EPSG:3857:17 55710 73210 35784 121395 EPSG:3857:18 111420 146421 71568 242791 EPSG:3857:19 222840 292843 143136 485582 EPSG:3857:20 445681 585687 286272 971165 EPSG:3857:21 891362 1171375 572545 1942331 EPSG:3857:22 1782724 2342750 1145090 3884662 EPSG:3857:23 3565448 4685501 2290180 7769325 EPSG:3857:24 7130896 9371002 4580360 15538650 EPSG:3857:25 14261793 18742005 9160720 31077301 EPSG:3857:26 28523587 37484011 18321440 62154602 EPSG:3857:27 57047174 74968023 36642880 124309204 EPSG:3857:28 114094349 149936046 73285761 248618408 EPSG:3857:29 228188699 299872092 146571522 497236816 EPSG:3857:30 456377398 599744184 293143045 994473632 Travel_time_final_Burundi_opt 28.995910775304033 -4.477617488031152 30.8592085848395 -2.305992223429439 AccessMod:Travel_time_final_Burundi_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 64 65 74 74 EPSG:3857:8 129 131 148 149 EPSG:3857:9 259 262 297 299 EPSG:3857:10 518 524 594 599 EPSG:3857:11 1037 1049 1188 1199 EPSG:3857:12 2074 2098 2377 2399 EPSG:3857:13 4148 4197 4755 4798 EPSG:3857:14 8296 8395 9511 9596 EPSG:3857:15 16593 16791 19023 19192 EPSG:3857:16 33187 33583 38046 38385 EPSG:3857:17 66375 67167 76093 76771 EPSG:3857:18 132751 134335 152186 153542 EPSG:3857:19 265503 268671 304372 307085 EPSG:3857:20 531006 537343 608744 614171 EPSG:3857:21 1062013 1074686 1217489 1228343 EPSG:3857:22 2124026 2149373 2434978 2456687 EPSG:3857:23 4248052 4298746 4869957 4913375 EPSG:3857:24 8496104 8597492 9739915 9826751 EPSG:3857:25 16992208 17194985 19479830 19653502 EPSG:3857:26 33984416 34389971 38959661 39307005 EPSG:3857:27 67968832 68779942 77919323 78614010 EPSG:3857:28 135937664 137559885 155838646 157228021 EPSG:3857:29 271875329 275119770 311677292 314456043 EPSG:3857:30 543750659 550239540 623354584 628912086 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 32 33 74 74 EPSG:4326:7 65 67 148 149 EPSG:4326:8 131 134 297 299 EPSG:4326:9 262 268 594 599 EPSG:4326:10 525 537 1188 1199 EPSG:4326:11 1050 1074 2377 2399 EPSG:4326:12 2100 2149 4755 4798 EPSG:4326:13 4200 4299 9511 9596 EPSG:4326:14 8401 8599 19023 19192 EPSG:4326:15 16803 17199 38046 38385 EPSG:4326:16 33607 34398 76093 76771 EPSG:4326:17 67215 68796 152186 153542 EPSG:4326:18 134430 137593 304372 307085 EPSG:4326:19 268860 275186 608744 614171 EPSG:4326:20 537721 550372 1217489 1228343 EPSG:4326:21 1075442 1100744 2434978 2456687 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 64 65 74 74 EPSG:3857:8 129 131 148 149 EPSG:3857:9 259 262 297 299 EPSG:3857:10 518 524 594 599 EPSG:3857:11 1037 1049 1188 1199 EPSG:3857:12 2074 2098 2377 2399 EPSG:3857:13 4148 4197 4755 4798 EPSG:3857:14 8296 8395 9511 9596 EPSG:3857:15 16593 16791 19023 19192 EPSG:3857:16 33187 33583 38046 38385 EPSG:3857:17 66375 67167 76093 76771 EPSG:3857:18 132751 134335 152186 153542 EPSG:3857:19 265503 268671 304372 307085 EPSG:3857:20 531006 537343 608744 614171 EPSG:3857:21 1062013 1074686 1217489 1228343 EPSG:3857:22 2124026 2149373 2434978 2456687 EPSG:3857:23 4248052 4298746 4869957 4913375 EPSG:3857:24 8496104 8597492 9739915 9826751 EPSG:3857:25 16992208 17194985 19479830 19653502 EPSG:3857:26 33984416 34389971 38959661 39307005 EPSG:3857:27 67968832 68779942 77919323 78614010 EPSG:3857:28 135937664 137559885 155838646 157228021 EPSG:3857:29 271875329 275119770 311677292 314456043 EPSG:3857:30 543750659 550239540 623354584 628912086 Tropical cyclone surge hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:cs_phex_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone surge/ Mangroves at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_man9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Winter temperature change (°C) for the period 2040 - 2059 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_djf_MIDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Average year precipitations (1991-2022) Average year precipitations in mm across the period 1991-2022. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_91_22_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tunisia_remote_site_screening_res50 7.5281449999999825 30.245430054000035 11.598144999999983 37.543930054000036 mapx_chemobs:tunisia_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 6 8 8 EPSG:3857:5 12 13 16 17 EPSG:3857:6 24 26 33 34 EPSG:3857:7 49 52 66 68 EPSG:3857:8 99 105 133 136 EPSG:3857:9 198 210 266 272 EPSG:3857:10 396 421 533 544 EPSG:3857:11 793 843 1066 1089 EPSG:3857:12 1586 1686 2133 2179 EPSG:3857:13 3173 3373 4267 4359 EPSG:3857:14 6346 6746 8534 8719 EPSG:3857:15 12692 13493 17069 17439 EPSG:3857:16 25384 26986 34138 34879 EPSG:3857:17 50768 53973 68276 69758 EPSG:3857:18 101536 107947 136553 139517 EPSG:3857:19 203073 215894 273107 279035 EPSG:3857:20 406146 431789 546215 558070 EPSG:3857:21 812292 863579 1092430 1116140 EPSG:3857:22 1624585 1727159 2184861 2232280 EPSG:3857:23 3249171 3454319 4369722 4464560 EPSG:3857:24 6498342 6908639 8739444 8929120 EPSG:3857:25 12996684 13817279 17478889 17858241 EPSG:3857:26 25993368 27634558 34957779 35716482 EPSG:3857:27 51986736 55269117 69915559 71432965 EPSG:3857:28 103973472 110538235 139831119 142865931 EPSG:3857:29 207946945 221076471 279662239 285731863 EPSG:3857:30 415893890 442152942 559324479 571463726 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 2 8 8 EPSG:4326:4 4 5 16 17 EPSG:4326:5 9 10 33 34 EPSG:4326:6 18 21 66 68 EPSG:4326:7 37 42 133 136 EPSG:4326:8 74 84 266 272 EPSG:4326:9 149 169 533 544 EPSG:4326:10 298 339 1066 1089 EPSG:4326:11 596 679 2133 2179 EPSG:4326:12 1193 1359 4267 4359 EPSG:4326:13 2387 2719 8534 8719 EPSG:4326:14 4774 5438 17069 17439 EPSG:4326:15 9549 10877 34138 34879 EPSG:4326:16 19098 21755 68276 69758 EPSG:4326:17 38197 43511 136553 139517 EPSG:4326:18 76394 87023 273107 279035 EPSG:4326:19 152789 174047 546215 558070 EPSG:4326:20 305578 348095 1092430 1116140 EPSG:4326:21 611157 696191 2184861 2232280 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 6 8 8 EPSG:3857:5 12 13 16 17 EPSG:3857:6 24 26 33 34 EPSG:3857:7 49 52 66 68 EPSG:3857:8 99 105 133 136 EPSG:3857:9 198 210 266 272 EPSG:3857:10 396 421 533 544 EPSG:3857:11 793 843 1066 1089 EPSG:3857:12 1586 1686 2133 2179 EPSG:3857:13 3173 3373 4267 4359 EPSG:3857:14 6346 6746 8534 8719 EPSG:3857:15 12692 13493 17069 17439 EPSG:3857:16 25384 26986 34138 34879 EPSG:3857:17 50768 53973 68276 69758 EPSG:3857:18 101536 107947 136553 139517 EPSG:3857:19 203073 215894 273107 279035 EPSG:3857:20 406146 431789 546215 558070 EPSG:3857:21 812292 863579 1092430 1116140 EPSG:3857:22 1624585 1727159 2184861 2232280 EPSG:3857:23 3249171 3454319 4369722 4464560 EPSG:3857:24 6498342 6908639 8739444 8929120 EPSG:3857:25 12996684 13817279 17478889 17858241 EPSG:3857:26 25993368 27634558 34957779 35716482 EPSG:3857:27 51986736 55269117 69915559 71432965 EPSG:3857:28 103973472 110538235 139831119 142865931 EPSG:3857:29 207946945 221076471 279662239 285731863 EPSG:3857:30 415893890 442152942 559324479 571463726 Winter precipitations change (%) for the period 2080 - 2099 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_djf_ENDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Average year precipitations anomalies (1991-2000) against 1901-1920 Average year precipitations anomalies in mm across the period 1991-2000 calculated over the average precipitations per year in the period 1901-1920 (as close as possible to the pre-industrial era). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_91_00_anom_1901_1920 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Precipitation seasonality [coefficient of variation] (2041-2060) RCP8.5 - CIMP5 The Coefficient of Variation is the standard deviation of the monthly precipitation estimates expressed as a percentage of the mean of those estimates (i.e. the annual mean) for the period 2041-2060 based on RCP8.5. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_bio_mon_ACCESS1-0_rcp85_r1i1p1_g025.nc_15_2041-2060_V1.2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 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116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 Fragility The map displays total fragility data at province level scale using the first administrative division polygon files from the Global Administrative Areas database version 2.8. The map retains the five fragility categories seen in the total fragility measure, classifying areas as having low, some, moderate, high, or highest fragility. To help achieve this study’s goal of identifying the intersection of fragility and climate risks globally, this study develops a new fragility measure. Developing a new measure specifically for this purpose provides a comprehensive fragility measure while avoiding use of existing fragility measures that include environmental indicators and thus should not be overlaid on climate hazards. This study uses open-source data to create a measure of state fragility that is similar in composition and outcome to USAID’s internal methods and framework for analyzing fragility.11 Like USAID’s internal measure, the new measure assesses fragility in state effectiveness and legitimacy in four key spheres: political, security, economic, and social. This is based on an understanding of fragility as being rooted in poor state capacity and poor state-society relationships, both of which can contribute to instability. Poor state capacity and state-society relationships can lead to and perpetuate other forms of overt instability, including conflict or an inability to address and mitigate stresses such as a changing environment, difficult global financial situations, or conflict in neighboring states. This <a href="https://pdf.usaid.gov/pdf_docs/PA00TBFH.pdf"target=_blank>document</a> outlines the indicators, data sources, and process used to assess countries’ relative state capacity and state-society relationship on a global scale. -179.99999999999994 -90.0 180.0 83.65833282470703 UN_Sahel:USAID_CMM_frag_0-001_v image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 40 1023 0 1023 EPSG:3857:11 80 2047 0 2047 EPSG:3857:12 161 4095 0 4095 EPSG:3857:13 323 8191 0 8191 EPSG:3857:14 647 16383 0 16383 EPSG:3857:15 1295 32767 0 32767 EPSG:3857:16 2590 65535 0 65535 EPSG:3857:17 5181 131071 0 131071 EPSG:3857:18 10362 262143 0 262143 EPSG:3857:19 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EPSG:3857:25 12070369 16917042 15099494 23767722 EPSG:3857:26 24140738 33834084 30198988 47535445 EPSG:3857:27 48281477 67668168 60397977 95070890 EPSG:3857:28 96562954 135336336 120795955 190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 Evapotranspiration Anomaly 2017 (1-10) USGS Calculated through raster calculator as average of 10 specific rasters, each per month from jan to oct 2017. -20.008449316024837 -38.00309218093754 55.00689406692973 40.004371177405076 MAPX:ET2017_1-10_usgs image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 1 2 3 5 EPSG:4326:3 2 5 7 10 EPSG:4326:4 4 11 14 20 EPSG:4326:5 8 22 28 41 EPSG:4326:6 17 45 56 83 EPSG:4326:7 35 91 113 167 EPSG:4326:8 71 182 227 334 EPSG:4326:9 142 364 455 668 EPSG:4326:10 284 728 910 1336 EPSG:4326:11 568 1456 1820 2673 EPSG:4326:12 1137 2912 3640 5347 EPSG:4326:13 2275 5825 7281 10695 EPSG:4326:14 4550 11651 14562 21390 EPSG:4326:15 9101 23302 29125 42781 EPSG:4326:16 18202 46604 58251 85563 EPSG:4326:17 36405 93209 116502 171126 EPSG:4326:18 72811 186418 233004 342253 EPSG:4326:19 145622 372836 466009 684507 EPSG:4326:20 291245 745672 932018 1369014 EPSG:4326:21 582491 1491344 1864036 2738028 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 1 2 1 2 EPSG:900913:3 3 4 3 5 EPSG:900913:4 6 9 7 10 EPSG:900913:5 12 19 14 20 EPSG:900913:6 24 39 28 41 EPSG:900913:7 48 78 56 83 EPSG:900913:8 96 157 113 167 EPSG:900913:9 193 314 227 334 EPSG:900913:10 387 629 455 668 EPSG:900913:11 775 1258 910 1336 EPSG:900913:12 1550 2516 1820 2673 EPSG:900913:13 3101 5032 3640 5347 EPSG:900913:14 6202 10064 7281 10695 EPSG:900913:15 12404 20128 14562 21390 EPSG:900913:16 24809 40257 29125 42781 EPSG:900913:17 49619 80515 58251 85563 EPSG:900913:18 99238 161030 116502 171126 EPSG:900913:19 198476 322060 233004 342253 EPSG:900913:20 396952 644121 466009 684507 EPSG:900913:21 793904 1288243 932018 1369014 EPSG:900913:22 1587809 2576486 1864036 2738028 EPSG:900913:23 3175619 5152972 3728073 5476057 EPSG:900913:24 6351238 10305945 7456146 10952115 EPSG:900913:25 12702476 20611891 14912293 21904230 EPSG:900913:26 25404953 41223783 29824586 43808460 EPSG:900913:27 50809906 82447566 59649173 87616920 EPSG:900913:28 101619813 164895133 119298346 175233841 EPSG:900913:29 203239627 329790266 238596693 350467682 EPSG:900913:30 406479255 659580532 477193387 700935364 Economic Stock The Global Exposure Database (GED) was developed for GAR15 by UNEP/GRID-Geneva with close collaboration and inputs from WAPMERR (World Agency of Planetary Monitoring and Earthquake Risk Reduction), EU Joint Research Center (JRC), and Kokusai Kogyo. The GED provides estimation on the economic value of the exposed assets (public and private buildings located in urban and rural areas), as well as their physical characteristics and occupancy levels. This information is key to assess the potential damages from different hazards to each of the exposed elements and to assign the appropriate vulnerability models. The global exposure database is developed at 1x1 km spatial resolution at coastal areas and at 5x5 km spatial resolution everywhere else on the globe. The GED is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies. For more details see: De Bono and Chatenoux (2014). -179.99954 -55.71600000000001 179.95786999999999 81.82433 wesr_risk:gar_eco_exp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 10 0 15 EPSG:3857:5 2 21 0 31 EPSG:3857:6 5 43 0 63 EPSG:3857:7 10 87 0 127 EPSG:3857:8 20 175 0 255 EPSG:3857:9 40 351 0 511 EPSG:3857:10 81 703 0 1023 EPSG:3857:11 163 1407 0 2047 EPSG:3857:12 327 2814 0 4095 EPSG:3857:13 655 5629 0 8191 EPSG:3857:14 1311 11259 0 16382 EPSG:3857:15 2623 22518 0 32764 EPSG:3857:16 5247 45036 0 65528 EPSG:3857:17 10494 90072 0 131056 EPSG:3857:18 20989 180145 0 262113 EPSG:3857:19 41978 360291 0 524226 EPSG:3857:20 83957 720582 1 1048453 EPSG:3857:21 167914 1441165 2 2096906 EPSG:3857:22 335828 2882330 5 4193813 EPSG:3857:23 671656 5764660 10 8387626 EPSG:3857:24 1343312 11529320 21 16775252 EPSG:3857:25 2686624 23058641 42 33550505 EPSG:3857:26 5373249 46117282 85 67101010 EPSG:3857:27 10746499 92234565 171 134202020 EPSG:3857:28 21492999 184469131 342 268404041 EPSG:3857:29 42985998 368938262 685 536808083 EPSG:3857:30 85971997 737876524 1371 1073616166 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 5 103 0 255 EPSG:4326:8 11 207 0 511 EPSG:4326:9 23 414 0 1023 EPSG:4326:10 46 828 0 2047 EPSG:4326:11 93 1657 0 4095 EPSG:4326:12 186 3315 0 8191 EPSG:4326:13 372 6631 0 16382 EPSG:4326:14 744 13263 0 32764 EPSG:4326:15 1488 26526 0 65528 EPSG:4326:16 2976 53053 0 131056 EPSG:4326:17 5953 106107 0 262113 EPSG:4326:18 11906 212214 0 524226 EPSG:4326:19 23813 424428 1 1048453 EPSG:4326:20 47626 848857 2 2096906 EPSG:4326:21 95253 1697714 5 4193813 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 10 0 15 EPSG:3857:5 2 21 0 31 EPSG:3857:6 5 43 0 63 EPSG:3857:7 10 87 0 127 EPSG:3857:8 20 175 0 255 EPSG:3857:9 40 351 0 511 EPSG:3857:10 81 703 0 1023 EPSG:3857:11 163 1407 0 2047 EPSG:3857:12 327 2814 0 4095 EPSG:3857:13 655 5629 0 8191 EPSG:3857:14 1311 11259 0 16382 EPSG:3857:15 2623 22518 0 32764 EPSG:3857:16 5247 45036 0 65528 EPSG:3857:17 10494 90072 0 131056 EPSG:3857:18 20989 180145 0 262113 EPSG:3857:19 41978 360291 0 524226 EPSG:3857:20 83957 720582 1 1048453 EPSG:3857:21 167914 1441165 2 2096906 EPSG:3857:22 335828 2882330 5 4193813 EPSG:3857:23 671656 5764660 10 8387626 EPSG:3857:24 1343312 11529320 21 16775252 EPSG:3857:25 2686624 23058641 42 33550505 EPSG:3857:26 5373249 46117282 85 67101010 EPSG:3857:27 10746499 92234565 171 134202020 EPSG:3857:28 21492999 184469131 342 268404041 EPSG:3857:29 42985998 368938262 685 536808083 EPSG:3857:30 85971997 737876524 1371 1073616166 Tropical Cyclone Wind 500 Years Return Period (km/h) The tropical cyclonic strong wind and storm surge hazard model uses information from 2594 historical tropical cyclones besides data on topography, terrain roughness, and bathymetry. The historical tropical cyclones used in the cyclone wind and storm surge hazard model for the GAR Atlas cover the five different oceanic basins: Northeast Pacific, Northwest Pacific, South Pacific, North Indian, South Indian and North Atlantic. In all cases, the data associated to each track were obtained from the IBTrACS database (Knapp et al., 2010). Topography data from the Shuttle Radar Topography Mission (SRTM) of NASA, which provides terrain elevation grids at a 90 meters resolution, delivered by quadrants over the world was used and, additionally, to account for surface roughness, polygons of urban areas worldwide were obtained from the Socioeconomic Data and Applications Centre, SEDAC (CIESIN et al., 2011). A digital bathymetry model, with a spatial resolution of 30 arc-seconds, from the GEBCO_08 (General Bathymetric Chart of the Oceans) Grid Database of the British Oceanographic Data Centre (2009) was used. More information about the cyclone wind and storm surge hazard model can be found in Cardona et al., 2015. Hazard analysis was performed using the software CAPRA Team Tropical Cyclones Hazard Modeler (Bernal, 2014). -180.0 -55.13566066745048 179.9077507461337 59.904585330559826 wesr_risk:cy_hazard_500_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 0 15 EPSG:4326:4 2 12 0 31 EPSG:4326:5 5 25 0 63 EPSG:4326:6 10 51 0 127 EPSG:4326:7 21 103 0 255 EPSG:4326:8 42 206 0 511 EPSG:4326:9 85 412 0 1023 EPSG:4326:10 171 825 0 2047 EPSG:4326:11 342 1651 0 4094 EPSG:4326:12 684 3302 0 8189 EPSG:4326:13 1369 6605 0 16379 EPSG:4326:14 2739 13210 0 32759 EPSG:4326:15 5478 26421 0 65519 EPSG:4326:16 10957 52842 0 131038 EPSG:4326:17 21914 105684 0 262076 EPSG:4326:18 43829 211369 0 524153 EPSG:4326:19 87659 422738 0 1048307 EPSG:4326:20 175318 845476 0 2096614 EPSG:4326:21 350636 1690953 0 4193229 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 Combination Tsunami/Coral reefs at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_cor6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Global estimated risk index for tropical cyclone hazard -180.0 -90.0 179.99999999985602 83.99999999993042 MAPX:wld_cy1010irmt_cl_wgs84 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 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EPSG:900913:24 515056 16777215 0 16777215 EPSG:900913:25 1030113 33554431 0 33554431 EPSG:900913:26 2060227 67108863 0 67108863 EPSG:900913:27 4120454 134217727 0 134217727 EPSG:900913:28 8240909 268435455 0 268435455 EPSG:900913:29 16481819 536870911 0 536870911 EPSG:900913:30 32963639 1073741823 0 1073741823 dust_strong_events_2017_2022_output -17.499999999999943 -1.4999999999999432 75.00000000000006 45.00000000000006 grid_data_core:dust_strong_events_2017_2022_output image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 231 362 EPSG:3857:10 368 516 462 725 EPSG:3857:11 736 1032 924 1450 EPSG:3857:12 1473 2065 1848 2901 EPSG:3857:13 2946 4130 3697 5802 EPSG:3857:14 5893 8260 7395 11605 EPSG:3857:15 11787 16520 14791 23210 EPSG:3857:16 23574 33041 29582 46421 EPSG:3857:17 47149 66082 59164 92842 EPSG:3857:18 94299 132164 118328 185685 EPSG:3857:19 188599 264328 236657 371370 EPSG:3857:20 377199 528657 473315 742741 EPSG:3857:21 754398 1057315 946631 1485482 EPSG:3857:22 1508796 2114630 1893262 2970965 EPSG:3857:23 3017592 4229260 3786524 5941930 EPSG:3857:24 6035184 8458521 7573048 11883861 EPSG:3857:25 12070369 16917042 15146097 23767722 EPSG:3857:26 24140738 33834084 30292195 47535445 EPSG:3857:27 48281477 67668168 60584391 95070890 EPSG:3857:28 96562954 135336336 121168782 190141781 EPSG:3857:29 193125908 270672673 242337564 380283562 EPSG:3857:30 386251817 541345347 484675128 760567125 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 7 11 EPSG:4326:4 3 8 14 22 EPSG:4326:5 7 16 28 45 EPSG:4326:6 15 32 57 90 EPSG:4326:7 31 65 115 181 EPSG:4326:8 63 130 231 362 EPSG:4326:9 127 260 462 725 EPSG:4326:10 255 520 924 1450 EPSG:4326:11 511 1041 1848 2901 EPSG:4326:12 1023 2082 3697 5802 EPSG:4326:13 2047 4164 7395 11605 EPSG:4326:14 4095 8328 14791 23210 EPSG:4326:15 8191 16657 29582 46421 EPSG:4326:16 16383 33314 59164 92842 EPSG:4326:17 32767 66628 118328 185685 EPSG:4326:18 65535 133256 236657 371370 EPSG:4326:19 131071 266513 473315 742741 EPSG:4326:20 262143 533026 946631 1485482 EPSG:4326:21 524287 1066052 1893262 2970965 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 231 362 EPSG:3857:10 368 516 462 725 EPSG:3857:11 736 1032 924 1450 EPSG:3857:12 1473 2065 1848 2901 EPSG:3857:13 2946 4130 3697 5802 EPSG:3857:14 5893 8260 7395 11605 EPSG:3857:15 11787 16520 14791 23210 EPSG:3857:16 23574 33041 29582 46421 EPSG:3857:17 47149 66082 59164 92842 EPSG:3857:18 94299 132164 118328 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text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Aboveground biomass density of vegetation (Mg/ha) This file provides the pan-tropical biomass map published by Avitabile et al. (2016) "An integrated pan-tropical biomass map using multiple reference datasets". The data shows the aboveground biomass in Mg per ha in the tropic region at approximately 1 km resolution. For a proper use and description of this dataset, please refer to the mentioned article. Source: Avitabile, V., Herold, M., Heuvelink, G. B. M., Lewis, S. L., Phillips, O. L., Asner, G. P., Armston, J., Ashton, P. S., Banin, L., Bayol, N., Berry, N. J., Boeckx, P., de Jong, B. H. J., DeVries, B., Girardin, C. A. J., Kearsley, E., Lindsell, J. A., Lopez-Gonzalez, G., Lucas, R., Malhi, Y., Morel, A., Mitchard, E. T. A., Nagy, L., Qie, L., Quinones, M. J., Ryan, C. M., Ferry, S. J. W., Sunderland, T., Laurin, G. V., Gatti, R. C., Valentini, R., Verbeeck, H., Wijaya, A. and Willcock, S. (2016), An integrated pan-tropical biomass map using multiple reference datasets. Glob Change Biol, 22: 1406–1420. doi:10.1111/gcb.13139 -112.85865304959007 -56.259938619115786 154.9996695694099 39.99839086388421 MapX_UNDP:Avitabile_AGB_Map image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 5 1 7 EPSG:3857:4 6 11 2 14 EPSG:3857:5 12 22 5 29 EPSG:3857:6 24 44 11 59 EPSG:3857:7 48 88 23 119 EPSG:3857:8 96 176 47 238 EPSG:3857:9 193 353 95 476 EPSG:3857:10 387 706 190 952 EPSG:3857:11 775 1412 381 1905 EPSG:3857:12 1550 2825 763 3811 EPSG:3857:13 3101 5651 1527 7623 EPSG:3857:14 6202 11303 3055 15246 EPSG:3857:15 12405 22606 6111 30492 EPSG:3857:16 24810 45213 12222 60984 EPSG:3857:17 49621 90426 24445 121969 EPSG:3857:18 99243 180853 48890 243939 EPSG:3857:19 198487 361707 97781 487878 EPSG:3857:20 396975 723414 195563 975757 EPSG:3857:21 793950 1446829 391126 1951514 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2893659 782253 3903029 EPSG:3857:23 3175801 5787319 1564506 7806058 EPSG:3857:24 6351602 11574639 3129013 15612116 EPSG:3857:25 12703204 23149279 6258027 31224232 EPSG:3857:26 25406408 46298558 12516054 62448464 EPSG:3857:27 50812817 92597116 25032108 124896929 EPSG:3857:28 101625635 185194233 50064216 249793858 EPSG:3857:29 203251270 370388466 100128433 499587717 EPSG:3857:30 406502540 740776933 200256867 999175434 sen_natural_hazards_exposure -17.553356309302842 12.295762807806764 -11.281279712807224 16.6921903507492 mapx_chemobs:sen_natural_hazards_exposure image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 28 29 28 29 EPSG:3857:7 57 59 57 59 EPSG:3857:8 115 119 115 119 EPSG:3857:9 231 238 231 239 EPSG:3857:10 463 476 462 479 EPSG:3857:11 927 953 924 959 EPSG:3857:12 1855 1907 1848 1919 EPSG:3857:13 3710 3814 3696 3839 EPSG:3857:14 7421 7628 7393 7678 EPSG:3857:15 14842 15256 14786 15357 EPSG:3857:16 29685 30512 29572 30714 EPSG:3857:17 59370 61024 59145 61428 EPSG:3857:18 118741 122048 118290 122857 EPSG:3857:19 237482 244097 236580 245714 EPSG:3857:20 474965 488195 473160 491428 EPSG:3857:21 949931 976391 946320 982857 EPSG:3857:22 1899862 1952783 1892640 1965715 EPSG:3857:23 3799725 3905567 3785281 3931431 EPSG:3857:24 7599451 7811134 7570562 7862862 EPSG:3857:25 15198903 15622268 15141124 15725724 EPSG:3857:26 30397807 31244537 30282249 31451449 EPSG:3857:27 60795614 62489074 60564498 62902898 EPSG:3857:28 121591229 124978148 121128996 125805796 EPSG:3857:29 243182459 249956296 242257993 251611592 EPSG:3857:30 486364919 499912593 484515987 503223184 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 29 EPSG:4326:6 26 27 57 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29572 30714 EPSG:3857:17 59370 61024 59145 61428 EPSG:3857:18 118741 122048 118290 122857 EPSG:3857:19 237482 244097 236580 245714 EPSG:3857:20 474965 488195 473160 491428 EPSG:3857:21 949931 976391 946320 982857 EPSG:3857:22 1899862 1952783 1892640 1965715 EPSG:3857:23 3799725 3905567 3785281 3931431 EPSG:3857:24 7599451 7811134 7570562 7862862 EPSG:3857:25 15198903 15622268 15141124 15725724 EPSG:3857:26 30397807 31244537 30282249 31451449 EPSG:3857:27 60795614 62489074 60564498 62902898 EPSG:3857:28 121591229 124978148 121128996 125805796 EPSG:3857:29 243182459 249956296 242257993 251611592 EPSG:3857:30 486364919 499912593 484515987 503223184 Self-calibrating Palmer Drought Severity Index (scPDSI) 2018 (CRU) This layer shows the average values for 2018 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_18_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 20190124Classes Classification of a Sentinel-2 image with post-processing using field knowledge. This research was funded by the Copernicus RawMatCop programme, through funding from EIT RawMaterials and the European Commission DG Internal Market, Industry, Entrepreneurship and SMEs (DG GROW). https://eitrawmaterials.eu/eit-rm-academy/rawmatcop/, in the scope of project CopX: "Geospatial mining transparency through Copernicus and MapX" -74.86103149540197 7.565680150087606 -74.77551708391071 7.624603274629289 UNILIEGE:20190124Classes image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125503 125546 76559 76622 EPSG:3857:19 251006 251093 153119 153244 EPSG:3857:20 502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7497 7503 9569 9577 EPSG:4326:15 14995 15006 19139 19155 EPSG:4326:16 29991 30013 38279 38311 EPSG:4326:17 59983 60026 76559 76622 EPSG:4326:18 119967 120053 153119 153244 EPSG:4326:19 239935 240107 306239 306488 EPSG:4326:20 479871 480214 612478 612977 EPSG:4326:21 959742 960429 1224957 1225954 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125503 125546 76559 76622 EPSG:3857:19 251006 251093 153119 153244 EPSG:3857:20 502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 Average annual temperature across 18 models for future climate using SRES A2 Scenario (2041 - 2060) Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:future_Av_annual_temp_Av_18_models_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Average year temperature (1991-2020) Average year temperature in °Celsius across the period 1991-2020. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_20_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tsunami/Coral reefs at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_cor9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average annual temperature for current climate (1970-2000) from WorldClim V2 Average annual temperature from current monthly temperature rasters. <br> WorldClim version 2 has average monthly climate data for minimum, mean, and maximum temperature and for precipitation for 1970-2000. You can download the variables (minimum temperature (°C), maximum temperature (°C), average temperature (°C), precipitation (mm), solar radiation (kJ m-2 day-1), wind speed (m s-1) and water vapor pressure (kPa)) for different spatial resolutions, from 30 seconds (~1 km2) to 10 minutes (~340 km2). Each download is a "zip" file containing 12 GeoTiff (.tif) files, one for each month of the year (January is 1; December is 12). <br> Fick, S.E. and R.J. Hijmans, 2017. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology. -180.0 -90.0 180.0 90.0 LWP:current_wc2_0_2_5m_tavg_annual_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Degraded Areas - PERU National map of degraded areas of Peru. Source: http://geoservidor.minam.gob.pe/informacion-institucional/intercambio-de-datos/ Methodology: http://geoservidor.minam.gob.pe/wp-content/uploads/2017/06/Estudio-Identificaci%C3%B3n-de-%C3%81reas-Degradadas.pdf Wallmap: http://geoservidor.minam.gob.pe/wp-content/uploads/2017/06/Mapa-Nacional-de-Areas-Degradadas.pdf -82.8117704208033 -19.05097182878838 -67.7006922413798 0.5435622953186765 MapX_UNDP_nd:degraded_areas_PER image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 17 8 9 EPSG:3857:6 31 35 17 19 EPSG:3857:7 63 70 34 39 EPSG:3857:8 127 141 69 79 EPSG:3857:9 255 283 138 159 EPSG:3857:10 510 567 276 319 EPSG:3857:11 1020 1134 552 638 EPSG:3857:12 2041 2268 1105 1277 EPSG:3857:13 4083 4537 2211 2555 EPSG:3857:14 8167 9075 4423 5110 EPSG:3857:15 16334 18150 8846 10221 EPSG:3857:16 32669 36301 17692 20443 EPSG:3857:17 65338 72603 35385 40886 EPSG:3857:18 130676 145207 70770 81773 EPSG:3857:19 261352 290414 141540 163547 EPSG:3857:20 522704 580829 283081 327095 EPSG:3857:21 1045409 1161659 566162 654190 EPSG:3857:22 2090818 2323318 1132324 1308381 EPSG:3857:23 4181637 4646637 2264649 2616763 EPSG:3857:24 8363275 9293274 4529299 5233527 EPSG:3857:25 16726551 18586548 9058599 10467054 EPSG:3857:26 33453103 37173097 18117199 20934108 EPSG:3857:27 66906206 74346195 36234398 41868216 EPSG:3857:28 133812412 148692391 72468796 83736433 EPSG:3857:29 267624824 297384782 144937592 167472866 EPSG:3857:30 535249649 594769564 289875185 334945732 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 1 1 1 EPSG:4326:2 1 2 2 2 EPSG:4326:3 3 4 4 4 EPSG:4326:4 7 9 8 9 EPSG:4326:5 15 19 17 19 EPSG:4326:6 31 38 34 39 EPSG:4326:7 63 77 69 79 EPSG:4326:8 127 155 138 159 EPSG:4326:9 254 310 276 319 EPSG:4326:10 508 620 552 638 EPSG:4326:11 1017 1240 1105 1277 EPSG:4326:12 2035 2481 2211 2555 EPSG:4326:13 4071 4963 4423 5110 EPSG:4326:14 8142 9926 8846 10221 EPSG:4326:15 16285 19852 17692 20443 EPSG:4326:16 32570 39704 35385 40886 EPSG:4326:17 65140 79408 70770 81773 EPSG:4326:18 130280 158816 141540 163547 EPSG:4326:19 260560 317633 283081 327095 EPSG:4326:20 521121 635267 566162 654190 EPSG:4326:21 1042243 1270535 1132324 1308381 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 17 8 9 EPSG:3857:6 31 35 17 19 EPSG:3857:7 63 70 34 39 EPSG:3857:8 127 141 69 79 EPSG:3857:9 255 283 138 159 EPSG:3857:10 510 567 276 319 EPSG:3857:11 1020 1134 552 638 EPSG:3857:12 2041 2268 1105 1277 EPSG:3857:13 4083 4537 2211 2555 EPSG:3857:14 8167 9075 4423 5110 EPSG:3857:15 16334 18150 8846 10221 EPSG:3857:16 32669 36301 17692 20443 EPSG:3857:17 65338 72603 35385 40886 EPSG:3857:18 130676 145207 70770 81773 EPSG:3857:19 261352 290414 141540 163547 EPSG:3857:20 522704 580829 283081 327095 EPSG:3857:21 1045409 1161659 566162 654190 EPSG:3857:22 2090818 2323318 1132324 1308381 EPSG:3857:23 4181637 4646637 2264649 2616763 EPSG:3857:24 8363275 9293274 4529299 5233527 EPSG:3857:25 16726551 18586548 9058599 10467054 EPSG:3857:26 33453103 37173097 18117199 20934108 EPSG:3857:27 66906206 74346195 36234398 41868216 EPSG:3857:28 133812412 148692391 72468796 83736433 EPSG:3857:29 267624824 297384782 144937592 167472866 EPSG:3857:30 535249649 594769564 289875185 334945732 Mean temperatures 2017 - Central African Republic Mean observed temperatures in 2017 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2017_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 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image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 15 15 35 36 EPSG:4326:6 30 31 71 72 EPSG:4326:7 61 62 143 144 EPSG:4326:8 123 124 287 288 EPSG:4326:9 246 249 574 577 EPSG:4326:10 492 499 1148 1154 EPSG:4326:11 985 999 2296 2309 EPSG:4326:12 1971 1998 4592 4618 EPSG:4326:13 3943 3997 9184 9237 EPSG:4326:14 7886 7995 18368 18474 EPSG:4326:15 15772 15990 36737 36949 EPSG:4326:16 31544 31980 73474 73899 EPSG:4326:17 63088 63960 146949 147799 EPSG:4326:18 126177 127920 293899 295599 EPSG:4326:19 252355 255841 587798 591199 EPSG:4326:20 504711 511682 1175596 1182399 EPSG:4326:21 1009423 1023364 2351192 2364799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 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EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 Comparison of central Congo Basin peatland maps (2022 and 2017) Metadata for the file: Crezee_2022_Map_comparison.tif This is the file used to create Figure 2 of the paper: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This is a raster file comparing peatland predictions from Crezee et al. (2022) and Dargie et al. (2017). For each study, a binary peat/non-peat map was created, based on a 50% peat probability threshold. In both maps, each pixel was classified as peat if it had >500 hardwood- or palm-dominated peat swamp forests predictions out of 1,000 model runs. A comparison was then made by overlaying the resulting maps. The class values are: 0. Neither study predicted peat swamp forest 1. Only Dargie et al. (2017) predicted peat swamp forest 2. Only Crezee et al. (2022) predicted peat swamp forest 3. Both studies predited peat swamp forest ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 14.99985 -5.000394440000001 25.72774272 3.30574472 peatlands:Crezee_2022_Map_comparison_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257326 269435 283989 299612 EPSG:3857:20 514653 538871 567978 599225 EPSG:3857:21 1029307 1077742 1135956 1198450 EPSG:3857:22 2058615 2155484 2271912 2396901 EPSG:3857:23 4117231 4310969 4543825 4793803 EPSG:3857:24 8234463 8621939 9087651 9587607 EPSG:3857:25 16468927 17243879 18175303 19175215 EPSG:3857:26 32937854 34487758 36350606 38350430 EPSG:3857:27 65875708 68975517 72701213 76700861 EPSG:3857:28 131751417 137951034 145402426 153401723 EPSG:3857:29 263502834 275902069 290804853 306803446 EPSG:3857:30 527005669 551804138 581609707 613606893 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 8 17 18 EPSG:4326:5 15 16 34 36 EPSG:4326:6 30 33 69 73 EPSG:4326:7 61 67 138 146 EPSG:4326:8 123 135 277 292 EPSG:4326:9 246 270 554 585 EPSG:4326:10 493 540 1109 1170 EPSG:4326:11 986 1080 2218 2340 EPSG:4326:12 1972 2161 4437 4681 EPSG:4326:13 3945 4323 8874 9362 EPSG:4326:14 7891 8647 17749 18725 EPSG:4326:15 15782 17294 35498 37451 EPSG:4326:16 31564 34588 70997 74903 EPSG:4326:17 63128 69177 141994 149806 EPSG:4326:18 126257 138354 283989 299612 EPSG:4326:19 252515 276708 567978 599225 EPSG:4326:20 505030 553417 1135956 1198450 EPSG:4326:21 1010061 1106834 2271912 2396901 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257326 269435 283989 299612 EPSG:3857:20 514653 538871 567978 599225 EPSG:3857:21 1029307 1077742 1135956 1198450 EPSG:3857:22 2058615 2155484 2271912 2396901 EPSG:3857:23 4117231 4310969 4543825 4793803 EPSG:3857:24 8234463 8621939 9087651 9587607 EPSG:3857:25 16468927 17243879 18175303 19175215 EPSG:3857:26 32937854 34487758 36350606 38350430 EPSG:3857:27 65875708 68975517 72701213 76700861 EPSG:3857:28 131751417 137951034 145402426 153401723 EPSG:3857:29 263502834 275902069 290804853 306803446 EPSG:3857:30 527005669 551804138 581609707 613606893 Total built-up surface in 198 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_1980 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 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678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 tsm_mambo_bado_20190312 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20190312 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 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8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 sentinel2_sierra_leone_20180208 -12.278532425848166 8.036744648101147 -11.274042950588264 9.036590153051195 MAPX:sentinel2_sierra_leone_20180208 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 14 14 EPSG:3857:6 30 30 29 29 EPSG:3857:7 60 61 59 59 EPSG:3857:8 121 122 119 119 EPSG:3857:9 243 244 238 239 EPSG:3857:10 486 489 477 479 EPSG:3857:11 972 978 954 959 EPSG:3857:12 1944 1956 1908 1919 EPSG:3857:13 3889 3912 3816 3839 EPSG:3857:14 7779 7825 7633 7678 EPSG:3857:15 15558 15650 15266 15357 EPSG:3857:16 31116 31300 30532 30715 EPSG:3857:17 62232 62600 61065 61431 EPSG:3857:18 124464 125200 122131 122862 EPSG:3857:19 248928 250401 244262 245724 EPSG:3857:20 497857 500802 488524 491449 EPSG:3857:21 995714 1001604 977048 982899 EPSG:3857:22 1991428 2003208 1954096 1965799 EPSG:3857:23 3982857 4006417 3908193 3931599 EPSG:3857:24 7965715 8012834 7816386 7863199 EPSG:3857:25 15931430 16025668 15632773 15726399 EPSG:3857:26 31862861 32051337 31265547 31452798 EPSG:3857:27 63725723 64102674 62531095 62905596 EPSG:3857:28 127451447 128205348 125062190 125811192 EPSG:3857:29 254902895 256410697 250124381 251622384 EPSG:3857:30 509805790 512821395 500248762 503244769 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 14 14 EPSG:4326:5 14 14 29 29 EPSG:4326:6 28 29 59 59 EPSG:4326:7 57 58 119 119 EPSG:4326:8 115 116 238 239 EPSG:4326:9 230 233 477 479 EPSG:4326:10 460 466 954 959 EPSG:4326:11 921 932 1908 1919 EPSG:4326:12 1842 1865 3816 3839 EPSG:4326:13 3684 3730 7633 7678 EPSG:4326:14 7369 7460 15266 15357 EPSG:4326:15 14738 14920 30532 30715 EPSG:4326:16 29477 29841 61065 61431 EPSG:4326:17 58955 59683 122131 122862 EPSG:4326:18 117911 119367 244262 245724 EPSG:4326:19 235823 238735 488524 491449 EPSG:4326:20 471646 477470 977048 982899 EPSG:4326:21 943292 954941 1954096 1965799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 14 14 EPSG:3857:6 30 30 29 29 EPSG:3857:7 60 61 59 59 EPSG:3857:8 121 122 119 119 EPSG:3857:9 243 244 238 239 EPSG:3857:10 486 489 477 479 EPSG:3857:11 972 978 954 959 EPSG:3857:12 1944 1956 1908 1919 EPSG:3857:13 3889 3912 3816 3839 EPSG:3857:14 7779 7825 7633 7678 EPSG:3857:15 15558 15650 15266 15357 EPSG:3857:16 31116 31300 30532 30715 EPSG:3857:17 62232 62600 61065 61431 EPSG:3857:18 124464 125200 122131 122862 EPSG:3857:19 248928 250401 244262 245724 EPSG:3857:20 497857 500802 488524 491449 EPSG:3857:21 995714 1001604 977048 982899 EPSG:3857:22 1991428 2003208 1954096 1965799 EPSG:3857:23 3982857 4006417 3908193 3931599 EPSG:3857:24 7965715 8012834 7816386 7863199 EPSG:3857:25 15931430 16025668 15632773 15726399 EPSG:3857:26 31862861 32051337 31265547 31452798 EPSG:3857:27 63725723 64102674 62531095 62905596 EPSG:3857:28 127451447 128205348 125062190 125811192 EPSG:3857:29 254902895 256410697 250124381 251622384 EPSG:3857:30 509805790 512821395 500248762 503244769 Total built-up surface in 1985 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_1985 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Accessibility To Cities 2015 This global accessibility map enumerates land-based travel time to the nearest densely-populated area for all areas between 85 degrees north and 60 degrees south for a nominal year 2015. Densely-populated areas are defined as contiguous areas with 1,500 or more inhabitants per square kilometre or a majority of built-up land cover types coincident with a population centre of at least 50,000 inhabitants. This map was produced through a collaboration between MAP (University of Oxford), Google, the European Union Joint Research Centre (JRC), and the University of Twente, Netherlands.The underlying datasets used to produce the map include roads (comprising the first ever global-scale use of Open Street Map and Google roads datasets), railways, rivers, lakes, oceans, topographic conditions (slope and elevation), landcover types, and national borders. These datasets were each allocated a speed or speeds of travel in terms of time to cross each pixel of that type. The datasets were then combined to produce a "friction surface"; a map where every pixel is allocated a nominal overall speed of travel based on the types occurring within that pixel. Least-cost-path algorithms (running in Google Earth Engine and, for high-latitude areas, in R) were used in conjunction with this friction surface to calculate the time of travel from all locations to the nearest (in time) city. The cities dataset used is the high-density-cover product created by the Global Human Settlement Project. Each pixel in the resultant accessibility map thus represents the modelled shortest time from that location to a city. Authors: D.J. Weiss, A. Nelson, H.S. Gibson, W. Temperley, S. Peedell, A. Lieber, M. Hancher, E. Poyart, S. Belchior, N. Fullman, B. Mappin, U. Dalrymple, J. Rozier, T.C.D. Lucas, R.E. Howes, L.S. Tusting, S.Y. Kang, E. Cameron, D. Bisanzio, K.E. Battle, S. Bhatt, and P.W. Gething. A global map of travel time to cities to assess inequalities in accessibility in 2015. (2018). Nature. doi:10.1038/nature25181 Processing notes: Data were processed from numerous sources including OpenStreetMap, Google Maps, Land Cover mapping, and others, to generate a global friction surface of average land-based travel speed. This accessibility surface was then derived from that friction surface via a least-cost-path algorithm finding at each location the closest point from global databases of population centres and densely-populated areas. Please see the associated publication for full details of the processing. Source: https://map.ox.ac.uk/research-project/accessibility_to_cities/ -180.0 -60.0 179.99985600000002 84.999942 MapX_UNDP:accessibility_to_cities_2015 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 1 726 0 1023 EPSG:3857:11 3 1453 0 2047 EPSG:3857:12 6 2906 0 4095 EPSG:3857:13 13 5813 0 8191 EPSG:3857:14 26 11626 0 16383 EPSG:3857:15 53 23252 0 32767 EPSG:3857:16 107 46504 0 65535 EPSG:3857:17 214 93008 0 131071 EPSG:3857:18 429 186017 0 262143 EPSG:3857:19 859 372034 0 524287 EPSG:3857:20 1719 744069 0 1048575 EPSG:3857:21 3438 1488139 0 2097151 EPSG:3857:22 6877 2976279 0 4194302 EPSG:3857:23 13755 5952559 0 8388604 EPSG:3857:24 27510 11905118 0 16777209 EPSG:3857:25 55021 23810236 0 33554418 EPSG:3857:26 110042 47620473 0 67108837 EPSG:3857:27 220085 95240947 0 134217674 EPSG:3857:28 440170 190481895 0 268435348 EPSG:3857:29 880341 380963791 0 536870697 EPSG:3857:30 1760682 761927583 0 1073741394 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 1 53 0 127 EPSG:4326:7 3 106 0 255 EPSG:4326:8 7 213 0 511 EPSG:4326:9 14 426 0 1023 EPSG:4326:10 28 853 0 2047 EPSG:4326:11 56 1706 0 4095 EPSG:4326:12 113 3413 0 8191 EPSG:4326:13 227 6826 0 16383 EPSG:4326:14 455 13653 0 32767 EPSG:4326:15 910 27306 0 65535 EPSG:4326:16 1820 54613 0 131071 EPSG:4326:17 3640 109226 0 262143 EPSG:4326:18 7281 218453 0 524287 EPSG:4326:19 14563 436906 0 1048575 EPSG:4326:20 29127 873813 0 2097151 EPSG:4326:21 58254 1747626 0 4194302 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 22 0 31 EPSG:900913:6 0 45 0 63 EPSG:900913:7 0 90 0 127 EPSG:900913:8 0 181 0 255 EPSG:900913:9 0 363 0 511 EPSG:900913:10 1 726 0 1023 EPSG:900913:11 3 1453 0 2047 EPSG:900913:12 6 2906 0 4095 EPSG:900913:13 13 5813 0 8191 EPSG:900913:14 26 11626 0 16383 EPSG:900913:15 53 23252 0 32767 EPSG:900913:16 107 46504 0 65535 EPSG:900913:17 214 93008 0 131071 EPSG:900913:18 429 186017 0 262143 EPSG:900913:19 859 372034 0 524287 EPSG:900913:20 1719 744069 0 1048575 EPSG:900913:21 3438 1488139 0 2097151 EPSG:900913:22 6877 2976279 0 4194302 EPSG:900913:23 13755 5952559 0 8388604 EPSG:900913:24 27510 11905118 0 16777209 EPSG:900913:25 55021 23810236 0 33554418 EPSG:900913:26 110042 47620473 0 67108837 EPSG:900913:27 220085 95240947 0 134217674 EPSG:900913:28 440170 190481895 0 268435348 EPSG:900913:29 880341 380963791 0 536870697 EPSG:900913:30 1760682 761927583 0 1073741394 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 1 726 0 1023 EPSG:3857:11 3 1453 0 2047 EPSG:3857:12 6 2906 0 4095 EPSG:3857:13 13 5813 0 8191 EPSG:3857:14 26 11626 0 16383 EPSG:3857:15 53 23252 0 32767 EPSG:3857:16 107 46504 0 65535 EPSG:3857:17 214 93008 0 131071 EPSG:3857:18 429 186017 0 262143 EPSG:3857:19 859 372034 0 524287 EPSG:3857:20 1719 744069 0 1048575 EPSG:3857:21 3438 1488139 0 2097151 EPSG:3857:22 6877 2976279 0 4194302 EPSG:3857:23 13755 5952559 0 8388604 EPSG:3857:24 27510 11905118 0 16777209 EPSG:3857:25 55021 23810236 0 33554418 EPSG:3857:26 110042 47620473 0 67108837 EPSG:3857:27 220085 95240947 0 134217674 EPSG:3857:28 440170 190481895 0 268435348 EPSG:3857:29 880341 380963791 0 536870697 EPSG:3857:30 1760682 761927583 0 1073741394 2001-2010 Average year precipitations change since previous decade (1991-2000) Average year precipitations anomalies in mm across the period 2001-2010 calculated over the average precipitations per year in the period 1991-2000. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_01_10_anom_91_00 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from CCSR/NIES/FRCGC, Japan, MIROC3.2, medium resolution Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_miroc3_2_medres_5km_2041-2060_debiasedmean_tas_av_12m_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Extreme Heat vulnerability recurrence map between 1995 and 2024 Vulnerability to extreme heat was assessed through the degree of urbanization and population density, highlighting socio-spatial inequalities in the face of heat waves. Urbanization, with a rate of 7.16% in 2024, exacerbates the phenomenon, and population density intensifies exposure to health risks. -13.243470490606473 12.296796567458285 -11.336069905109735 13.472353901206636 risk_southeast_senegal:heat_vulnerability image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60585 61024 60714 61408 EPSG:3857:18 121170 122048 121428 122817 EPSG:3857:19 242340 244096 242856 245634 EPSG:3857:20 484680 488192 485713 491269 EPSG:3857:21 969360 976385 971427 982538 EPSG:3857:22 1938720 1952771 1942854 1965077 EPSG:3857:23 3877441 3905542 3885708 3930154 EPSG:3857:24 7754883 7811084 7771417 7860308 EPSG:3857:25 15509767 15622169 15542835 15720617 EPSG:3857:26 31019535 31244339 31085670 31441235 EPSG:3857:27 62039071 62488679 62171340 62882470 EPSG:3857:28 124078142 124977359 124342680 125764941 EPSG:3857:29 248156284 249954718 248685361 251529883 EPSG:3857:30 496312568 499909437 497370722 503059766 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 221 474 479 EPSG:4326:10 435 442 948 959 EPSG:4326:11 870 884 1897 1919 EPSG:4326:12 1741 1768 3794 3838 EPSG:4326:13 3482 3536 7589 7676 EPSG:4326:14 6965 7072 15178 15352 EPSG:4326:15 13931 14145 30357 30704 EPSG:4326:16 27862 28290 60714 61408 EPSG:4326:17 55725 56581 121428 122817 EPSG:4326:18 111451 113163 242856 245634 EPSG:4326:19 222902 226326 485713 491269 EPSG:4326:20 445805 452653 971427 982538 EPSG:4326:21 891611 905307 1942854 1965077 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60585 61024 60714 61408 EPSG:3857:18 121170 122048 121428 122817 EPSG:3857:19 242340 244096 242856 245634 EPSG:3857:20 484680 488192 485713 491269 EPSG:3857:21 969360 976385 971427 982538 EPSG:3857:22 1938720 1952771 1942854 1965077 EPSG:3857:23 3877441 3905542 3885708 3930154 EPSG:3857:24 7754883 7811084 7771417 7860308 EPSG:3857:25 15509767 15622169 15542835 15720617 EPSG:3857:26 31019535 31244339 31085670 31441235 EPSG:3857:27 62039071 62488679 62171340 62882470 EPSG:3857:28 124078142 124977359 124342680 125764941 EPSG:3857:29 248156284 249954718 248685361 251529883 EPSG:3857:30 496312568 499909437 497370722 503059766 Global Human Modification Index 1990 Detailed global datasets for 1990, 2015, and 2017 for land use modification of terrestrial lands (excluding Antarctica) are provided here. These data were calculated using the degree of human modification approach that combines the proportion of a pixel of a given stressor (i.e. footprint) times the intensity of that stressor (ranging from 0 to 1.0). Our novel datasets are detailed (~300m resolution), temporally consistent (for 1990-2015), comprehensive (11 change stressors, 14 current), robust (using an established framework and incorporating classification errors and parameter uncertainty), and strongly validated. A dataset for ~2017 is also provide, that is derived from 14 stressors, for an even more comprehensive dataset, but it should not be used to calculate change with the other datasets (1990-2015). Theobald, D. M., Kennedy, C., Chen, B., Oakleaf, J., Baruch-Mordo, S., and Kiesecker, J.: Earth transformed: detailed mapping of global human modification from 1990 to 2017, Earth Syst. Sci. Data., https://doi.org/10.5194/essd-2019-252, 2020 Source: https://zenodo.org/record/3963013#.X5ChM0JKjUI -180.0 -75.00027807853427 179.99932064640564 85.00013997386212 MapX_UNDP:gHMv1_1990_wgs image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 26 0 31 EPSG:3857:6 0 52 0 63 EPSG:3857:7 0 105 0 127 EPSG:3857:8 0 210 0 255 EPSG:3857:9 0 421 0 511 EPSG:3857:10 1 842 0 1023 EPSG:3857:11 3 1684 0 2047 EPSG:3857:12 6 3369 0 4095 EPSG:3857:13 13 6739 0 8191 EPSG:3857:14 26 13479 0 16383 EPSG:3857:15 53 26958 0 32767 EPSG:3857:16 107 53916 0 65535 EPSG:3857:17 214 107833 0 131071 EPSG:3857:18 428 215666 0 262143 EPSG:3857:19 856 431333 0 524287 EPSG:3857:20 1712 862667 0 1048574 EPSG:3857:21 3425 1725335 0 2097148 EPSG:3857:22 6851 3450670 0 4194296 EPSG:3857:23 13702 6901340 0 8388592 EPSG:3857:24 27404 13802680 0 16777184 EPSG:3857:25 54809 27605360 0 33554368 EPSG:3857:26 109619 55210721 0 67108737 EPSG:3857:27 219238 110421443 0 134217474 EPSG:3857:28 438476 220842886 0 268434949 EPSG:3857:29 876953 441685773 0 536869898 EPSG:3857:30 1753907 883371547 0 1073739797 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 1 58 0 127 EPSG:4326:7 3 117 0 255 EPSG:4326:8 7 234 0 511 EPSG:4326:9 14 469 0 1023 EPSG:4326:10 28 938 0 2047 EPSG:4326:11 56 1877 0 4095 EPSG:4326:12 113 3754 0 8191 EPSG:4326:13 227 7509 0 16383 EPSG:4326:14 455 15018 0 32767 EPSG:4326:15 910 30037 0 65535 EPSG:4326:16 1820 60074 0 131071 EPSG:4326:17 3640 120149 0 262143 EPSG:4326:18 7281 240299 0 524287 EPSG:4326:19 14563 480598 0 1048574 EPSG:4326:20 29126 961196 0 2097148 EPSG:4326:21 58252 1922392 0 4194296 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 26 0 31 EPSG:3857:6 0 52 0 63 EPSG:3857:7 0 105 0 127 EPSG:3857:8 0 210 0 255 EPSG:3857:9 0 421 0 511 EPSG:3857:10 1 842 0 1023 EPSG:3857:11 3 1684 0 2047 EPSG:3857:12 6 3369 0 4095 EPSG:3857:13 13 6739 0 8191 EPSG:3857:14 26 13479 0 16383 EPSG:3857:15 53 26958 0 32767 EPSG:3857:16 107 53916 0 65535 EPSG:3857:17 214 107833 0 131071 EPSG:3857:18 428 215666 0 262143 EPSG:3857:19 856 431333 0 524287 EPSG:3857:20 1712 862667 0 1048574 EPSG:3857:21 3425 1725335 0 2097148 EPSG:3857:22 6851 3450670 0 4194296 EPSG:3857:23 13702 6901340 0 8388592 EPSG:3857:24 27404 13802680 0 16777184 EPSG:3857:25 54809 27605360 0 33554368 EPSG:3857:26 109619 55210721 0 67108737 EPSG:3857:27 219238 110421443 0 134217474 EPSG:3857:28 438476 220842886 0 268434949 EPSG:3857:29 876953 441685773 0 536869898 EPSG:3857:30 1753907 883371547 0 1073739797 Average year precipitations anomalies (2021-2022) over 1991-2020 climatology Average year precipitations anomalies in mm across the period 2021-2022 calculated over the average precipitations per year in the period 1991-2020 (climatology). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_21_22_anom9120 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mean temperatures in 2023 time total precipitations in 2021 - Central African Republic This layer shows the product between the mean temperatures observed in 2023 and the total year precipitations occurred in 2021 per each pixel in the Central African Republic. 14.41796031 2.218838752 27.470481388 11.013345383 cc_and_health:temp_2023_x_precip_2021_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Yearly emissions of N2O - 2000 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -90.0 180.0 90.0 wesr_climat:v60_N2O_2000_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Landslide/Forest at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_lds_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 vulnerability_pesato_02_03 -5.3554163761242854 30.264583696518883 35.977083623875714 45.50708369651888 Medicip:vulnerability_pesato_02_03 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 31 38 EPSG:3857:7 45 52 62 76 EPSG:3857:8 91 105 124 153 EPSG:3857:9 183 210 248 307 EPSG:3857:10 366 421 496 614 EPSG:3857:11 732 843 993 1228 EPSG:3857:12 1465 1686 1987 2457 EPSG:3857:13 2930 3372 3974 4914 EPSG:3857:14 5860 6745 7948 9829 EPSG:3857:15 11721 13491 15896 19658 EPSG:3857:16 23443 26982 31793 39317 EPSG:3857:17 46887 53965 63586 78634 EPSG:3857:18 93775 107931 127172 157269 EPSG:3857:19 187550 215862 254344 314539 EPSG:3857:20 375100 431725 508689 629078 EPSG:3857:21 750201 863450 1017378 1258157 EPSG:3857:22 1500403 1726901 2034756 2516315 EPSG:3857:23 3000807 3453803 4069513 5032630 EPSG:3857:24 6001615 6907606 8139027 10065261 EPSG:3857:25 12003230 13815212 16278055 20130523 EPSG:3857:26 24006460 27630425 32556110 40261046 EPSG:3857:27 48012920 55260850 65112220 80522092 EPSG:3857:28 96025840 110521701 130224440 161044185 EPSG:3857:29 192051680 221043403 260448880 322088371 EPSG:3857:30 384103360 442086806 520897760 644176743 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 15 19 EPSG:4326:5 7 10 31 38 EPSG:4326:6 15 21 62 76 EPSG:4326:7 31 42 124 153 EPSG:4326:8 63 84 248 307 EPSG:4326:9 126 169 496 614 EPSG:4326:10 253 339 993 1228 EPSG:4326:11 506 679 1987 2457 EPSG:4326:12 1012 1359 3974 4914 EPSG:4326:13 2024 2718 7948 9829 EPSG:4326:14 4049 5437 15896 19658 EPSG:4326:15 8099 10874 31793 39317 EPSG:4326:16 16199 21749 63586 78634 EPSG:4326:17 32398 43498 127172 157269 EPSG:4326:18 64797 86996 254344 314539 EPSG:4326:19 129595 173992 508689 629078 EPSG:4326:20 259190 347984 1017378 1258157 EPSG:4326:21 518380 695968 2034756 2516315 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 31 38 EPSG:3857:7 45 52 62 76 EPSG:3857:8 91 105 124 153 EPSG:3857:9 183 210 248 307 EPSG:3857:10 366 421 496 614 EPSG:3857:11 732 843 993 1228 EPSG:3857:12 1465 1686 1987 2457 EPSG:3857:13 2930 3372 3974 4914 EPSG:3857:14 5860 6745 7948 9829 EPSG:3857:15 11721 13491 15896 19658 EPSG:3857:16 23443 26982 31793 39317 EPSG:3857:17 46887 53965 63586 78634 EPSG:3857:18 93775 107931 127172 157269 EPSG:3857:19 187550 215862 254344 314539 EPSG:3857:20 375100 431725 508689 629078 EPSG:3857:21 750201 863450 1017378 1258157 EPSG:3857:22 1500403 1726901 2034756 2516315 EPSG:3857:23 3000807 3453803 4069513 5032630 EPSG:3857:24 6001615 6907606 8139027 10065261 EPSG:3857:25 12003230 13815212 16278055 20130523 EPSG:3857:26 24006460 27630425 32556110 40261046 EPSG:3857:27 48012920 55260850 65112220 80522092 EPSG:3857:28 96025840 110521701 130224440 161044185 EPSG:3857:29 192051680 221043403 260448880 322088371 EPSG:3857:30 384103360 442086806 520897760 644176743 Self-calibrating Palmer Drought Severity Index (scPDSI) 2001-2010 (CRU) This layer shows the average values over the 2001 to 2010 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_01_10_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Total built-up surface in 1990 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_1990 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Sea grasses total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:seagrakm2a image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Total built-up surface in 1995 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_1995 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 v432_CH4_2012_opt_deflate -180.0 -77.95 179.95 88.15000000000002 wesr_climat:v432_CH4_2012_opt_deflate image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 0 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 -1 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 0 115142440 0 134199086 EPSG:3857:28 -1 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 0 921139526 0 1073592693 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 -1 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 0 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 -1 115142440 0 134199086 EPSG:3857:28 0 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 -1 921139526 0 1073592693 World Urban Areas - Natural Earth -159.671325683594 -44.1649017333984 179.713973999023 70.3367004394531 grid_data_core:ne_10m_urban_areas image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 2 0 7 EPSG:4326:3 0 5 0 15 EPSG:4326:4 1 11 1 31 EPSG:4326:5 3 23 3 63 EPSG:4326:6 6 47 7 127 EPSG:4326:7 13 95 14 255 EPSG:4326:8 27 190 28 511 EPSG:4326:9 55 381 57 1023 EPSG:4326:10 111 763 115 2046 EPSG:4326:11 223 1526 231 4092 EPSG:4326:12 447 3052 462 8185 EPSG:4326:13 894 6105 925 16370 EPSG:4326:14 1789 12211 1850 32741 EPSG:4326:15 3579 24423 3700 65483 EPSG:4326:16 7159 48847 7401 130967 EPSG:4326:17 14318 97695 14802 261935 EPSG:4326:18 28636 195391 29605 523871 EPSG:4326:19 57273 390783 59211 1047742 EPSG:4326:20 114547 781567 118423 2095485 EPSG:4326:21 229094 1563134 236846 4190971 EPSG:900913 2020-03_albedo -180.0 -59.995535714 179.995535715 80.004464286 wesr_mountains:2020-03_albedo image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 3 53 0 127 EPSG:4326:7 7 106 0 255 EPSG:4326:8 14 213 0 511 EPSG:4326:9 28 426 0 1023 EPSG:4326:10 56 853 0 2047 EPSG:4326:11 113 1706 0 4095 EPSG:4326:12 227 3413 0 8191 EPSG:4326:13 454 6826 0 16383 EPSG:4326:14 909 13652 0 32767 EPSG:4326:15 1819 27305 0 65535 EPSG:4326:16 3639 54611 0 131070 EPSG:4326:17 7278 109223 0 262140 EPSG:4326:18 14557 218446 0 524281 EPSG:4326:19 29114 436893 0 1048562 EPSG:4326:20 58228 873787 0 2097125 EPSG:4326:21 116456 1747574 0 4194251 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 Global urban extent - MODIS 500m -180.0 -90.0 180.0 90.0 grid_data_core_pro:u4_modis500 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:900913 Phospate (autumn) - WOA13 World Ocean Atlas 2013 (WOA13) is a long-term set of objectively analyzed climatologies of temperature, salinity, oxygen, phosphate, silicate, and nitrate for annual, seasonal, and monthly periods for the World Ocean. Data (at surface) are expressed in µmol/l -180.0 -78.0 180.0 90.0 unea_pollution:ph_aut image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 0 119 0 255 EPSG:4326:8 0 238 0 511 EPSG:4326:9 0 477 0 1023 EPSG:4326:10 0 955 0 2047 EPSG:4326:11 0 1911 0 4095 EPSG:4326:12 0 3822 0 8191 EPSG:4326:13 0 7645 0 16383 EPSG:4326:14 0 15291 0 32767 EPSG:4326:15 0 30583 0 65535 EPSG:4326:16 0 61166 0 131071 EPSG:4326:17 0 122333 0 262143 EPSG:4326:18 0 244667 0 524287 EPSG:4326:19 0 489335 0 1048575 EPSG:4326:20 0 978670 0 2097151 EPSG:4326:21 0 1957341 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 13 0 15 EPSG:900913:5 0 27 0 31 EPSG:900913:6 0 54 0 63 EPSG:900913:7 0 109 0 127 EPSG:900913:8 0 219 0 255 EPSG:900913:9 0 439 0 511 EPSG:900913:10 0 879 0 1023 EPSG:900913:11 0 1758 0 2047 EPSG:900913:12 0 3516 0 4095 EPSG:900913:13 0 7033 0 8191 EPSG:900913:14 0 14066 0 16383 EPSG:900913:15 0 28132 0 32767 EPSG:900913:16 0 56265 0 65535 EPSG:900913:17 0 112531 0 131071 EPSG:900913:18 0 225062 0 262143 EPSG:900913:19 0 450124 0 524287 EPSG:900913:20 0 900249 0 1048575 EPSG:900913:21 0 1800498 0 2097151 EPSG:900913:22 0 3600997 0 4194303 EPSG:900913:23 0 7201994 0 8388607 EPSG:900913:24 0 14403989 0 16777215 EPSG:900913:25 0 28807979 0 33554431 EPSG:900913:26 0 57615958 0 67108863 EPSG:900913:27 0 115231917 0 134217727 EPSG:900913:28 0 230463834 0 268435455 EPSG:900913:29 0 460927668 0 536870911 EPSG:900913:30 0 921855337 0 1073741823 Global High Resolution Estimates of the Human Development Index, Version 2.0 These are the predictions generated from the machine learning model combining MOSAIKS daytime image and nightlight (NL) features These predictions are clipped to have values that fall within 0 and 1. These estimates are centered such that the population-weighted average of the 0.01 x 0.01 degree tile HDI estimates matches the ADM1 data from Smits and Permanyer (https://globaldatalab.org/shdi). Population weights come from the Global Human Settlement Data (GHS-POP) (https://ghsl.jrc.ec.europa.eu/download.php?ds=pop). Note that we only release estimates where human settlements are known to exist. -180.0 -56.0 180.0 74.0 unccd:hdi_predictions image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 3 11 0 15 EPSG:3857:5 6 22 0 31 EPSG:3857:6 12 44 0 63 EPSG:3857:7 24 88 0 127 EPSG:3857:8 48 176 0 255 EPSG:3857:9 96 352 0 511 EPSG:3857:10 192 705 0 1023 EPSG:3857:11 384 1410 0 2047 EPSG:3857:12 768 2820 0 4095 EPSG:3857:13 1537 5641 0 8191 EPSG:3857:14 3075 11282 0 16383 EPSG:3857:15 6150 22564 0 32767 EPSG:3857:16 12300 45128 0 65535 EPSG:3857:17 24601 90257 0 131071 EPSG:3857:18 49203 180514 0 262143 EPSG:3857:19 98407 361028 0 524287 EPSG:3857:20 196814 722056 0 1048575 EPSG:3857:21 393629 1444112 0 2097151 EPSG:3857:22 787258 2888225 0 4194304 EPSG:3857:23 1574517 5776451 0 8388608 EPSG:3857:24 3149034 11552902 0 16777215 EPSG:3857:25 6298068 23105805 0 33554431 EPSG:3857:26 12596137 46211611 0 67108863 EPSG:3857:27 25192274 92423223 0 134217727 EPSG:3857:28 50384548 184846446 0 268435456 EPSG:3857:29 100769096 369692893 0 536870911 EPSG:3857:30 201538192 739385787 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 0 31 EPSG:4326:5 2 25 0 63 EPSG:4326:6 5 51 0 127 EPSG:4326:7 11 103 0 255 EPSG:4326:8 22 207 0 511 EPSG:4326:9 45 415 0 1023 EPSG:4326:10 91 830 0 2047 EPSG:4326:11 182 1661 0 4095 EPSG:4326:12 364 3322 0 8191 EPSG:4326:13 728 6644 0 16383 EPSG:4326:14 1456 13289 0 32767 EPSG:4326:15 2912 26578 0 65535 EPSG:4326:16 5825 53156 0 131071 EPSG:4326:17 11650 106313 0 262143 EPSG:4326:18 23301 212627 0 524287 EPSG:4326:19 46603 425255 0 1048575 EPSG:4326:20 93206 850511 0 2097151 EPSG:4326:21 186413 1701023 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 3 11 0 15 EPSG:3857:5 6 22 0 31 EPSG:3857:6 12 44 0 63 EPSG:3857:7 24 88 0 127 EPSG:3857:8 48 176 0 255 EPSG:3857:9 96 352 0 511 EPSG:3857:10 192 705 0 1023 EPSG:3857:11 384 1410 0 2047 EPSG:3857:12 768 2820 0 4095 EPSG:3857:13 1537 5641 0 8191 EPSG:3857:14 3075 11282 0 16383 EPSG:3857:15 6150 22564 0 32767 EPSG:3857:16 12300 45128 0 65535 EPSG:3857:17 24601 90257 0 131071 EPSG:3857:18 49203 180514 0 262143 EPSG:3857:19 98407 361028 0 524287 EPSG:3857:20 196814 722056 0 1048575 EPSG:3857:21 393629 1444112 0 2097152 EPSG:3857:22 787258 2888225 0 4194304 EPSG:3857:23 1574517 5776451 0 8388607 EPSG:3857:24 3149034 11552902 0 16777215 EPSG:3857:25 6298068 23105805 0 33554431 EPSG:3857:26 12596137 46211611 0 67108863 EPSG:3857:27 25192274 92423223 0 134217728 EPSG:3857:28 50384548 184846446 0 268435455 EPSG:3857:29 100769096 369692893 0 536870911 EPSG:3857:30 201538192 739385787 0 1073741824 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from Bjerknes Centre for Climate Research, Norway, BCM2.0 Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_bccr_bcm2_0_5km_2041-2060_debiasedmean_tas_av_12month_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Yearly emissions of CO2 (excluding short cycle organic Carbon) - 2018 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -85.19999999999004 179.99999999997954 90.0 wesr_climat:v60_CO2_excl_short-cycle_org_C_2018_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 62 0 127 EPSG:4326:7 0 124 0 255 EPSG:4326:8 0 249 0 511 EPSG:4326:9 0 498 0 1023 EPSG:4326:10 0 996 0 2047 EPSG:4326:11 0 1993 0 4095 EPSG:4326:12 0 3986 0 8191 EPSG:4326:13 0 7973 0 16383 EPSG:4326:14 0 15947 0 32767 EPSG:4326:15 0 31894 0 65535 EPSG:4326:16 0 63788 0 131071 EPSG:4326:17 0 127576 0 262143 EPSG:4326:18 0 255153 0 524287 EPSG:4326:19 0 510306 0 1048575 EPSG:4326:20 0 1020613 0 2097151 EPSG:4326:21 0 2041227 0 4194303 EPSG:900913 EPSG:3857_512 wesr_climate_sta_nov -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_sta_nov image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_col_zaragoza_20210712 -74.8651063820499 7.579889039548307 -74.7899249680916 7.640072688469066 rs_for_asgm:tsm_col_zaragoza_20210712 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7496 7502 9569 9576 EPSG:4326:15 14993 15004 19139 19152 EPSG:4326:16 29986 30008 38278 38305 EPSG:4326:17 59972 60016 76556 76611 EPSG:4326:18 119945 120032 153113 153223 EPSG:4326:19 239890 240065 306227 306446 EPSG:4326:20 479781 480131 612455 612893 EPSG:4326:21 959562 960263 1224910 1225786 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 Automn temperature change (°C) for the period 2020 - 2039 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_son_NEARREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Bhutan - Carbon Sequestration (upper) 2010 Carbon sequestration map for Bhutan simulated for 2010 following a Business As Usual (BAU) scenario using a potential carbon sequestration value of 394.74 ton/ha for forests including carbon in biomass and soil. 88.73352726023123 26.684993773827255 92.1470305182156 28.248035723321824 TEEB:BHU_carbonSeq_upper_2010 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 3 EPSG:3857:3 3 3 5 6 EPSG:3857:4 6 6 11 12 EPSG:3857:5 13 13 23 24 EPSG:3857:6 26 27 47 48 EPSG:3857:7 53 54 95 96 EPSG:3857:8 107 108 191 193 EPSG:3857:9 214 216 382 387 EPSG:3857:10 428 433 764 774 EPSG:3857:11 856 866 1528 1548 EPSG:3857:12 1712 1732 3057 3096 EPSG:3857:13 3425 3465 6115 6192 EPSG:3857:14 6850 6931 12230 12385 EPSG:3857:15 13701 13862 24460 24771 EPSG:3857:16 27403 27724 48921 49542 EPSG:3857:17 54807 55448 97842 99085 EPSG:3857:18 109614 110897 195685 198171 EPSG:3857:19 219229 221794 391371 396342 EPSG:3857:20 438458 443589 782743 792685 EPSG:3857:21 876916 887179 1565486 1585371 EPSG:3857:22 1753833 1774358 3130972 3170742 EPSG:3857:23 3507666 3548717 6261945 6341485 EPSG:3857:24 7015333 7097434 12523890 12682970 EPSG:3857:25 14030667 14194869 25047780 25365941 EPSG:3857:26 28061334 28389738 50095560 50731883 EPSG:3857:27 56122669 56779476 100191120 101463766 EPSG:3857:28 112245338 113558952 200382241 202927533 EPSG:3857:29 224490676 227117905 400764482 405855067 EPSG:3857:30 448981353 454235810 801528965 811710135 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 3 EPSG:4326:2 1 1 5 6 EPSG:4326:3 2 2 11 12 EPSG:4326:4 5 5 23 24 EPSG:4326:5 10 11 47 48 EPSG:4326:6 21 22 95 96 EPSG:4326:7 43 45 191 193 EPSG:4326:8 87 90 382 387 EPSG:4326:9 175 180 764 774 EPSG:4326:10 351 360 1528 1548 EPSG:4326:11 702 720 3057 3096 EPSG:4326:12 1405 1440 6115 6192 EPSG:4326:13 2810 2881 12230 12385 EPSG:4326:14 5620 5763 24460 24771 EPSG:4326:15 11241 11526 48921 49542 EPSG:4326:16 22483 23052 97842 99085 EPSG:4326:17 44966 46104 195685 198171 EPSG:4326:18 89932 92209 391371 396342 EPSG:4326:19 179865 184418 782743 792685 EPSG:4326:20 359731 368836 1565486 1585371 EPSG:4326:21 719462 737673 3130972 3170742 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 3 EPSG:3857:3 3 3 5 6 EPSG:3857:4 6 6 11 12 EPSG:3857:5 13 13 23 24 EPSG:3857:6 26 27 47 48 EPSG:3857:7 53 54 95 96 EPSG:3857:8 107 108 191 193 EPSG:3857:9 214 216 382 387 EPSG:3857:10 428 433 764 774 EPSG:3857:11 856 866 1528 1548 EPSG:3857:12 1712 1732 3057 3096 EPSG:3857:13 3425 3465 6115 6192 EPSG:3857:14 6850 6931 12230 12385 EPSG:3857:15 13701 13862 24460 24771 EPSG:3857:16 27403 27724 48921 49542 EPSG:3857:17 54807 55448 97842 99085 EPSG:3857:18 109614 110897 195685 198171 EPSG:3857:19 219229 221794 391371 396342 EPSG:3857:20 438458 443589 782743 792685 EPSG:3857:21 876916 887179 1565486 1585371 EPSG:3857:22 1753833 1774358 3130972 3170742 EPSG:3857:23 3507666 3548717 6261945 6341485 EPSG:3857:24 7015333 7097434 12523890 12682970 EPSG:3857:25 14030667 14194869 25047780 25365941 EPSG:3857:26 28061334 28389738 50095560 50731883 EPSG:3857:27 56122669 56779476 100191120 101463766 EPSG:3857:28 112245338 113558952 200382241 202927533 EPSG:3857:29 224490676 227117905 400764482 405855067 EPSG:3857:30 448981353 454235810 801528965 811710135 Landslide hazard frequency 60.879999999999995 23.709999999999994 75.38 36.9 UNDAC-PAK:ls_freq2af_P3_pak_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 10 11 EPSG:3857:5 12 13 21 22 EPSG:3857:6 24 27 42 45 EPSG:3857:7 49 55 85 90 EPSG:3857:8 99 110 171 181 EPSG:3857:9 199 221 342 363 EPSG:3857:10 398 442 685 726 EPSG:3857:11 797 885 1370 1452 EPSG:3857:12 1595 1770 2740 2905 EPSG:3857:13 3191 3540 5481 5811 EPSG:3857:14 6382 7080 10962 11622 EPSG:3857:15 12765 14161 21925 23245 EPSG:3857:16 25531 28322 43850 46490 EPSG:3857:17 51062 56645 87701 92981 EPSG:3857:18 102125 113291 175403 185962 EPSG:3857:19 204250 226583 350806 371924 EPSG:3857:20 408501 453167 701613 743848 EPSG:3857:21 817003 906335 1403227 1487696 EPSG:3857:22 1634007 1812671 2806455 2975392 EPSG:3857:23 3268014 3625342 5612910 5950785 EPSG:3857:24 6536028 7250684 11225821 11901570 EPSG:3857:25 13072057 14501368 22451643 23803141 EPSG:3857:26 26144114 29002736 44903286 47606282 EPSG:3857:27 52288228 58005473 89806573 95212564 EPSG:3857:28 104576456 116010946 179613146 190425129 EPSG:3857:29 209152912 232021892 359226292 380850259 EPSG:3857:30 418305824 464043784 718452584 761700519 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 2 2 10 11 EPSG:4326:4 4 5 21 22 EPSG:4326:5 9 11 42 45 EPSG:4326:6 18 23 85 90 EPSG:4326:7 37 47 171 181 EPSG:4326:8 75 94 342 363 EPSG:4326:9 151 188 685 726 EPSG:4326:10 302 377 1370 1452 EPSG:4326:11 604 754 2740 2905 EPSG:4326:12 1208 1508 5481 5811 EPSG:4326:13 2416 3016 10962 11622 EPSG:4326:14 4833 6033 21925 23245 EPSG:4326:15 9666 12067 43850 46490 EPSG:4326:16 19333 24135 87701 92981 EPSG:4326:17 38666 48270 175403 185962 EPSG:4326:18 77332 96541 350806 371924 EPSG:4326:19 154664 193083 701613 743848 EPSG:4326:20 309329 386167 1403227 1487696 EPSG:4326:21 618659 772334 2806455 2975392 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 10 11 EPSG:3857:5 12 13 21 22 EPSG:3857:6 24 27 42 45 EPSG:3857:7 49 55 85 90 EPSG:3857:8 99 110 171 181 EPSG:3857:9 199 221 342 363 EPSG:3857:10 398 442 685 726 EPSG:3857:11 797 885 1370 1452 EPSG:3857:12 1595 1770 2740 2905 EPSG:3857:13 3191 3540 5481 5811 EPSG:3857:14 6382 7080 10962 11622 EPSG:3857:15 12765 14161 21925 23245 EPSG:3857:16 25531 28322 43850 46490 EPSG:3857:17 51062 56645 87701 92981 EPSG:3857:18 102125 113291 175403 185962 EPSG:3857:19 204250 226583 350806 371924 EPSG:3857:20 408501 453167 701613 743848 EPSG:3857:21 817003 906335 1403227 1487696 EPSG:3857:22 1634007 1812671 2806455 2975392 EPSG:3857:23 3268014 3625342 5612910 5950785 EPSG:3857:24 6536028 7250684 11225821 11901570 EPSG:3857:25 13072057 14501368 22451643 23803141 EPSG:3857:26 26144114 29002736 44903286 47606282 EPSG:3857:27 52288228 58005473 89806573 95212564 EPSG:3857:28 104576456 116010946 179613146 190425129 EPSG:3857:29 209152912 232021892 359226292 380850259 EPSG:3857:30 418305824 464043784 718452584 761700519 Combination Tropical cyclone surge/ Sea grasses at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_sea9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 hwsd_texture -180.0 -88.999999992912 179.99999998559997 88.999999999968 mapx_chemobs:hwsd_texture image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 1 254 0 511 EPSG:4326:9 2 509 0 1023 EPSG:4326:10 5 1018 0 2047 EPSG:4326:11 11 2036 0 4095 EPSG:4326:12 22 4073 0 8191 EPSG:4326:13 45 8146 0 16383 EPSG:4326:14 91 16292 0 32767 EPSG:4326:15 182 32585 0 65535 EPSG:4326:16 364 65171 0 131071 EPSG:4326:17 728 130343 0 262143 EPSG:4326:18 1456 260687 0 524287 EPSG:4326:19 2912 521375 0 1048575 EPSG:4326:20 5825 1042750 0 2097151 EPSG:4326:21 11650 2085501 0 4194303 EPSG:900913 EPSG:3857_512 tsm_mambo_bado_20200624 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20200624 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 Yearly emissions of CO2 (excluding short cycle organic Carbon) - 1990 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -88.79999999998984 179.99999999997954 90.0 wesr_climat:v60_CO2_excl_short-cycle_org_C_1990_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 254 0 511 EPSG:4326:9 0 508 0 1023 EPSG:4326:10 0 1017 0 2047 EPSG:4326:11 0 2034 0 4095 EPSG:4326:12 0 4068 0 8191 EPSG:4326:13 0 8137 0 16383 EPSG:4326:14 0 16274 0 32767 EPSG:4326:15 0 32549 0 65535 EPSG:4326:16 0 65099 0 131071 EPSG:4326:17 0 130198 0 262143 EPSG:4326:18 0 260396 0 524287 EPSG:4326:19 0 520792 0 1048575 EPSG:4326:20 0 1041585 0 2097151 EPSG:4326:21 0 2083170 0 4194303 EPSG:900913 EPSG:3857_512 frac_cats_2017_kamituga_west 28.166978184291047 -3.075687270143314 28.181206954060514 -3.0642747063483102 rs_for_asgm:frac_cats_2017_kamituga_west image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 520 592 592 EPSG:3857:11 1041 1041 1184 1184 EPSG:3857:12 2082 2083 2368 2368 EPSG:3857:13 4165 4166 4736 4737 EPSG:3857:14 8331 8332 9473 9474 EPSG:3857:15 16663 16664 18947 18949 EPSG:3857:16 33326 33328 37895 37898 EPSG:3857:17 66652 66656 75791 75796 EPSG:3857:18 133304 133312 151582 151592 EPSG:3857:19 266608 266625 303165 303185 EPSG:3857:20 533217 533250 606330 606371 EPSG:3857:21 1066435 1066501 1212660 1212743 EPSG:3857:22 2132870 2133003 2425321 2425486 EPSG:3857:23 4265740 4266007 4850642 4850973 EPSG:3857:24 8531481 8532014 9701284 9701947 EPSG:3857:25 17062963 17064028 19402568 19403894 EPSG:3857:26 34125926 34128057 38805137 38807789 EPSG:3857:27 68251853 68256114 77610274 77615579 EPSG:3857:28 136503706 136512228 155220549 155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 264 592 592 EPSG:4326:10 529 529 1184 1184 EPSG:4326:11 1058 1058 2368 2368 EPSG:4326:12 2117 2117 4736 4737 EPSG:4326:13 4235 4235 9473 9474 EPSG:4326:14 8470 8471 18947 18949 EPSG:4326:15 16941 16943 37895 37898 EPSG:4326:16 33883 33887 75791 75796 EPSG:4326:17 67767 67775 151582 151592 EPSG:4326:18 135534 135551 303165 303185 EPSG:4326:19 271069 271102 606330 606371 EPSG:4326:20 542138 542205 1212660 1212743 EPSG:4326:21 1084277 1084410 2425321 2425486 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 520 592 592 EPSG:3857:11 1041 1041 1184 1184 EPSG:3857:12 2082 2083 2368 2368 EPSG:3857:13 4165 4166 4736 4737 EPSG:3857:14 8331 8332 9473 9474 EPSG:3857:15 16663 16664 18947 18949 EPSG:3857:16 33326 33328 37895 37898 EPSG:3857:17 66652 66656 75791 75796 EPSG:3857:18 133304 133312 151582 151592 EPSG:3857:19 266608 266625 303165 303185 EPSG:3857:20 533217 533250 606330 606371 EPSG:3857:21 1066435 1066501 1212660 1212743 EPSG:3857:22 2132870 2133003 2425321 2425486 EPSG:3857:23 4265740 4266007 4850642 4850973 EPSG:3857:24 8531481 8532014 9701284 9701947 EPSG:3857:25 17062963 17064028 19402568 19403894 EPSG:3857:26 34125926 34128057 38805137 38807789 EPSG:3857:27 68251853 68256114 77610274 77615579 EPSG:3857:28 136503706 136512228 155220549 155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 Year precipitations 2001 - Central African Republic Total precipitations observed in 2001 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2001_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Winter temperature change (°C) for the period 2080 - 2099 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_djf_ENDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 2021-2022 Average year precipitations change since previous decade (2011-2020) Average year precipitations anomalies in mm across the period 2021-2022 calculated over the average precipitations per year in the period 2011-2020. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_21_22_anom_11_20 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 frac_cats_2018_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_2018_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Kerala Flood 500 Years RP - Historical Kerala State flood hazard map - Historical. Maximum expected flood event water height in a 500 years return period, expressed in cm. 74.85875 8.25375 77.49291666666667 12.842916666666673 ECO-DRR:Kerala_Flood_500_Yrs_Historical image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185582 187500 EPSG:4326:18 112368 119051 371164 375001 EPSG:4326:19 224736 238103 742329 750002 EPSG:4326:20 449472 476206 1484659 1500004 EPSG:4326:21 898945 952412 2969319 3000009 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 Forest Height (Montana State University) The forest structural condition index is derived from the University of Maryland canopy cover, canopy height, and time since forest loss data sets. The index spans from short, open-canopy, recently disturbed forests to tall, closed canopy forests that have not been disturbed with the last 14 years. Forest stature and canopy cover are products of both the biophysical potential of a local site and of disturbance history. The tallest, most dense forests are found in settings with favorable climate and soils but with low levels if natural or human disturbance. Such forests have been shown to support high levels of biodiversity, store high levels of carbon, and be more resilient to climate variability. Our maps of forest structural condition are the first to identify locations in the humid tropics of tall, dense forests resulting from high biophysical potential and low disturbance rates. Data are provided by the Montana State University for South America, Africa and Asia separately, and have been merged into a single dataset here. License information: CC-4.0 Attribution. -117.0005 -32.0005 180.0 32.0005 MapX_UNDP:forest_height image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 12 19 5 31 EPSG:3857:6 25 38 11 63 EPSG:3857:7 51 76 22 127 EPSG:3857:8 103 152 44 255 EPSG:3857:9 207 304 89 511 EPSG:3857:10 415 608 179 1023 EPSG:3857:11 831 1216 358 2047 EPSG:3857:12 1663 2432 716 4095 EPSG:3857:13 3326 4865 1433 8191 EPSG:3857:14 6653 9730 2867 16383 EPSG:3857:15 13306 19461 5734 32767 EPSG:3857:16 26613 38922 11468 65535 EPSG:3857:17 53227 77844 22937 131071 EPSG:3857:18 106454 155689 45874 262143 EPSG:3857:19 212909 311378 91749 524287 EPSG:3857:20 425818 622757 183499 1048575 EPSG:3857:21 851636 1245515 366998 2097151 EPSG:3857:22 1703272 2491031 733997 4194304 EPSG:3857:23 3406544 4982063 1467994 8388608 EPSG:3857:24 6813088 9964127 2935989 16777215 EPSG:3857:25 13626176 19928255 5871978 33554431 EPSG:3857:26 27252353 39856510 11743957 67108863 EPSG:3857:27 54504706 79713021 23487915 134217727 EPSG:3857:28 109009413 159426042 46975831 268435456 EPSG:3857:29 218018827 318852084 93951663 536870911 EPSG:3857:30 436037654 637704169 187903327 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 1 2 1 7 EPSG:4326:3 2 5 2 15 EPSG:4326:4 5 10 5 31 EPSG:4326:5 10 21 11 63 EPSG:4326:6 20 43 22 127 EPSG:4326:7 41 86 44 255 EPSG:4326:8 82 173 89 511 EPSG:4326:9 164 347 179 1023 EPSG:4326:10 329 694 358 2047 EPSG:4326:11 659 1388 716 4095 EPSG:4326:12 1319 2776 1433 8191 EPSG:4326:13 2639 5552 2867 16383 EPSG:4326:14 5279 11104 5734 32767 EPSG:4326:15 10558 22209 11468 65535 EPSG:4326:16 21116 44419 22937 131071 EPSG:4326:17 42233 88838 45874 262143 EPSG:4326:18 84467 177676 91749 524287 EPSG:4326:19 168935 355352 183499 1048575 EPSG:4326:20 337871 710704 366998 2097151 EPSG:4326:21 675743 1421408 733997 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 12 19 5 31 EPSG:3857:6 25 38 11 63 EPSG:3857:7 51 76 22 127 EPSG:3857:8 103 152 44 255 EPSG:3857:9 207 304 89 511 EPSG:3857:10 415 608 179 1023 EPSG:3857:11 831 1216 358 2047 EPSG:3857:12 1663 2432 716 4095 EPSG:3857:13 3326 4865 1433 8191 EPSG:3857:14 6653 9730 2867 16383 EPSG:3857:15 13306 19461 5734 32767 EPSG:3857:16 26613 38922 11468 65535 EPSG:3857:17 53227 77844 22937 131071 EPSG:3857:18 106454 155689 45874 262143 EPSG:3857:19 212909 311378 91749 524287 EPSG:3857:20 425818 622757 183499 1048575 EPSG:3857:21 851636 1245515 366998 2097152 EPSG:3857:22 1703272 2491031 733997 4194304 EPSG:3857:23 3406544 4982063 1467994 8388607 EPSG:3857:24 6813088 9964127 2935989 16777215 EPSG:3857:25 13626176 19928255 5871978 33554431 EPSG:3857:26 27252353 39856510 11743957 67108863 EPSG:3857:27 54504706 79713021 23487915 134217728 EPSG:3857:28 109009413 159426042 46975831 268435455 EPSG:3857:29 218018827 318852084 93951663 536870911 EPSG:3857:30 436037654 637704169 187903327 1073741824 Soil Loss (RUSLE - v1.1) - 2012 - GloSEM_25km - ESDAC - JRC Assessment of global soil erosion for 2012 based on Global Soil Erosion Modelling platform (GloSEM). We used the 250m original data to re-sample at 25km. In this study 202 countries are included with more than 125 millionKm2. The total soil loss has been estimated to 35 Pg yr-1 of soil eroded in 2001. The estimates are lower compared to past studies in 2012, 35.9 Pg yr-1 - Increase of 2.5% in soil erosion globally (due to land use change). Spatial coverage: World (125 million Km2 - c.a 84% of the earht surface) Pixel size: 25km. Measurement Unit: t ha-1 yr-1 Projection: GCS_WGS_1984 Temporal coverage: 2012 a More information: Global Soil Erosion https://esdac.jrc.ec.europa.eu/taxonomy/term/4756 -180.0 -56.6229166666667 179.99999999999943 83.58541666666642 UN_Sahel:RUSLE_SoilLoss_v1.1_yr2012_25km image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 177 0 255 EPSG:3857:9 21 354 0 511 EPSG:3857:10 42 708 0 1023 EPSG:3857:11 84 1416 0 2047 EPSG:3857:12 169 2833 0 4095 EPSG:3857:13 338 5666 0 8191 EPSG:3857:14 677 11333 0 16383 EPSG:3857:15 1355 22666 0 32767 EPSG:3857:16 2710 45332 0 65535 EPSG:3857:17 5420 90665 0 131071 EPSG:3857:18 10840 181331 0 262143 EPSG:3857:19 21681 362663 0 524287 EPSG:3857:20 43363 725327 0 1048575 EPSG:3857:21 86726 1450655 0 2097151 EPSG:3857:22 173453 2901310 0 4194304 EPSG:3857:23 346906 5802620 0 8388608 EPSG:3857:24 693812 11605241 0 16777215 EPSG:3857:25 1387625 23210482 0 33554431 EPSG:3857:26 2775251 46420964 0 67108863 EPSG:3857:27 5550503 92841928 0 134217727 EPSG:3857:28 11101006 185683856 0 268435456 EPSG:3857:29 22202013 371367713 0 536870911 EPSG:3857:30 44404027 742735427 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 52 0 127 EPSG:4326:7 4 104 0 255 EPSG:4326:8 9 208 0 511 EPSG:4326:9 18 417 0 1023 EPSG:4326:10 36 834 0 2047 EPSG:4326:11 72 1668 0 4095 EPSG:4326:12 145 3336 0 8191 EPSG:4326:13 291 6672 0 16383 EPSG:4326:14 583 13345 0 32767 EPSG:4326:15 1167 26691 0 65535 EPSG:4326:16 2335 53383 0 131071 EPSG:4326:17 4670 106767 0 262143 EPSG:4326:18 9341 213535 0 524287 EPSG:4326:19 18683 427070 0 1048575 EPSG:4326:20 37367 854140 0 2097151 EPSG:4326:21 74735 1708280 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 177 0 255 EPSG:3857:9 21 354 0 511 EPSG:3857:10 42 708 0 1023 EPSG:3857:11 84 1416 0 2047 EPSG:3857:12 169 2833 0 4095 EPSG:3857:13 338 5666 0 8191 EPSG:3857:14 677 11333 0 16383 EPSG:3857:15 1355 22666 0 32767 EPSG:3857:16 2710 45332 0 65535 EPSG:3857:17 5420 90665 0 131071 EPSG:3857:18 10840 181331 0 262143 EPSG:3857:19 21681 362663 0 524287 EPSG:3857:20 43363 725327 0 1048575 EPSG:3857:21 86726 1450655 0 2097152 EPSG:3857:22 173453 2901310 0 4194304 EPSG:3857:23 346906 5802620 0 8388607 EPSG:3857:24 693812 11605241 0 16777215 EPSG:3857:25 1387625 23210482 0 33554431 EPSG:3857:26 2775251 46420964 0 67108863 EPSG:3857:27 5550503 92841928 0 134217728 EPSG:3857:28 11101006 185683856 0 268435455 EPSG:3857:29 22202013 371367713 0 536870911 EPSG:3857:30 44404027 742735427 0 1073741824 Global Terrestrial Human Footprint (HFP) - 2010 To come -81.71613498761286 -20.61982884080102 153.4232678403954 26.041652531903203 MapX_UNDP:hfp2010_meris_wgs_subset image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27855 36605 17892 60697 EPSG:3857:17 55710 73210 35784 121395 EPSG:3857:18 111420 146421 71568 242791 EPSG:3857:19 222840 292843 143136 485582 EPSG:3857:20 445681 585687 286272 971165 EPSG:3857:21 891362 1171375 572545 1942331 EPSG:3857:22 1782724 2342750 1145090 3884662 EPSG:3857:23 3565448 4685501 2290180 7769325 EPSG:3857:24 7130896 9371002 4580360 15538650 EPSG:3857:25 14261793 18742005 9160720 31077301 EPSG:3857:26 28523587 37484011 18321440 62154602 EPSG:3857:27 57047174 74968023 36642880 124309204 EPSG:3857:28 114094349 149936046 73285761 248618408 EPSG:3857:29 228188699 299872092 146571522 497236816 EPSG:3857:30 456377398 599744184 293143045 994473632 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 90 157 139 474 EPSG:4326:9 181 314 279 948 EPSG:4326:10 363 629 559 1896 EPSG:4326:11 727 1258 1118 3793 EPSG:4326:12 1455 2517 2236 7587 EPSG:4326:13 2910 5034 4473 15174 EPSG:4326:14 5821 10068 8946 30348 EPSG:4326:15 11643 20137 17892 60697 EPSG:4326:16 23286 40275 35784 121395 EPSG:4326:17 46573 80550 71568 242791 EPSG:4326:18 93146 161101 143136 485582 EPSG:4326:19 186292 322203 286272 971165 EPSG:4326:20 372584 644407 572545 1942331 EPSG:4326:21 745168 1288814 1145090 3884662 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 1 2 1 3 EPSG:900913:3 3 4 2 7 EPSG:900913:4 6 8 4 14 EPSG:900913:5 13 17 8 29 EPSG:900913:6 27 35 17 59 EPSG:900913:7 54 71 34 118 EPSG:900913:8 108 142 69 237 EPSG:900913:9 217 285 139 474 EPSG:900913:10 435 571 279 948 EPSG:900913:11 870 1143 559 1896 EPSG:900913:12 1740 2287 1118 3793 EPSG:900913:13 3481 4575 2236 7587 EPSG:900913:14 6963 9151 4473 15174 EPSG:900913:15 13927 18302 8946 30348 EPSG:900913:16 27855 36605 17892 60697 EPSG:900913:17 55710 73210 35784 121395 EPSG:900913:18 111420 146421 71568 242791 EPSG:900913:19 222840 292843 143136 485582 EPSG:900913:20 445681 585687 286272 971165 EPSG:900913:21 891362 1171375 572545 1942331 EPSG:900913:22 1782724 2342750 1145090 3884662 EPSG:900913:23 3565448 4685501 2290180 7769325 EPSG:900913:24 7130896 9371002 4580360 15538650 EPSG:900913:25 14261793 18742005 9160720 31077301 EPSG:900913:26 28523587 37484011 18321440 62154602 EPSG:900913:27 57047174 74968023 36642880 124309204 EPSG:900913:28 114094349 149936046 73285761 248618408 EPSG:900913:29 228188699 299872092 146571522 497236816 EPSG:900913:30 456377398 599744184 293143045 994473632 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27855 36605 17892 60697 EPSG:3857:17 55710 73210 35784 121395 EPSG:3857:18 111420 146421 71568 242791 EPSG:3857:19 222840 292843 143136 485582 EPSG:3857:20 445681 585687 286272 971165 EPSG:3857:21 891362 1171375 572545 1942331 EPSG:3857:22 1782724 2342750 1145090 3884662 EPSG:3857:23 3565448 4685501 2290180 7769325 EPSG:3857:24 7130896 9371002 4580360 15538650 EPSG:3857:25 14261793 18742005 9160720 31077301 EPSG:3857:26 28523587 37484011 18321440 62154602 EPSG:3857:27 57047174 74968023 36642880 124309204 EPSG:3857:28 114094349 149936046 73285761 248618408 EPSG:3857:29 228188699 299872092 146571522 497236816 EPSG:3857:30 456377398 599744184 293143045 994473632 Combination Tsunami/Sea grasses at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_sea9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Global Rainfall Erosivity (R factor) - ESDAC - JRC The new global erosivity map is a critical input to global and continental assessments of soil erosion by water, flood risk and natural hazard prevention. Current global estimates of soil erosion by water are very uncertain, ranging over one order of magnitude (from around 20 to over 200 Pg per year). More accurate global predictions of rill and interrill soil erosion rates can only be achieved when the rainfall erosivity factor is thoroughly computed. The global erosivity map is publicly available and can be used by other research groups to perform national, continental and global soil erosion modelling. This map provides a complete rainfall erosivity dataset for the whole World based on 3,625 precipitation stations and around 60,000 years of rainfall records at high temporal resolution (1 to 60 minutes). Gaussian Process Regression(GPR) model was used to interpolate the rainfall erosivity values of single stations and to generate the R-factor map. Spatial coverage: World Pixel size: 30 arc-seconds (~1 km at the Equator). Measurement Unit: MJ mm ha-1 h-1 yr-1 Temporal coverage: 30-40 years - Predominant in the last decade: 2000 - 2010 References: A complete description of the methodology and the application in World is described in the paper: Panagos P., Borrelli P., Meusburger K., Yu B., Klik A., Lim K.J., Yang J.E, Ni J., Miao C., Chattopadhyay N., Sadeghi S.H., Hazbavi Z., Zabihi M., Larionov G.A., Krasnov S.F., Garobets A., Levi Y., Erpul G., Birkel C., Hoyos N., Naipal V., Oliveira P.T.S., Bonilla C.A., Meddi M., Nel W., Dashti H., Boni M., Diodato N., Van Oost K., Nearing M.A., Ballabio C., 2017. Global rainfall erosivity assessment based on high-temporal resolution rainfall records. Scientific Reports 7: 4175. DOI: 10.1038/s41598-017-04282-8. -179.99999999999997 -58.49228515076997 179.99999999999986 72.25771484922997 UN_Sahel:GlobalR_NoPol_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 3 11 0 15 EPSG:3857:5 6 22 0 31 EPSG:3857:6 13 44 0 63 EPSG:3857:7 26 89 0 127 EPSG:3857:8 52 179 0 255 EPSG:3857:9 104 359 0 511 EPSG:3857:10 209 718 0 1023 EPSG:3857:11 418 1436 0 2047 EPSG:3857:12 837 2872 0 4095 EPSG:3857:13 1674 5745 0 8191 EPSG:3857:14 3348 11491 0 16383 EPSG:3857:15 6697 22983 0 32767 EPSG:3857:16 13394 45967 0 65535 EPSG:3857:17 26789 91935 0 131071 EPSG:3857:18 53578 183870 0 262143 EPSG:3857:19 107157 367740 0 524287 EPSG:3857:20 214315 735480 0 1048575 EPSG:3857:21 428631 1470960 0 2097151 EPSG:3857:22 857263 2941920 0 4194304 EPSG:3857:23 1714527 5883841 0 8388608 EPSG:3857:24 3429054 11767682 0 16777215 EPSG:3857:25 6858109 23535364 0 33554431 EPSG:3857:26 13716219 47070729 0 67108863 EPSG:3857:27 27432438 94141459 0 134217727 EPSG:3857:28 54864877 188282918 0 268435456 EPSG:3857:29 109729754 376565836 0 536870911 EPSG:3857:30 219459509 753131672 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 13 0 31 EPSG:4326:5 3 26 0 63 EPSG:4326:6 6 52 0 127 EPSG:4326:7 12 105 0 255 EPSG:4326:8 25 211 0 511 EPSG:4326:9 50 422 0 1023 EPSG:4326:10 100 844 0 2047 EPSG:4326:11 201 1689 0 4095 EPSG:4326:12 403 3379 0 8191 EPSG:4326:13 807 6758 0 16383 EPSG:4326:14 1614 13516 0 32767 EPSG:4326:15 3229 27032 0 65535 EPSG:4326:16 6459 54064 0 131071 EPSG:4326:17 12919 108128 0 262143 EPSG:4326:18 25839 216257 0 524287 EPSG:4326:19 51678 432515 0 1048575 EPSG:4326:20 103356 865030 0 2097151 EPSG:4326:21 206712 1730060 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 3 11 0 15 EPSG:3857:5 6 22 0 31 EPSG:3857:6 13 44 0 63 EPSG:3857:7 26 89 0 127 EPSG:3857:8 52 179 0 255 EPSG:3857:9 104 359 0 511 EPSG:3857:10 209 718 0 1023 EPSG:3857:11 418 1436 0 2047 EPSG:3857:12 837 2872 0 4095 EPSG:3857:13 1674 5745 0 8191 EPSG:3857:14 3348 11491 0 16383 EPSG:3857:15 6697 22983 0 32767 EPSG:3857:16 13394 45967 0 65535 EPSG:3857:17 26789 91935 0 131071 EPSG:3857:18 53578 183870 0 262143 EPSG:3857:19 107157 367740 0 524287 EPSG:3857:20 214315 735480 0 1048575 EPSG:3857:21 428631 1470960 0 2097152 EPSG:3857:22 857263 2941920 0 4194304 EPSG:3857:23 1714527 5883841 0 8388607 EPSG:3857:24 3429054 11767682 0 16777215 EPSG:3857:25 6858109 23535364 0 33554431 EPSG:3857:26 13716219 47070729 0 67108863 EPSG:3857:27 27432438 94141459 0 134217728 EPSG:3857:28 54864877 188282918 0 268435455 EPSG:3857:29 109729754 376565836 0 536870911 EPSG:3857:30 219459509 753131672 0 1073741824 site_0060_Landsat_v2 -10.858176899138206 8.079534492312552 -10.189521743955197 8.79879002262406 test_imagemosaic_tom:site_0060_Landsat_v2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 30 30 EPSG:4326:6 28 29 60 60 EPSG:4326:7 57 58 120 120 EPSG:4326:8 115 116 240 241 EPSG:4326:9 230 233 481 483 EPSG:4326:10 461 466 962 966 EPSG:4326:11 923 932 1924 1932 EPSG:4326:12 1847 1864 3848 3864 EPSG:4326:13 3695 3728 7697 7728 EPSG:4326:14 7391 7456 15395 15456 EPSG:4326:15 14782 14913 30791 30913 EPSG:4326:16 29564 29826 61582 61826 EPSG:4326:17 59128 59652 123165 123652 EPSG:4326:18 118257 119305 246330 247304 EPSG:4326:19 236515 238610 492661 494608 EPSG:4326:20 473031 477221 985322 989217 EPSG:4326:21 946062 954442 1970645 1978435 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 Combination Tsunami/Forest at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 test_update_lyr -180.0 -90.0 179.9583333336651 85.99166664241335 testing:test_update_lyr image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16382 EPSG:3857:15 0 32767 0 32764 EPSG:3857:16 0 65535 0 65528 EPSG:3857:17 0 131071 0 131056 EPSG:3857:18 0 262143 0 262113 EPSG:3857:19 0 524287 0 524227 EPSG:3857:20 0 1048575 0 1048454 EPSG:3857:21 0 2097151 0 2096909 EPSG:3857:22 -1 4194303 0 4193818 EPSG:3857:23 -1 8388607 0 8387637 EPSG:3857:24 0 16777215 0 16775274 EPSG:3857:25 0 33554431 0 33550548 EPSG:3857:26 0 67108863 0 67101096 EPSG:3857:27 0 134217727 0 134202193 EPSG:3857:28 -1 268435455 0 268404387 EPSG:3857:29 0 536870911 0 536808774 EPSG:3857:30 0 1073741823 0 1073617548 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 2 127 0 255 EPSG:4326:8 5 255 0 511 EPSG:4326:9 11 511 0 1023 EPSG:4326:10 22 1023 0 2047 EPSG:4326:11 45 2047 0 4095 EPSG:4326:12 91 4095 0 8191 EPSG:4326:13 182 8191 0 16382 EPSG:4326:14 364 16383 0 32764 EPSG:4326:15 729 32767 0 65528 EPSG:4326:16 1459 65535 0 131056 EPSG:4326:17 2918 131071 0 262113 EPSG:4326:18 5837 262143 0 524227 EPSG:4326:19 11675 524287 0 1048454 EPSG:4326:20 23350 1048575 0 2096909 EPSG:4326:21 46700 2097151 0 4193818 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16382 EPSG:3857:15 0 32767 0 32764 EPSG:3857:16 0 65535 0 65528 EPSG:3857:17 0 131071 0 131056 EPSG:3857:18 0 262143 0 262113 EPSG:3857:19 0 524287 0 524227 EPSG:3857:20 0 1048575 0 1048454 EPSG:3857:21 -1 2097151 0 2096909 EPSG:3857:22 -1 4194303 0 4193818 EPSG:3857:23 0 8388607 0 8387637 EPSG:3857:24 0 16777215 0 16775274 EPSG:3857:25 0 33554431 0 33550548 EPSG:3857:26 0 67108863 0 67101096 EPSG:3857:27 -1 134217727 0 134202193 EPSG:3857:28 0 268435455 0 268404387 EPSG:3857:29 0 536870911 0 536808774 EPSG:3857:30 -1 1073741823 0 1073617548 20170703Classes Classification of a Sentinel-2 image with post-processing using field knowledge. This research was funded by the Copernicus RawMatCop programme, through funding from EIT RawMaterials and the European Commission DG Internal Market, Industry, Entrepreneurship and SMEs (DG GROW). https://eitrawmaterials.eu/eit-rm-academy/rawmatcop/, in the scope of project CopX: "Geospatial mining transparency through Copernicus and MapX" -74.86103149540197 7.565680150087606 -74.77551708391071 7.624603274629289 UNILIEGE:20170703Classes image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125503 125546 76559 76622 EPSG:3857:19 251006 251093 153119 153244 EPSG:3857:20 502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7497 7503 9569 9577 EPSG:4326:15 14995 15006 19139 19155 EPSG:4326:16 29991 30013 38279 38311 EPSG:4326:17 59983 60026 76559 76622 EPSG:4326:18 119967 120053 153119 153244 EPSG:4326:19 239935 240107 306239 306488 EPSG:4326:20 479871 480214 612478 612977 EPSG:4326:21 959742 960429 1224957 1225954 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125503 125546 76559 76622 EPSG:3857:19 251006 251093 153119 153244 EPSG:3857:20 502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 Albedo Spring 2020 (Copernicus) Unit: ratio of the solar radiation reflected by a surface to the total incoming solar radiation, usually measured between 0 (all incident radiation absorbed) and 1 (all incident radiation refleted). Surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. The present layer represents the black-sky albedo (directional albedo), which is considered as an Essential Climate Variable by the Global Climate Observing System (GCOS). Surface albedo is a sensitive indicator of environmental vulnerability making it a key element required by climate, biogeochemical, hydrological, and weather forecast models. It has a spatial resolution of 1km and is available from the Copernicus Global Land Service (https://land.copernicus.eu/global/products/sa) as netCDF files (technical documentation available at https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_PUM_SA1km-V1_I1.40.pdf. The present raster is the broadband directional albedo over full spectrum [0.3-4µm]. It is the average of the various albedo files available in spring 2020 (3 March 2020, 13 March 2020, 24 March 2020, 3 April 2020, 13 April 2020, 23 April 2020, 3 May 2020, 13 May 2020 and 24 May 2020), then transformed into a geotiff in order to display and example of albedo reflectance in spring. -180.0 -59.995535714253904 179.9955357142039 80.00446428571429 wesr_mountains:c_gls_ALDH_2020_printemps_raster_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 3 53 0 127 EPSG:4326:7 7 106 0 255 EPSG:4326:8 14 213 0 511 EPSG:4326:9 28 426 0 1023 EPSG:4326:10 56 853 0 2047 EPSG:4326:11 113 1706 0 4095 EPSG:4326:12 227 3413 0 8191 EPSG:4326:13 454 6826 0 16383 EPSG:4326:14 909 13652 0 32767 EPSG:4326:15 1819 27305 0 65535 EPSG:4326:16 3639 54611 0 131070 EPSG:4326:17 7278 109223 0 262140 EPSG:4326:18 14557 218446 0 524281 EPSG:4326:19 29114 436893 0 1048562 EPSG:4326:20 58228 873787 0 2097125 EPSG:4326:21 116456 1747574 0 4194251 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 CPSCCF - Coastal Exposure Index Exposure-related variables: Land Cover, Population density Area: Morocco Child Project: SCCF Source: GEF-MedProgramme -6.243055555556 34.6680215 -3.8036111091600007 35.922465945448 medprogramme:MOR_cei_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 6 6 7 7 EPSG:3857:5 12 12 15 15 EPSG:3857:6 25 25 30 31 EPSG:3857:7 50 50 61 62 EPSG:3857:8 100 101 123 125 EPSG:3857:9 201 203 247 250 EPSG:3857:10 402 406 494 501 EPSG:3857:11 804 813 988 1002 EPSG:3857:12 1609 1627 1976 2004 EPSG:3857:13 3219 3254 3953 4009 EPSG:3857:14 6438 6508 7907 8018 EPSG:3857:15 12876 13016 15815 16037 EPSG:3857:16 25752 26032 31631 32075 EPSG:3857:17 51504 52064 63262 64151 EPSG:3857:18 103009 104129 126525 128302 EPSG:3857:19 206019 208258 253051 256604 EPSG:3857:20 412039 416516 506103 513209 EPSG:3857:21 824079 833033 1012207 1026418 EPSG:3857:22 1648159 1666066 2024415 2052836 EPSG:3857:23 3296318 3332133 4048830 4105673 EPSG:3857:24 6592637 6664267 8097660 8211346 EPSG:3857:25 13185274 13328535 16195321 16422693 EPSG:3857:26 26370549 26657071 32390642 32845387 EPSG:3857:27 52741099 53314142 64781284 65690774 EPSG:3857:28 105482198 106628284 129562568 131381549 EPSG:3857:29 210964396 213256568 259125136 262763099 EPSG:3857:30 421928792 426513136 518250273 525526199 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 2 2 7 7 EPSG:4326:4 4 4 15 15 EPSG:4326:5 9 9 30 31 EPSG:4326:6 19 19 61 62 EPSG:4326:7 38 39 123 125 EPSG:4326:8 76 78 247 250 EPSG:4326:9 153 157 494 501 EPSG:4326:10 307 314 988 1002 EPSG:4326:11 615 629 1976 2004 EPSG:4326:12 1230 1259 3953 4009 EPSG:4326:13 2461 2518 7907 8018 EPSG:4326:14 4922 5036 15815 16037 EPSG:4326:15 9844 10072 31631 32075 EPSG:4326:16 19689 20145 63262 64151 EPSG:4326:17 39378 40291 126525 128302 EPSG:4326:18 78756 80583 253051 256604 EPSG:4326:19 157512 161166 506103 513209 EPSG:4326:20 315024 322332 1012207 1026418 EPSG:4326:21 630048 644664 2024415 2052836 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 6 6 7 7 EPSG:3857:5 12 12 15 15 EPSG:3857:6 25 25 30 31 EPSG:3857:7 50 50 61 62 EPSG:3857:8 100 101 123 125 EPSG:3857:9 201 203 247 250 EPSG:3857:10 402 406 494 501 EPSG:3857:11 804 813 988 1002 EPSG:3857:12 1609 1627 1976 2004 EPSG:3857:13 3219 3254 3953 4009 EPSG:3857:14 6438 6508 7907 8018 EPSG:3857:15 12876 13016 15815 16037 EPSG:3857:16 25752 26032 31631 32075 EPSG:3857:17 51504 52064 63262 64151 EPSG:3857:18 103009 104129 126525 128302 EPSG:3857:19 206019 208258 253051 256604 EPSG:3857:20 412039 416516 506103 513209 EPSG:3857:21 824079 833033 1012207 1026418 EPSG:3857:22 1648159 1666066 2024415 2052836 EPSG:3857:23 3296318 3332133 4048830 4105673 EPSG:3857:24 6592637 6664267 8097660 8211346 EPSG:3857:25 13185274 13328535 16195321 16422693 EPSG:3857:26 26370549 26657071 32390642 32845387 EPSG:3857:27 52741099 53314142 64781284 65690774 EPSG:3857:28 105482198 106628284 129562568 131381549 EPSG:3857:29 210964396 213256568 259125136 262763099 EPSG:3857:30 421928792 426513136 518250273 525526199 albania_remote_site_screening_res50 19.262757000000047 39.6460501110001 21.057257000000046 42.6610501110001 mapx_chemobs:albania_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 3 4 4 EPSG:3857:4 5 6 8 8 EPSG:3857:5 11 12 17 17 EPSG:3857:6 23 24 35 35 EPSG:3857:7 47 48 70 71 EPSG:3857:8 94 97 141 142 EPSG:3857:9 188 194 283 285 EPSG:3857:10 377 388 566 571 EPSG:3857:11 755 777 1133 1143 EPSG:3857:12 1510 1555 2267 2287 EPSG:3857:13 3020 3111 4534 4575 EPSG:3857:14 6041 6223 9068 9150 EPSG:3857:15 12082 12447 18137 18300 EPSG:3857:16 24165 24894 36274 36601 EPSG:3857:17 48330 49788 72549 73202 EPSG:3857:18 96661 99577 145098 146405 EPSG:3857:19 193322 199155 290197 292810 EPSG:3857:20 386644 398311 580394 585621 EPSG:3857:21 773289 796622 1160789 1171243 EPSG:3857:22 1546578 1593245 2321579 2342486 EPSG:3857:23 3093157 3186490 4643158 4684973 EPSG:3857:24 6186315 6372981 9286317 9369947 EPSG:3857:25 12372630 12745963 18572635 18739894 EPSG:3857:26 24745261 25491927 37145270 37479789 EPSG:3857:27 49490523 50983854 74290540 74959578 EPSG:3857:28 98981047 101967709 148581080 149919156 EPSG:3857:29 197962095 203935419 297162161 299838313 EPSG:3857:30 395924191 407870838 594324322 599676627 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 2 8 8 EPSG:4326:4 4 4 17 17 EPSG:4326:5 8 8 35 35 EPSG:4326:6 16 17 70 71 EPSG:4326:7 33 35 141 142 EPSG:4326:8 67 71 283 285 EPSG:4326:9 134 143 566 571 EPSG:4326:10 269 286 1133 1143 EPSG:4326:11 538 572 2267 2287 EPSG:4326:12 1077 1145 4534 4575 EPSG:4326:13 2154 2291 9068 9150 EPSG:4326:14 4308 4583 18137 18300 EPSG:4326:15 8617 9166 36274 36601 EPSG:4326:16 17235 18333 72549 73202 EPSG:4326:17 34471 36666 145098 146405 EPSG:4326:18 68942 73333 290197 292810 EPSG:4326:19 137884 146666 580394 585621 EPSG:4326:20 275769 293333 1160789 1171243 EPSG:4326:21 551538 586666 2321579 2342486 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 3 4 4 EPSG:3857:4 5 6 8 8 EPSG:3857:5 11 12 17 17 EPSG:3857:6 23 24 35 35 EPSG:3857:7 47 48 70 71 EPSG:3857:8 94 97 141 142 EPSG:3857:9 188 194 283 285 EPSG:3857:10 377 388 566 571 EPSG:3857:11 755 777 1133 1143 EPSG:3857:12 1510 1555 2267 2287 EPSG:3857:13 3020 3111 4534 4575 EPSG:3857:14 6041 6223 9068 9150 EPSG:3857:15 12082 12447 18137 18300 EPSG:3857:16 24165 24894 36274 36601 EPSG:3857:17 48330 49788 72549 73202 EPSG:3857:18 96661 99577 145098 146405 EPSG:3857:19 193322 199155 290197 292810 EPSG:3857:20 386644 398311 580394 585621 EPSG:3857:21 773289 796622 1160789 1171243 EPSG:3857:22 1546578 1593245 2321579 2342486 EPSG:3857:23 3093157 3186490 4643158 4684973 EPSG:3857:24 6186315 6372981 9286317 9369947 EPSG:3857:25 12372630 12745963 18572635 18739894 EPSG:3857:26 24745261 25491927 37145270 37479789 EPSG:3857:27 49490523 50983854 74290540 74959578 EPSG:3857:28 98981047 101967709 148581080 149919156 EPSG:3857:29 197962095 203935419 297162161 299838313 EPSG:3857:30 395924191 407870838 594324322 599676627 Global Human Modification Index 2017 Detailed global datasets for 1990, 2015, and 2017 for land use modification of terrestrial lands (excluding Antarctica) are provided here. These data were calculated using the degree of human modification approach that combines the proportion of a pixel of a given stressor (i.e. footprint) times the intensity of that stressor (ranging from 0 to 1.0). Our novel datasets are detailed (~300m resolution), temporally consistent (for 1990-2015), comprehensive (11 change stressors, 14 current), robust (using an established framework and incorporating classification errors and parameter uncertainty), and strongly validated. A dataset for ~2017 is also provide, that is derived from 14 stressors, for an even more comprehensive dataset, but it should not be used to calculate change with the other datasets (1990-2015). Theobald, D. M., Kennedy, C., Chen, B., Oakleaf, J., Baruch-Mordo, S., and Kiesecker, J.: Earth transformed: detailed mapping of global human modification from 1990 to 2017, Earth Syst. Sci. Data., https://doi.org/10.5194/essd-2019-252, 2020 Source: https://zenodo.org/record/3963013#.X5ChM0JKjUI -180.0 -75.00027807853427 179.99932064640564 85.00013997386212 MapX_UNDP:gHMv1_2017_wgs image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 26 0 31 EPSG:3857:6 0 52 0 63 EPSG:3857:7 0 105 0 127 EPSG:3857:8 0 210 0 255 EPSG:3857:9 0 421 0 511 EPSG:3857:10 1 842 0 1023 EPSG:3857:11 3 1684 0 2047 EPSG:3857:12 6 3369 0 4095 EPSG:3857:13 13 6739 0 8191 EPSG:3857:14 26 13479 0 16383 EPSG:3857:15 53 26958 0 32767 EPSG:3857:16 107 53916 0 65535 EPSG:3857:17 214 107833 0 131071 EPSG:3857:18 428 215666 0 262143 EPSG:3857:19 856 431333 0 524287 EPSG:3857:20 1712 862667 0 1048574 EPSG:3857:21 3425 1725335 0 2097148 EPSG:3857:22 6851 3450670 0 4194296 EPSG:3857:23 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EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 26 0 31 EPSG:3857:6 0 52 0 63 EPSG:3857:7 0 105 0 127 EPSG:3857:8 0 210 0 255 EPSG:3857:9 0 421 0 511 EPSG:3857:10 1 842 0 1023 EPSG:3857:11 3 1684 0 2047 EPSG:3857:12 6 3369 0 4095 EPSG:3857:13 13 6739 0 8191 EPSG:3857:14 26 13479 0 16383 EPSG:3857:15 53 26958 0 32767 EPSG:3857:16 107 53916 0 65535 EPSG:3857:17 214 107833 0 131071 EPSG:3857:18 428 215666 0 262143 EPSG:3857:19 856 431333 0 524287 EPSG:3857:20 1712 862667 0 1048574 EPSG:3857:21 3425 1725335 0 2097148 EPSG:3857:22 6851 3450670 0 4194296 EPSG:3857:23 13702 6901340 0 8388592 EPSG:3857:24 27404 13802680 0 16777184 EPSG:3857:25 54809 27605360 0 33554368 EPSG:3857:26 109619 55210721 0 67108737 EPSG:3857:27 219238 110421443 0 134217474 EPSG:3857:28 438476 220842886 0 268434949 EPSG:3857:29 876953 441685773 0 536869898 EPSG:3857:30 1753907 883371547 0 1073739797 Bhutan - Carbon Sequestration (upper) 2030 Carbon sequestration map for Bhutan simulated for 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65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 frac_cats_2019_kamituga_west 28.166978184291047 -3.075687270143314 28.181206954060514 -3.0642747063483102 rs_for_asgm:frac_cats_2019_kamituga_west image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 520 592 592 EPSG:3857:11 1041 1041 1184 1184 EPSG:3857:12 2082 2083 2368 2368 EPSG:3857:13 4165 4166 4736 4737 EPSG:3857:14 8331 8332 9473 9474 EPSG:3857:15 16663 16664 18947 18949 EPSG:3857:16 33326 33328 37895 37898 EPSG:3857:17 66652 66656 75791 75796 EPSG:3857:18 133304 133312 151582 151592 EPSG:3857:19 266608 266625 303165 303185 EPSG:3857:20 533217 533250 606330 606371 EPSG:3857:21 1066435 1066501 1212660 1212743 EPSG:3857:22 2132870 2133003 2425321 2425486 EPSG:3857:23 4265740 4266007 4850642 4850973 EPSG:3857:24 8531481 8532014 9701284 9701947 EPSG:3857:25 17062963 17064028 19402568 19403894 EPSG:3857:26 34125926 34128057 38805137 38807789 EPSG:3857:27 68251853 68256114 77610274 77615579 EPSG:3857:28 136503706 136512228 155220549 155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 264 592 592 EPSG:4326:10 529 529 1184 1184 EPSG:4326:11 1058 1058 2368 2368 EPSG:4326:12 2117 2117 4736 4737 EPSG:4326:13 4235 4235 9473 9474 EPSG:4326:14 8470 8471 18947 18949 EPSG:4326:15 16941 16943 37895 37898 EPSG:4326:16 33883 33887 75791 75796 EPSG:4326:17 67767 67775 151582 151592 EPSG:4326:18 135534 135551 303165 303185 EPSG:4326:19 271069 271102 606330 606371 EPSG:4326:20 542138 542205 1212660 1212743 EPSG:4326:21 1084277 1084410 2425321 2425486 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 520 592 592 EPSG:3857:11 1041 1041 1184 1184 EPSG:3857:12 2082 2083 2368 2368 EPSG:3857:13 4165 4166 4736 4737 EPSG:3857:14 8331 8332 9473 9474 EPSG:3857:15 16663 16664 18947 18949 EPSG:3857:16 33326 33328 37895 37898 EPSG:3857:17 66652 66656 75791 75796 EPSG:3857:18 133304 133312 151582 151592 EPSG:3857:19 266608 266625 303165 303185 EPSG:3857:20 533217 533250 606330 606371 EPSG:3857:21 1066435 1066501 1212660 1212743 EPSG:3857:22 2132870 2133003 2425321 2425486 EPSG:3857:23 4265740 4266007 4850642 4850973 EPSG:3857:24 8531481 8532014 9701284 9701947 EPSG:3857:25 17062963 17064028 19402568 19403894 EPSG:3857:26 34125926 34128057 38805137 38807789 EPSG:3857:27 68251853 68256114 77610274 77615579 EPSG:3857:28 136503706 136512228 155220549 155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 Ba200702 0.166015625 11.6953125 15.995117188 23.525390625 MAPX:Ba200702 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1114 EPSG:3857:12 1772 1913 2049 2229 EPSG:3857:13 3544 3827 4099 4459 EPSG:3857:14 7089 7655 8199 8919 EPSG:3857:15 14179 15311 16399 17839 EPSG:3857:16 28359 30623 32798 35679 EPSG:3857:17 56719 61247 65596 71359 EPSG:3857:18 113438 122495 131192 142719 EPSG:3857:19 226877 244991 262385 285438 EPSG:3857:20 453754 489983 524771 570877 EPSG:3857:21 907509 979967 1049543 1141754 EPSG:3857:22 1815018 1959935 2099086 2283508 EPSG:3857:23 3630037 3919871 4198172 4567017 EPSG:3857:24 7260074 7839742 8396344 9134034 EPSG:3857:25 14520148 15679484 16792689 18268068 EPSG:3857:26 29040296 31358968 33585379 36536137 EPSG:3857:27 58080592 62717936 67170759 73072275 EPSG:3857:28 116161185 125435873 134341518 146144551 EPSG:3857:29 232322370 250871747 268683036 292289103 EPSG:3857:30 464644740 501743494 537366072 584578207 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 3 8 8 EPSG:4326:4 5 6 16 17 EPSG:4326:5 11 13 32 34 EPSG:4326:6 23 27 64 69 EPSG:4326:7 47 55 128 139 EPSG:4326:8 94 111 256 278 EPSG:4326:9 189 222 512 557 EPSG:4326:10 378 445 1024 1114 EPSG:4326:11 756 890 2049 2229 EPSG:4326:12 1512 1781 4099 4459 EPSG:4326:13 3025 3563 8199 8919 EPSG:4326:14 6050 7127 16399 17839 EPSG:4326:15 12101 14254 32798 35679 EPSG:4326:16 24202 28509 65596 71359 EPSG:4326:17 48405 57019 131192 142719 EPSG:4326:18 96810 114039 262385 285438 EPSG:4326:19 193621 228078 524771 570877 EPSG:4326:20 387242 456157 1049543 1141754 EPSG:4326:21 774485 912315 2099086 2283508 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 3 3 4 4 EPSG:900913:4 6 7 8 8 EPSG:900913:5 13 14 16 17 EPSG:900913:6 27 29 32 34 EPSG:900913:7 55 59 64 69 EPSG:900913:8 110 119 128 139 EPSG:900913:9 221 239 256 278 EPSG:900913:10 443 478 512 557 EPSG:900913:11 886 956 1024 1114 EPSG:900913:12 1772 1913 2049 2229 EPSG:900913:13 3544 3827 4099 4459 EPSG:900913:14 7089 7655 8199 8919 EPSG:900913:15 14179 15311 16399 17839 EPSG:900913:16 28359 30623 32798 35679 EPSG:900913:17 56719 61247 65596 71359 EPSG:900913:18 113438 122495 131192 142719 EPSG:900913:19 226877 244991 262385 285438 EPSG:900913:20 453754 489983 524771 570877 EPSG:900913:21 907509 979967 1049543 1141754 EPSG:900913:22 1815018 1959935 2099086 2283508 EPSG:900913:23 3630037 3919871 4198172 4567017 EPSG:900913:24 7260074 7839742 8396344 9134034 EPSG:900913:25 14520148 15679484 16792689 18268068 EPSG:900913:26 29040296 31358968 33585379 36536137 EPSG:900913:27 58080592 62717936 67170759 73072275 EPSG:900913:28 116161185 125435873 134341518 146144551 EPSG:900913:29 232322370 250871747 268683036 292289103 EPSG:900913:30 464644740 501743494 537366072 584578207 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1114 EPSG:3857:12 1772 1913 2049 2229 EPSG:3857:13 3544 3827 4099 4459 EPSG:3857:14 7089 7655 8199 8919 EPSG:3857:15 14179 15311 16399 17839 EPSG:3857:16 28359 30623 32798 35679 EPSG:3857:17 56719 61247 65596 71359 EPSG:3857:18 113438 122495 131192 142719 EPSG:3857:19 226877 244991 262385 285438 EPSG:3857:20 453754 489983 524771 570877 EPSG:3857:21 907509 979967 1049543 1141754 EPSG:3857:22 1815018 1959935 2099086 2283508 EPSG:3857:23 3630037 3919871 4198172 4567017 EPSG:3857:24 7260074 7839742 8396344 9134034 EPSG:3857:25 14520148 15679484 16792689 18268068 EPSG:3857:26 29040296 31358968 33585379 36536137 EPSG:3857:27 58080592 62717936 67170759 73072275 EPSG:3857:28 116161185 125435873 134341518 146144551 EPSG:3857:29 232322370 250871747 268683036 292289103 EPSG:3857:30 464644740 501743494 537366072 584578207 Average year precipitations anomalies (1991-2000) over 1991-2020 climatology Average year precipitations anomalies in mm across the period 1991-2000 calculated over the average precipitations per year in the period 1991-2020 (climatology). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_91_00_anom9120 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Coastal Forcing Index The Coastal Forcing Index shows the coastal areas that are facing significant pressures from multiple forces driven by climate change, such as rising sea levels and increasing impacts of waves and storms coming from the sea, as well as extreme precipitation and desertification that are affecting both coastal areas and the inland. Population growth and tourists’ presence represent an added pressure to coastal and inland areas. Combination of: - Sea Level Rise; - Significant wave height; - Soil Aridity; - Extreme precipitations; - Population Growth; - Tourism trend Area: Morocco Child Project: SCCF Source: GEF-MedProgramme -6.243194443839 34.6680215 -3.804305552999 35.920521501002 medprogramme:MOR_cfi_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 6 6 7 7 EPSG:3857:5 12 12 15 15 EPSG:3857:6 25 25 30 31 EPSG:3857:7 50 50 61 62 EPSG:3857:8 100 101 123 125 EPSG:3857:9 201 203 247 250 EPSG:3857:10 402 406 494 501 EPSG:3857:11 804 813 988 1002 EPSG:3857:12 1609 1627 1976 2004 EPSG:3857:13 3219 3254 3953 4009 EPSG:3857:14 6438 6508 7907 8018 EPSG:3857:15 12876 13016 15815 16037 EPSG:3857:16 25752 26032 31631 32075 EPSG:3857:17 51505 52064 63262 64150 EPSG:3857:18 103011 104129 126525 128301 EPSG:3857:19 206023 208258 253051 256603 EPSG:3857:20 412046 416516 506103 513207 EPSG:3857:21 824093 833033 1012206 1026414 EPSG:3857:22 1648187 1666066 2024413 2052828 EPSG:3857:23 3296374 3332133 4048827 4105657 EPSG:3857:24 6592749 6664267 8097654 8211314 EPSG:3857:25 13185498 13328535 16195308 16422629 EPSG:3857:26 26370997 26657071 32390616 32845258 EPSG:3857:27 52741994 53314142 64781232 65690516 EPSG:3857:28 105483988 106628284 129562464 131381032 EPSG:3857:29 210967976 213256568 259124929 262762064 EPSG:3857:30 421935953 426513136 518249859 525524128 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 2 2 7 7 EPSG:4326:4 4 4 15 15 EPSG:4326:5 9 9 30 31 EPSG:4326:6 19 19 61 62 EPSG:4326:7 38 39 123 125 EPSG:4326:8 76 78 247 250 EPSG:4326:9 153 157 494 501 EPSG:4326:10 307 314 988 1002 EPSG:4326:11 615 629 1976 2004 EPSG:4326:12 1230 1259 3953 4009 EPSG:4326:13 2461 2518 7907 8018 EPSG:4326:14 4922 5036 15815 16037 EPSG:4326:15 9844 10072 31631 32075 EPSG:4326:16 19689 20145 63262 64150 EPSG:4326:17 39379 40291 126525 128301 EPSG:4326:18 78758 80583 253051 256603 EPSG:4326:19 157517 161166 506103 513207 EPSG:4326:20 315035 322332 1012206 1026414 EPSG:4326:21 630071 644664 2024413 2052828 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 6 6 7 7 EPSG:3857:5 12 12 15 15 EPSG:3857:6 25 25 30 31 EPSG:3857:7 50 50 61 62 EPSG:3857:8 100 101 123 125 EPSG:3857:9 201 203 247 250 EPSG:3857:10 402 406 494 501 EPSG:3857:11 804 813 988 1002 EPSG:3857:12 1609 1627 1976 2004 EPSG:3857:13 3219 3254 3953 4009 EPSG:3857:14 6438 6508 7907 8018 EPSG:3857:15 12876 13016 15815 16037 EPSG:3857:16 25752 26032 31631 32075 EPSG:3857:17 51505 52064 63262 64150 EPSG:3857:18 103011 104129 126525 128301 EPSG:3857:19 206023 208258 253051 256603 EPSG:3857:20 412046 416516 506103 513207 EPSG:3857:21 824093 833033 1012206 1026414 EPSG:3857:22 1648187 1666066 2024413 2052828 EPSG:3857:23 3296374 3332133 4048827 4105657 EPSG:3857:24 6592749 6664267 8097654 8211314 EPSG:3857:25 13185498 13328535 16195308 16422629 EPSG:3857:26 26370997 26657071 32390616 32845258 EPSG:3857:27 52741994 53314142 64781232 65690516 EPSG:3857:28 105483988 106628284 129562464 131381032 EPSG:3857:29 210967976 213256568 259124929 262762064 EPSG:3857:30 421935953 426513136 518249859 525524128 International Boundaries Polygons Level 0 - UNGIWG International boundary resources are prepared by United Nations Cartographic Section. The 1:1million dataset derived initially from VMAP0 has been corrected to better reflect the cartographic practise of UN Cartographic Section. -180.0 -90.0 180.0 84.4950561523438 grid_data_core_pro:_2012_ungiwg_cnt_ply_01 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 7 255 0 511 EPSG:4326:9 15 511 0 1023 EPSG:4326:10 31 1023 0 2047 EPSG:4326:11 62 2047 0 4095 EPSG:4326:12 125 4095 0 8191 EPSG:4326:13 250 8191 0 16383 EPSG:4326:14 501 16383 0 32767 EPSG:4326:15 1002 32767 0 65535 EPSG:4326:16 2004 65535 0 131071 EPSG:4326:17 4008 131071 0 262143 EPSG:4326:18 8017 262143 0 524287 EPSG:4326:19 16034 524287 0 1048575 EPSG:4326:20 32068 1048575 0 2097151 EPSG:4326:21 64137 2097151 0 4194303 EPSG:900913 forest_loss_su_2022_v1 -58.06766256156945 1.833557839460103 -53.98639912628145 6.011499880852531 tropisco:forest_loss_su_2022_v1 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 5 5 EPSG:3857:5 15 15 10 11 EPSG:3857:6 30 31 21 22 EPSG:3857:7 61 63 43 44 EPSG:3857:8 123 126 86 89 EPSG:3857:9 247 253 173 179 EPSG:3857:10 494 506 346 358 EPSG:3857:11 989 1013 693 716 EPSG:3857:12 1979 2027 1387 1433 EPSG:3857:13 3958 4054 2774 2867 EPSG:3857:14 7917 8108 5549 5735 EPSG:3857:15 15835 16217 11098 11470 EPSG:3857:16 31671 32434 22197 22940 EPSG:3857:17 63343 64868 44394 45880 EPSG:3857:18 126686 129736 88788 91760 EPSG:3857:19 253373 259473 177576 183520 EPSG:3857:20 506746 518946 355153 367041 EPSG:3857:21 1013492 1037892 710307 734082 EPSG:3857:22 2026984 2075785 1420614 1468164 EPSG:3857:23 4053968 4151571 2841229 2936329 EPSG:3857:24 8107936 8303143 5682458 5872659 EPSG:3857:25 16215872 16606286 11364917 11745318 EPSG:3857:26 32431745 33212573 22729835 23490637 EPSG:3857:27 64863490 66425147 45459670 46981275 EPSG:3857:28 129726981 132850294 90919340 93962551 EPSG:3857:29 259453963 265700589 181838681 187925102 EPSG:3857:30 518907927 531401179 363677362 375850204 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 5 5 EPSG:4326:4 7 7 10 11 EPSG:4326:5 14 15 21 22 EPSG:4326:6 29 31 43 44 EPSG:4326:7 59 62 86 89 EPSG:4326:8 119 125 173 179 EPSG:4326:9 238 250 346 358 EPSG:4326:10 477 501 693 716 EPSG:4326:11 955 1003 1387 1433 EPSG:4326:12 1911 2006 2774 2867 EPSG:4326:13 3822 4012 5549 5735 EPSG:4326:14 7644 8025 11098 11470 EPSG:4326:15 15289 16050 22197 22940 EPSG:4326:16 30579 32100 44394 45880 EPSG:4326:17 61158 64200 88788 91760 EPSG:4326:18 122317 128401 177576 183520 EPSG:4326:19 244634 256803 355153 367041 EPSG:4326:20 489268 513606 710307 734082 EPSG:4326:21 978536 1027213 1420614 1468164 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 5 5 EPSG:3857:5 15 15 10 11 EPSG:3857:6 30 31 21 22 EPSG:3857:7 61 63 43 44 EPSG:3857:8 123 126 86 89 EPSG:3857:9 247 253 173 179 EPSG:3857:10 494 506 346 358 EPSG:3857:11 989 1013 693 716 EPSG:3857:12 1979 2027 1387 1433 EPSG:3857:13 3958 4054 2774 2867 EPSG:3857:14 7917 8108 5549 5735 EPSG:3857:15 15835 16217 11098 11470 EPSG:3857:16 31671 32434 22197 22940 EPSG:3857:17 63343 64868 44394 45880 EPSG:3857:18 126686 129736 88788 91760 EPSG:3857:19 253373 259473 177576 183520 EPSG:3857:20 506746 518946 355153 367041 EPSG:3857:21 1013492 1037892 710307 734082 EPSG:3857:22 2026984 2075785 1420614 1468164 EPSG:3857:23 4053968 4151571 2841229 2936329 EPSG:3857:24 8107936 8303143 5682458 5872659 EPSG:3857:25 16215872 16606286 11364917 11745318 EPSG:3857:26 32431745 33212573 22729835 23490637 EPSG:3857:27 64863490 66425147 45459670 46981275 EPSG:3857:28 129726981 132850294 90919340 93962551 EPSG:3857:29 259453963 265700589 181838681 187925102 EPSG:3857:30 518907927 531401179 363677362 375850204 Evapotranspiration Summer 2020 (USGS) The original data is from the USGS FEWS Data Downloads (https://earlywarning.usgs.gov/fews/datadownloads/Global/PET). The present raster in the average monthly evapotranspiration for summer 2020. It in the average of the various evapotranspiration files available in summer 2020 (June 2020, July 2020 and August 2020). On vegetated landscapes, Evapotranspiration (ET) can be simplified as the combination of evaporation from soil and transpiration from vegetation. Actual ET (ETa) is produced using the Operational Simplified Surface Energy Balance (SSEBop) model (Senay et al., 2013) for 2003 to present using data stream from the Aqua satellite. The SSEBop setup is based on the original Simplified Surface Energy Balance (SSEB) approach (Senay et al., 2007, 2011) with unique and improved parameterizations for operational applications. It combines ET fractions generated from remotely sensed MODIS thermal imagery, summarized every 10 days (dekadal), with reference ET, generated from weather data fields using the Penman-Monteith Equation. The unique feature of the SSEBop parameterization is that it uses a pre-defined, seasonally dynamic surface psychrometer constant parameter that helps define the hot/dry and cold/wet reference limits, unique to each pixel. Furthermore, the cold/wet limit is determined using the daily maximum air temperature (Ta) using the c factor parameter which relates Ta to land surface temperature at well-vegetated/well-watered surfaces. The original SSEB model was formulated based on an adaptation of the hot and cold pixel principles of SEBAL (Bastiaanssen et al., 1998) and METRIC (Allen et al., 2007) models. NoData pixels are indicated as NoDATA in ArcGIS. However, other software (e.g., ERDAS imagine) show nodata as -32768.00. ETa data and anomaly products (current vs. 2003 &#8211; 2015 median), produced at 1 km resolution, are available at: https://earlywarning.usgs.gov/fews. -180.0 -60.00000000570601 180.0 80.002258848399 wesr_mountains:m202006-08_ete_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1838 11626 0 16383 EPSG:3857:15 3677 23252 0 32767 EPSG:3857:16 7354 46504 0 65535 EPSG:3857:17 14709 93008 0 131071 EPSG:3857:18 29418 186017 0 262143 EPSG:3857:19 58837 372034 0 524287 EPSG:3857:20 117674 744069 0 1048575 EPSG:3857:21 235349 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1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1838 11626 0 16383 EPSG:3857:15 3677 23252 0 32767 EPSG:3857:16 7354 46504 0 65535 EPSG:3857:17 14709 93008 0 131071 EPSG:3857:18 29418 186017 0 262143 EPSG:3857:19 58837 372034 0 524287 EPSG:3857:20 117674 744069 0 1048575 EPSG:3857:21 235349 1488139 0 2097152 EPSG:3857:22 470698 2976279 0 4194304 EPSG:3857:23 941396 5952559 0 8388607 EPSG:3857:24 1882793 11905118 0 16777215 EPSG:3857:25 3765587 23810236 0 33554431 EPSG:3857:26 7531175 47620473 0 67108863 EPSG:3857:27 15062350 95240947 0 134217728 EPSG:3857:28 30124701 190481895 0 268435455 EPSG:3857:29 60249403 380963791 0 536870911 EPSG:3857:30 120498807 761927583 0 1073741824 02042020_483_clip2_hotspots_test_australia hq sat image Australia for swipe test in hotspot project 148.37206943562214 -36.20649674079372 150.99161622893746 -34.39523606285789 wesr_swipe:02042020_483_clip2_hotspots_test_australia image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 77 77 116 117 EPSG:3857:8 154 155 233 235 EPSG:3857:9 308 311 467 470 EPSG:3857:10 616 622 934 941 EPSG:3857:11 1232 1245 1868 1882 EPSG:3857:12 2465 2490 3736 3765 EPSG:3857:13 4930 4980 7472 7531 EPSG:3857:14 9860 9961 14944 15063 EPSG:3857:15 19721 19923 29889 30127 EPSG:3857:16 39443 39847 59778 60255 EPSG:3857:17 78886 79694 119556 120510 EPSG:3857:18 157773 159389 239113 241020 EPSG:3857:19 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22975 59778 60255 EPSG:4326:16 45290 45950 119556 120510 EPSG:4326:17 90581 91900 239113 241020 EPSG:4326:18 181163 183801 478226 482041 EPSG:4326:19 362327 367603 956452 964082 EPSG:4326:20 724654 735206 1912905 1928165 EPSG:4326:21 1449309 1470412 3825811 3856331 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 77 77 116 117 EPSG:3857:8 154 155 233 235 EPSG:3857:9 308 311 467 470 EPSG:3857:10 616 622 934 941 EPSG:3857:11 1232 1245 1868 1882 EPSG:3857:12 2465 2490 3736 3765 EPSG:3857:13 4930 4980 7472 7531 EPSG:3857:14 9860 9961 14944 15063 EPSG:3857:15 19721 19923 29889 30127 EPSG:3857:16 39443 39847 59778 60255 EPSG:3857:17 78886 79694 119556 120510 EPSG:3857:18 157773 159389 239113 241020 EPSG:3857:19 315547 318779 478226 482041 EPSG:3857:20 631094 637559 956452 964082 EPSG:3857:21 1262189 1275119 1912905 1928165 EPSG:3857:22 2524379 2550238 3825811 3856331 EPSG:3857:23 5048758 5100476 7651623 7712663 EPSG:3857:24 10097516 10200953 15303247 15425327 EPSG:3857:25 20195033 20401907 30606495 30850654 EPSG:3857:26 40390066 40803814 61212990 61701309 EPSG:3857:27 80780133 81607629 122425980 123402618 EPSG:3857:28 161560266 163215258 244851961 246805237 EPSG:3857:29 323120532 326430516 489703923 493610474 EPSG:3857:30 646241065 652861032 979407846 987220949 Global Terrestrial Human Footprint (HFP) - 2000 (subset) This update to the Human Footprint (HFP) provides a measure of the direct and indirect human pressures on the environment globally in years 2000, 2005, 2010, and 2013. Per the orinal Human Footprint, this dataset is derived from remotely-sensed and bottom-up survey information compiled on eight measured variables. This represents not only the most current information of its type, but also the first temporally-consistent set of Human Footprint maps. Data on human pressures were acquired or developed for: 1) built environments, 2) population density, 3) electric infrastructure, 4) crop lands, 5) pasture lands, 6) roads, 7) railways, and 8) navigable waterways. This update incorporates updated and higher resolution population, nightlights, pasture, road, and railway input datasets. The Human Footprint maps find a range of uses as proxies for human disturbance of natural systems and can provide an increased understanding of the human pressures that drive macro-ecological patterns, as well as for tracking environmental change and informing conservation science and application. HFP values range from 0 (no human impact) to 50 (heavily human impacted).<br><br>See: <a href="https://www.nature.com/articles/ncomms12558" target="_blank">Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11</a>.<br/><br>This dataset can be downloaded uniquly from UN Biodiversity Lab. <br> Updated data is made available only to FIP pilot countires at present - rasters are clipped to other FIP data extents. -81.71613729134685 -20.618092964606667 153.42326553667291 26.043388408099844 MapX_UNDP:hfp2000_merisINT_subsetsGlobal image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27854 36605 17892 60697 EPSG:3857:17 55709 73210 35784 121395 EPSG:3857:18 111418 146420 71568 242791 EPSG:3857:19 222837 292841 143136 485582 EPSG:3857:20 445675 585682 286272 971165 EPSG:3857:21 891350 1171364 572544 1942331 EPSG:3857:22 1782701 2342729 1145089 3884662 EPSG:3857:23 3565403 4685458 2290179 7769325 EPSG:3857:24 7130806 9370916 4580359 15538650 EPSG:3857:25 14261613 18741832 9160719 31077300 EPSG:3857:26 28523227 37483665 18321439 62154601 EPSG:3857:27 57046454 74967331 36642879 124309203 EPSG:3857:28 114092909 149934663 73285759 248618406 EPSG:3857:29 228185818 299869326 146571519 497236812 EPSG:3857:30 456371636 599738652 293143038 994473625 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 90 157 139 474 EPSG:4326:9 181 314 279 948 EPSG:4326:10 363 629 559 1896 EPSG:4326:11 727 1258 1118 3793 EPSG:4326:12 1455 2517 2236 7587 EPSG:4326:13 2910 5034 4473 15174 EPSG:4326:14 5821 10068 8946 30348 EPSG:4326:15 11642 20137 17892 60697 EPSG:4326:16 23285 40274 35784 121395 EPSG:4326:17 46571 80549 71568 242791 EPSG:4326:18 93143 161099 143136 485582 EPSG:4326:19 186287 322198 286272 971165 EPSG:4326:20 372574 644397 572544 1942331 EPSG:4326:21 745148 1288794 1145089 3884662 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27854 36605 17892 60697 EPSG:3857:17 55709 73210 35784 121395 EPSG:3857:18 111418 146420 71568 242791 EPSG:3857:19 222837 292841 143136 485582 EPSG:3857:20 445675 585682 286272 971165 EPSG:3857:21 891350 1171364 572544 1942331 EPSG:3857:22 1782701 2342729 1145089 3884662 EPSG:3857:23 3565403 4685458 2290179 7769325 EPSG:3857:24 7130806 9370916 4580359 15538650 EPSG:3857:25 14261613 18741832 9160719 31077300 EPSG:3857:26 28523227 37483665 18321439 62154601 EPSG:3857:27 57046454 74967331 36642879 124309203 EPSG:3857:28 114092909 149934663 73285759 248618406 EPSG:3857:29 228185818 299869326 146571519 497236812 EPSG:3857:30 456371636 599738652 293143038 994473625 Evapotranspiration anomaly 2016_USGS Data downloaded directly from USGS. -20.00844965760001 -38.005350777400054 55.006893565199974 40.002112414399946 MAPX:y2016_modisSSEBopETv4_anomaly_pct image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 1 2 3 5 EPSG:4326:3 2 5 7 10 EPSG:4326:4 4 11 14 20 EPSG:4326:5 8 22 28 41 EPSG:4326:6 17 45 56 83 EPSG:4326:7 35 91 113 167 EPSG:4326:8 71 182 227 334 EPSG:4326:9 142 364 455 668 EPSG:4326:10 284 728 910 1336 EPSG:4326:11 568 1456 1820 2673 EPSG:4326:12 1137 2912 3640 5347 EPSG:4326:13 2275 5825 7281 10695 EPSG:4326:14 4550 11651 14562 21390 EPSG:4326:15 9101 23302 29125 42781 EPSG:4326:16 18203 46605 58251 85563 EPSG:4326:17 36407 93210 116502 171126 EPSG:4326:18 72814 186421 233004 342253 EPSG:4326:19 145629 372842 466009 684507 EPSG:4326:20 291258 745685 932018 1369014 EPSG:4326:21 582517 1491370 1864036 2738028 EPSG:900913 UN Country Administrative Boundaries 2018 United Nations map (known as UNmap) is a worldwide geospatial database consisting of country and geographic name information on a global scale. The data is designed for the production of cartographic documents and maps, including their dissemination via public electronic networks, for the Secretariat of the United Nations.The United Nations maintains the Data as a courtesy to those who may choose to access the Data. The Data is provided “as is”, without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose and non-infringement.<br> <br> Disclaimers: <br> - The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations. <br> - The designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. <br> - Dotted line represents approximately the Line of Control in Jammu and Kashmir agreed upon by India and Pakistan. <br> - The final status of Jammu and Kashmir has not yet been agreed upon by the parties. <br> - Final boundary between the Republic of Sudan and the Republic of South Sudan has not yet been determined. <br> - Final status of the Abyei area is not yet determined. <br> - A dispute exists between the Governments of Argentina and the United Kingdom of Great Britain and Northern Ireland concerning sovereignty over the Falkland Islands (Malvinas).<br> <br> Generalization parametrisation for the data is developed based on the work of Douglas and Peucker (1973), Wang (1996) and the Polynomial Approximation with Exponential Kernel algorithm.The adequate generalized data should be used for the intended dissemination scale and not rely on software or platform-automated generalization as some specific geographic features are removed at scales. For instance, the region of Abyei is not included at the scale of 1:25 million but is included at lower scales.<br> <br> Maps produced using this layer should be featured with the appropriate disclaimer depending on the shown area.<br><br> Source: United Nations International and Administrative Boundaries Resources -180.0 -89.90000152599998 180.0 83.62741851600005 grid_data_core_pro:UN0_administrative_boundaries_2018 application/vnd.mapbox-vector-tile image/png image/vnd.jpeg-png image/jpeg application/json;type=geojson application/json;type=topojson image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 41 1023 0 1023 EPSG:3857:11 82 2047 0 2047 EPSG:3857:12 165 4095 0 4095 EPSG:3857:13 330 8191 0 8191 EPSG:3857:14 660 16383 0 16383 EPSG:3857:15 1320 32767 0 32767 EPSG:3857:16 2641 65535 0 65535 EPSG:3857:17 5283 131071 0 131071 EPSG:3857:18 10566 262143 0 262143 EPSG:3857:19 21132 524287 0 524287 EPSG:3857:20 42264 1048575 0 1048575 EPSG:3857:21 84529 2097151 0 2097151 EPSG:3857:22 169058 4194303 0 4194304 EPSG:3857:23 338117 8388607 0 8388608 EPSG:3857:24 676235 16777215 0 16777215 EPSG:3857:25 1352470 33554431 0 33554431 EPSG:3857:26 2704940 67108863 0 67108863 EPSG:3857:27 5409880 134217727 0 134217727 EPSG:3857:28 10819760 268435455 0 268435456 EPSG:3857:29 21639520 536870911 0 536870911 EPSG:3857:30 43279041 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 9 255 0 511 EPSG:4326:9 18 511 0 1023 EPSG:4326:10 36 1023 0 2047 EPSG:4326:11 72 2046 0 4095 EPSG:4326:12 145 4093 0 8191 EPSG:4326:13 290 8187 0 16383 EPSG:4326:14 580 16374 0 32767 EPSG:4326:15 1160 32749 0 65535 EPSG:4326:16 2320 65499 0 131071 EPSG:4326:17 4640 130999 0 262143 EPSG:4326:18 9280 261998 0 524287 EPSG:4326:19 18561 523996 0 1048575 EPSG:4326:20 37122 1047993 0 2097151 EPSG:4326:21 74245 2095986 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 1 31 0 31 EPSG:900913:6 2 63 0 63 EPSG:900913:7 5 127 0 127 EPSG:900913:8 10 255 0 255 EPSG:900913:9 20 511 0 511 EPSG:900913:10 41 1023 0 1023 EPSG:900913:11 82 2047 0 2047 EPSG:900913:12 165 4095 0 4095 EPSG:900913:13 330 8191 0 8191 EPSG:900913:14 660 16383 0 16383 EPSG:900913:15 1320 32767 0 32767 EPSG:900913:16 2641 65535 0 65535 EPSG:900913:17 5283 131071 0 131071 EPSG:900913:18 10566 262143 0 262143 EPSG:900913:19 21132 524287 0 524287 EPSG:900913:20 42264 1048575 0 1048575 EPSG:900913:21 84529 2097151 0 2097151 EPSG:900913:22 169058 4194303 0 4194303 EPSG:900913:23 338117 8388607 0 8388607 EPSG:900913:24 676235 16777215 0 16777215 EPSG:900913:25 1352470 33554431 0 33554431 EPSG:900913:26 2704940 67108863 0 67108863 EPSG:900913:27 5409880 134217727 0 134217727 EPSG:900913:28 10819760 268435455 0 268435455 EPSG:900913:29 21639520 536870911 0 536870911 EPSG:900913:30 43279041 1073741823 0 1073741823 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 41 1023 0 1023 EPSG:3857:11 82 2047 0 2047 EPSG:3857:12 165 4095 0 4095 EPSG:3857:13 330 8191 0 8191 EPSG:3857:14 660 16383 0 16383 EPSG:3857:15 1320 32767 0 32767 EPSG:3857:16 2641 65535 0 65535 EPSG:3857:17 5283 131071 0 131071 EPSG:3857:18 10566 262143 0 262143 EPSG:3857:19 21132 524287 0 524287 EPSG:3857:20 42264 1048575 0 1048575 EPSG:3857:21 84529 2097151 0 2097152 EPSG:3857:22 169058 4194303 0 4194304 EPSG:3857:23 338117 8388607 0 8388607 EPSG:3857:24 676235 16777215 0 16777215 EPSG:3857:25 1352470 33554431 0 33554431 EPSG:3857:26 2704940 67108863 0 67108863 EPSG:3857:27 5409880 134217727 0 134217728 EPSG:3857:28 10819760 268435455 0 268435455 EPSG:3857:29 21639520 536870911 0 536870911 EPSG:3857:30 43279041 1073741823 0 1073741824 Average year precipitations (2001-2010) Average year precipitations in mm across the period 2001-2010. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_01_10_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Deforestation and Degradation - 2015-2020 (CAFI) The layer shows the degraded forest areas and the deforested areas in the Congo Basin. Data produced in the frame of the project "Assessing deforestation and forest degradation trends and associated current and historical direct drivers in the six CAFI partner countries". Credits: CAFI. Central African Forest Initiative 5.354407954878081 -13.459105669480616 31.7723896460075 13.083556355951599 peatlands:CAFI_change_map_2015_2020_sinu_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 14 17 16 18 EPSG:3857:6 29 34 32 37 EPSG:3857:7 59 68 65 75 EPSG:3857:8 118 137 131 150 EPSG:3857:9 237 275 263 301 EPSG:3857:10 474 550 527 602 EPSG:3857:11 948 1101 1054 1204 EPSG:3857:12 1897 2202 2108 2409 EPSG:3857:13 3795 4405 4217 4818 EPSG:3857:14 7591 8810 8435 9637 EPSG:3857:15 15182 17620 16871 19275 EPSG:3857:16 30365 35241 33742 38551 EPSG:3857:17 60730 70482 67485 77103 EPSG:3857:18 121460 140964 134970 154207 EPSG:3857:19 242921 281928 269941 308415 EPSG:3857:20 485843 563856 539883 616831 EPSG:3857:21 971687 1127712 1079767 1233663 EPSG:3857:22 1943375 2255424 2159535 2467327 EPSG:3857:23 3886750 4510848 4319070 4934654 EPSG:3857:24 7773500 9021697 8638141 9869308 EPSG:3857:25 15547001 18043394 17276282 19738617 EPSG:3857:26 31094003 36086789 34552565 39477234 EPSG:3857:27 62188007 72173578 69105131 78954469 EPSG:3857:28 124376014 144347156 138210263 157908938 EPSG:3857:29 248752028 288694312 276420527 315817877 EPSG:3857:30 497504056 577388624 552841055 631635755 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 6 9 16 18 EPSG:4326:5 13 18 32 37 EPSG:4326:6 27 36 65 75 EPSG:4326:7 54 73 131 150 EPSG:4326:8 109 147 263 301 EPSG:4326:9 218 294 527 602 EPSG:4326:10 437 588 1054 1204 EPSG:4326:11 875 1177 2108 2409 EPSG:4326:12 1750 2354 4217 4818 EPSG:4326:13 3500 4708 8435 9637 EPSG:4326:14 7001 9417 16871 19275 EPSG:4326:15 14002 18834 33742 38551 EPSG:4326:16 28004 37668 67485 77103 EPSG:4326:17 56008 75336 134970 154207 EPSG:4326:18 112017 150673 269941 308415 EPSG:4326:19 224035 301346 539883 616831 EPSG:4326:20 448070 602692 1079767 1233663 EPSG:4326:21 896141 1205385 2159535 2467327 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 14 17 16 18 EPSG:3857:6 29 34 32 37 EPSG:3857:7 59 68 65 75 EPSG:3857:8 118 137 131 150 EPSG:3857:9 237 275 263 301 EPSG:3857:10 474 550 527 602 EPSG:3857:11 948 1101 1054 1204 EPSG:3857:12 1897 2202 2108 2409 EPSG:3857:13 3795 4405 4217 4818 EPSG:3857:14 7591 8810 8435 9637 EPSG:3857:15 15182 17620 16871 19275 EPSG:3857:16 30365 35241 33742 38551 EPSG:3857:17 60730 70482 67485 77103 EPSG:3857:18 121460 140964 134970 154207 EPSG:3857:19 242921 281928 269941 308415 EPSG:3857:20 485843 563856 539883 616831 EPSG:3857:21 971687 1127712 1079767 1233663 EPSG:3857:22 1943375 2255424 2159535 2467327 EPSG:3857:23 3886750 4510848 4319070 4934654 EPSG:3857:24 7773500 9021697 8638141 9869308 EPSG:3857:25 15547001 18043394 17276282 19738617 EPSG:3857:26 31094003 36086789 34552565 39477234 EPSG:3857:27 62188007 72173578 69105131 78954469 EPSG:3857:28 124376014 144347156 138210263 157908938 EPSG:3857:29 248752028 288694312 276420527 315817877 EPSG:3857:30 497504056 577388624 552841055 631635755 Temperature Seasonality - Climatology (1979-2013) [standard deviation] Standard deviation of the monthly mean temperatures [standard deviation]. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_bio10_04_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 South Sudan SRTM 30 Meters This data represents the 30 meters Digital Elevation Model (DEM) from Shuttle Radar Topography Mission (SRTM). This data-set was derived through mosaicking of individual SRTM tiles for a particular country and clipping the mosaicked tiles using the country boundary extent. 24.139861111111113 3.492916666666666 35.941250000000004 12.219027777777777 MAPX:South_Sudan_SRTM30meters_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2456 EPSG:3857:13 3815 4016 4645 4913 EPSG:3857:14 7631 8032 9290 9827 EPSG:3857:15 15263 16065 18581 19655 EPSG:3857:16 30526 32131 37162 39310 EPSG:3857:17 61053 64263 74325 78621 EPSG:3857:18 122106 128526 148650 157243 EPSG:3857:19 244212 257053 297300 314487 EPSG:3857:20 488424 514107 594600 628974 EPSG:3857:21 976849 1028215 1189200 1257948 EPSG:3857:22 1953698 2056431 2378401 2515897 EPSG:3857:23 3907396 4112862 4756803 5031795 EPSG:3857:24 7814793 8225725 9513607 10063591 EPSG:3857:25 15629587 16451450 19027214 20127183 EPSG:3857:26 31259175 32902901 38054428 40254366 EPSG:3857:27 62518350 65805802 76108856 80508733 EPSG:3857:28 125036700 131611605 152217713 161017466 EPSG:3857:29 250073401 263223211 304435426 322034932 EPSG:3857:30 500146803 526446423 608870852 644069865 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 6 7 18 19 EPSG:4326:5 13 15 36 38 EPSG:4326:6 27 30 72 76 EPSG:4326:7 55 61 145 153 EPSG:4326:8 110 123 290 307 EPSG:4326:9 221 246 580 614 EPSG:4326:10 442 492 1161 1228 EPSG:4326:11 884 984 2322 2456 EPSG:4326:12 1769 1968 4645 4913 EPSG:4326:13 3539 3937 9290 9827 EPSG:4326:14 7079 7874 18581 19655 EPSG:4326:15 14159 15748 37162 39310 EPSG:4326:16 28319 31496 74325 78621 EPSG:4326:17 56638 62992 148650 157243 EPSG:4326:18 113276 125985 297300 314487 EPSG:4326:19 226553 251970 594600 628974 EPSG:4326:20 453107 503940 1189200 1257948 EPSG:4326:21 906214 1007880 2378401 2515897 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2456 EPSG:3857:13 3815 4016 4645 4913 EPSG:3857:14 7631 8032 9290 9827 EPSG:3857:15 15263 16065 18581 19655 EPSG:3857:16 30526 32131 37162 39310 EPSG:3857:17 61053 64263 74325 78621 EPSG:3857:18 122106 128526 148650 157243 EPSG:3857:19 244212 257053 297300 314487 EPSG:3857:20 488424 514107 594600 628974 EPSG:3857:21 976849 1028215 1189200 1257948 EPSG:3857:22 1953698 2056431 2378401 2515897 EPSG:3857:23 3907396 4112862 4756803 5031795 EPSG:3857:24 7814793 8225725 9513607 10063591 EPSG:3857:25 15629587 16451450 19027214 20127183 EPSG:3857:26 31259175 32902901 38054428 40254366 EPSG:3857:27 62518350 65805802 76108856 80508733 EPSG:3857:28 125036700 131611605 152217713 161017466 EPSG:3857:29 250073401 263223211 304435426 322034932 EPSG:3857:30 500146803 526446423 608870852 644069865 1991-2000 Average year precipitations change since previous decade (1981-1900) Average year precipitations anomalies in mm across the period 1991-2000 calculated over the average precipitations per year in the period 1981-1990. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_91_00_anom_81_90 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Evapotranspiration Spring 2020 (USGS) The original data is from the USGS FEWS Data Downloads (https://earlywarning.usgs.gov/fews/datadownloads/Global/PET). The present raster in the average monthly evapotranspiration for spring 2020. It in the average of the various evapotranspiration files available in spring 2020 (March 2020, April 2020 and May 2020). On vegetated landscapes, Evapotranspiration (ET) can be simplified as the combination of evaporation from soil and transpiration from vegetation. Actual ET (ETa) is produced using the Operational Simplified Surface Energy Balance (SSEBop) model (Senay et al., 2013) for 2003 to present using data stream from the Aqua satellite. The SSEBop setup is based on the original Simplified Surface Energy Balance (SSEB) approach (Senay et al., 2007, 2011) with unique and improved parameterizations for operational applications. It combines ET fractions generated from remotely sensed MODIS thermal imagery, summarized every 10 days (dekadal), with reference ET, generated from weather data fields using the Penman-Monteith Equation. The unique feature of the SSEBop parameterization is that it uses a pre-defined, seasonally dynamic surface psychrometer constant parameter that helps define the hot/dry and cold/wet reference limits, unique to each pixel. Furthermore, the cold/wet limit is determined using the daily maximum air temperature (Ta) using the c factor parameter which relates Ta to land surface temperature at well-vegetated/well-watered surfaces. The original SSEB model was formulated based on an adaptation of the hot and cold pixel principles of SEBAL (Bastiaanssen et al., 1998) and METRIC (Allen et al., 2007) models. NoData pixels are indicated as NoDATA in ArcGIS. However, other software (e.g., ERDAS imagine) show nodata as -32768.00. ETa data and anomaly products (current vs. 2003 &#8211; 2015 median), produced at 1 km resolution, are available at: https://earlywarning.usgs.gov/fews. -180.0 -60.00000000570601 180.0 80.002258848399 wesr_mountains:m202003-05_printemps_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1838 11626 0 16383 EPSG:3857:15 3677 23252 0 32767 EPSG:3857:16 7354 46504 0 65535 EPSG:3857:17 14709 93008 0 131071 EPSG:3857:18 29418 186017 0 262143 EPSG:3857:19 58837 372034 0 524287 EPSG:3857:20 117674 744069 0 1048575 EPSG:3857:21 235349 1488139 0 2097151 EPSG:3857:22 470698 2976279 0 4194304 EPSG:3857:23 941396 5952559 0 8388608 EPSG:3857:24 1882793 11905118 0 16777215 EPSG:3857:25 3765587 23810236 0 33554431 EPSG:3857:26 7531175 47620473 0 67108863 EPSG:3857:27 15062350 95240947 0 134217727 EPSG:3857:28 30124701 190481895 0 268435456 EPSG:3857:29 60249403 380963791 0 536870911 EPSG:3857:30 120498807 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 3 53 0 127 EPSG:4326:7 7 106 0 255 EPSG:4326:8 14 213 0 511 EPSG:4326:9 28 426 0 1023 EPSG:4326:10 56 853 0 2047 EPSG:4326:11 113 1706 0 4095 EPSG:4326:12 227 3413 0 8191 EPSG:4326:13 455 6826 0 16383 EPSG:4326:14 910 13653 0 32767 EPSG:4326:15 1820 27306 0 65535 EPSG:4326:16 3640 54613 0 131071 EPSG:4326:17 7280 109226 0 262143 EPSG:4326:18 14560 218453 0 524287 EPSG:4326:19 29120 436906 0 1048575 EPSG:4326:20 58241 873813 0 2097151 EPSG:4326:21 116482 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1838 11626 0 16383 EPSG:3857:15 3677 23252 0 32767 EPSG:3857:16 7354 46504 0 65535 EPSG:3857:17 14709 93008 0 131071 EPSG:3857:18 29418 186017 0 262143 EPSG:3857:19 58837 372034 0 524287 EPSG:3857:20 117674 744069 0 1048575 EPSG:3857:21 235349 1488139 0 2097152 EPSG:3857:22 470698 2976279 0 4194304 EPSG:3857:23 941396 5952559 0 8388607 EPSG:3857:24 1882793 11905118 0 16777215 EPSG:3857:25 3765587 23810236 0 33554431 EPSG:3857:26 7531175 47620473 0 67108863 EPSG:3857:27 15062350 95240947 0 134217728 EPSG:3857:28 30124701 190481895 0 268435455 EPSG:3857:29 60249403 380963791 0 536870911 EPSG:3857:30 120498807 761927583 0 1073741824 Spring temperature change (°C) for the period 2020 - 2039 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_mam_NEARREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Combination Tropical cyclone surge/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_for6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Sea grasses total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:seagrakm2a_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 NVG_2000 -180.0 -90.0 180.0 90.0 mapx_chemobs:NVG_2000 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mean temperatures 2018 - Central African Republic Mean observed temperatures in 2018 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2018_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 UN Country Administrative Boundaries 2020 United Nations map geospatial database (and hereafter referred to as the “Data”) is a worldwide geospatial database consisting of country and geographic name information on a global scale. The data is designed for the production of cartographic documents and maps, including their dissemination via public electronic networks, for the Secretariat of the United Nations. The United Nations maintains the Data as a courtesy to those who may choose to access the Data (“Users”). The Data is provided “as is”, without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose and non-infringement. The designations employed and the presentation of material contained in the Data do not imply the expression of any opinion whatsoever on the part of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.<br> <br> Disclaimers: <br> - The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations. <br> - The designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.<br> - Dotted line represents approximately the Line of Control in Jammu and Kashmir agreed upon by India and Pakistan. The final status of Jammu and Kashmir has not yet been agreed upon by the parties. <br> - Final boundary between the Republic of Sudan and the Republic of South Sudan has not yet been determined. <br> - Final status of the Abyei area is not yet determined. <br> - A dispute exists between the Governments of Argentina and the United Kingdom of Great Britain and Northern Ireland concerning sovereignty over the Falkland Islands (Malvinas).<br> <br> Generalization parametrization for the Data is developed based on the work of Douglas and Peucker (1973), Wang (1996) and the Polynomial Approximation with Exponential Kernel algorithm. The adequate generalized Data should be used for the intended dissemination scale and not rely on software or platform-automated generalization as some specific geographic features are removed at scales. For example, the region of Abyei is not included at the scale of 1:25 million but is included at larger scales.<br> <br> Maps produced using this layer should be featured with the appropriate disclaimer depending on the shown area.<br><br> Source: United Nations International and Administrative Boundaries Resources -180.0 -89.90000152599998 180.0 83.62741851600002 grid_data_core_pro:UN0_administrative_boundaries_2020 application/vnd.mapbox-vector-tile image/png image/vnd.jpeg-png image/jpeg application/json;type=geojson application/json;type=topojson image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 41 1023 0 1023 EPSG:3857:11 82 2047 0 2047 EPSG:3857:12 165 4095 0 4095 EPSG:3857:13 330 8191 0 8191 EPSG:3857:14 660 16383 0 16383 EPSG:3857:15 1320 32767 0 32767 EPSG:3857:16 2641 65535 0 65535 EPSG:3857:17 5283 131071 0 131071 EPSG:3857:18 10566 262143 0 262143 EPSG:3857:19 21132 524287 0 524287 EPSG:3857:20 42264 1048575 0 1048575 EPSG:3857:21 84529 2097151 0 2097151 EPSG:3857:22 169058 4194303 0 4194304 EPSG:3857:23 338117 8388607 0 8388608 EPSG:3857:24 676235 16777215 0 16777215 EPSG:3857:25 1352470 33554431 0 33554431 EPSG:3857:26 2704940 67108863 0 67108863 EPSG:3857:27 5409880 134217727 0 134217727 EPSG:3857:28 10819760 268435455 0 268435456 EPSG:3857:29 21639520 536870911 0 536870911 EPSG:3857:30 43279041 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 9 255 0 511 EPSG:4326:9 18 511 0 1023 EPSG:4326:10 36 1023 0 2047 EPSG:4326:11 72 2046 0 4095 EPSG:4326:12 145 4093 0 8191 EPSG:4326:13 290 8187 0 16383 EPSG:4326:14 580 16374 0 32767 EPSG:4326:15 1160 32749 0 65535 EPSG:4326:16 2320 65499 0 131071 EPSG:4326:17 4640 130999 0 262143 EPSG:4326:18 9280 261998 0 524287 EPSG:4326:19 18561 523996 0 1048575 EPSG:4326:20 37122 1047993 0 2097151 EPSG:4326:21 74245 2095986 0 4194303 EPSG:32637 0 0 0 0 0 1 0 0 0 0 2 0 1 0 0 3 0 3 0 0 4 0 7 0 0 5 0 14 0 1 6 0 29 0 2 7 0 59 0 4 8 0 119 0 8 9 0 238 0 17 10 0 477 0 34 11 0 955 0 68 12 0 1910 0 136 13 0 3820 0 273 14 0 7640 0 547 15 0 15281 0 1094 16 0 30563 0 2188 17 0 61126 0 4376 18 0 122253 0 8753 19 0 244506 0 17506 20 0 489012 0 35013 21 0 978024 0 70026 22 0 1956049 0 140053 23 0 3912099 0 280106 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 41 1023 0 1023 EPSG:3857:11 82 2047 0 2047 EPSG:3857:12 165 4095 0 4095 EPSG:3857:13 330 8191 0 8191 EPSG:3857:14 660 16383 0 16383 EPSG:3857:15 1320 32767 0 32767 EPSG:3857:16 2641 65535 0 65535 EPSG:3857:17 5283 131071 0 131071 EPSG:3857:18 10566 262143 0 262143 EPSG:3857:19 21132 524287 0 524287 EPSG:3857:20 42264 1048575 0 1048575 EPSG:3857:21 84529 2097151 0 2097152 EPSG:3857:22 169058 4194303 0 4194304 EPSG:3857:23 338117 8388607 0 8388607 EPSG:3857:24 676235 16777215 0 16777215 EPSG:3857:25 1352470 33554431 0 33554431 EPSG:3857:26 2704940 67108863 0 67108863 EPSG:3857:27 5409880 134217727 0 134217728 EPSG:3857:28 10819760 268435455 0 268435455 EPSG:3857:29 21639520 536870911 0 536870911 EPSG:3857:30 43279041 1073741823 0 1073741824 K2_new_YG -180.0 -59.47894000000001 179.97859 83.64583 grid_data_core:K2_new_YG image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 45 0 63 EPSG:3857:7 5 90 0 127 EPSG:3857:8 10 180 0 255 EPSG:3857:9 20 361 0 511 EPSG:3857:10 40 723 0 1023 EPSG:3857:11 81 1447 0 2047 EPSG:3857:12 163 2894 0 4095 EPSG:3857:13 326 5789 0 8191 EPSG:3857:14 652 11579 0 16383 EPSG:3857:15 1305 23158 0 32766 EPSG:3857:16 2611 46316 0 65532 EPSG:3857:17 5222 92632 0 131064 EPSG:3857:18 10445 185264 0 262128 EPSG:3857:19 20890 370529 0 524256 EPSG:3857:20 41780 741058 0 1048513 EPSG:3857:21 83561 1482116 0 2097027 EPSG:3857:22 167123 2964232 0 4194054 EPSG:3857:23 334246 5928465 0 8388109 EPSG:3857:24 668493 11856930 0 16776218 EPSG:3857:25 1336986 23713860 0 33552436 EPSG:3857:26 2673973 47427720 0 67104872 EPSG:3857:27 5347946 94855440 0 134209745 EPSG:3857:28 10695893 189710880 0 268419491 EPSG:3857:29 21391787 379421761 0 536838983 EPSG:3857:30 42783574 758843523 0 1073677966 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 9 212 0 511 EPSG:4326:9 18 425 0 1023 EPSG:4326:10 36 850 0 2047 EPSG:4326:11 72 1700 0 4095 EPSG:4326:12 144 3401 0 8191 EPSG:4326:13 289 6802 0 16383 EPSG:4326:14 578 13605 0 32766 EPSG:4326:15 1156 27211 0 65532 EPSG:4326:16 2313 54423 0 131064 EPSG:4326:17 4626 108847 0 262128 EPSG:4326:18 9253 217694 0 524256 EPSG:4326:19 18507 435388 0 1048513 EPSG:4326:20 37015 870777 0 2097027 EPSG:4326:21 74031 1741555 0 4194054 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 45 0 63 EPSG:3857:7 5 90 0 127 EPSG:3857:8 10 180 0 255 EPSG:3857:9 20 361 0 511 EPSG:3857:10 40 723 0 1023 EPSG:3857:11 81 1447 0 2047 EPSG:3857:12 163 2894 0 4095 EPSG:3857:13 326 5789 0 8191 EPSG:3857:14 652 11579 0 16383 EPSG:3857:15 1305 23158 0 32766 EPSG:3857:16 2611 46316 0 65532 EPSG:3857:17 5222 92632 0 131064 EPSG:3857:18 10445 185264 0 262128 EPSG:3857:19 20890 370529 0 524256 EPSG:3857:20 41780 741058 0 1048513 EPSG:3857:21 83561 1482116 0 2097027 EPSG:3857:22 167123 2964232 0 4194054 EPSG:3857:23 334246 5928465 0 8388109 EPSG:3857:24 668493 11856930 0 16776218 EPSG:3857:25 1336986 23713860 0 33552436 EPSG:3857:26 2673973 47427720 0 67104872 EPSG:3857:27 5347946 94855440 0 134209745 EPSG:3857:28 10695893 189710880 0 268419491 EPSG:3857:29 21391787 379421761 0 536838983 EPSG:3857:30 42783574 758843523 0 1073677966 Tropical Cyclone Wind 250 Years Return Period (km/h) The tropical cyclonic strong wind and storm surge hazard model uses information from 2594 historical tropical cyclones besides data on topography, terrain roughness, and bathymetry. The historical tropical cyclones used in the cyclone wind and storm surge hazard model for the GAR Atlas cover the five different oceanic basins: Northeast Pacific, Northwest Pacific, South Pacific, North Indian, South Indian and North Atlantic. In all cases, the data associated to each track were obtained from the IBTrACS database (Knapp et al., 2010). Topography data from the Shuttle Radar Topography Mission (SRTM) of NASA, which provides terrain elevation grids at a 90 meters resolution, delivered by quadrants over the world was used and, additionally, to account for surface roughness, polygons of urban areas worldwide were obtained from the Socioeconomic Data and Applications Centre, SEDAC (CIESIN et al., 2011). A digital bathymetry model, with a spatial resolution of 30 arc-seconds, from the GEBCO_08 (General Bathymetric Chart of the Oceans) Grid Database of the British Oceanographic Data Centre (2009) was used. More information about the cyclone wind and storm surge hazard model can be found in Cardona et al., 2015. Hazard analysis was performed using the software CAPRA Team Tropical Cyclones Hazard Modeler (Bernal, 2014). -180.0 -55.13566066745048 179.9077507461337 59.904585330559826 wesr_risk:cy_hazard_250_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 0 15 EPSG:4326:4 2 12 0 31 EPSG:4326:5 5 25 0 63 EPSG:4326:6 10 51 0 127 EPSG:4326:7 21 103 0 255 EPSG:4326:8 42 206 0 511 EPSG:4326:9 85 412 0 1023 EPSG:4326:10 171 825 0 2047 EPSG:4326:11 342 1651 0 4094 EPSG:4326:12 684 3302 0 8189 EPSG:4326:13 1369 6605 0 16379 EPSG:4326:14 2739 13210 0 32759 EPSG:4326:15 5478 26421 0 65519 EPSG:4326:16 10957 52842 0 131038 EPSG:4326:17 21914 105684 0 262076 EPSG:4326:18 43829 211369 0 524153 EPSG:4326:19 87659 422738 0 1048307 EPSG:4326:20 175318 845476 0 2096614 EPSG:4326:21 350636 1690953 0 4193229 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 Tropical cyclone hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:cy_phex_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Self-calibrating Palmer Drought Severity Index (scPDSI) 1970-1979 (CRU) This layer shows the average values over the 1970 to 1979 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901 to 2018. Original data were subset and processed using QGIS at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> The dataset has been updated each year using newer versions of CRU TS input data, currently to the end of 2018 using a preliminary version of CRU TS 4.03 (0.5° resolution). <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 UN_Sahel:scPDSI.cru_ts403_1970-1979 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Global Emissions CO 2010 - EDGARD -180.0 -77.95 179.95 88.15000000000002 unea_pollution:edg10_co image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 Population Estimates for 2019 GHA Region the data indicates to the estimated total number of people per grid-cell at a resolution of 1 Km. 21.838947 -11.745699999198003 51.4196463067 23.14286 wesr_cca:icpac_worldpop_2019_population_gha image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 6 8 8 10 EPSG:3857:5 13 17 17 20 EPSG:3857:6 27 34 35 41 EPSG:3857:7 55 68 71 82 EPSG:3857:8 111 136 143 164 EPSG:3857:9 222 272 287 329 EPSG:3857:10 444 545 574 658 EPSG:3857:11 888 1091 1148 1316 EPSG:3857:12 1777 2182 2296 2633 EPSG:3857:13 3554 4365 4592 5266 EPSG:3857:14 7108 8730 9185 10532 EPSG:3857:15 14217 17460 18371 21064 EPSG:3857:16 28435 34921 36743 42128 EPSG:3857:17 56871 69842 73487 84257 EPSG:3857:18 113742 139685 146974 168514 EPSG:3857:19 227484 279371 293949 337029 EPSG:3857:20 454968 558742 587898 674058 EPSG:3857:21 909936 1117484 1175797 1348117 EPSG:3857:22 1819872 2234968 2351594 2696234 EPSG:3857:23 3639744 4469936 4703188 5392468 EPSG:3857:24 7279489 8939872 9406376 10784937 EPSG:3857:25 14558978 17879744 18812753 21569874 EPSG:3857:26 29117957 35759488 37625506 43139748 EPSG:3857:27 58235914 71518976 75251013 86279497 EPSG:3857:28 116471828 143037953 150502027 172558995 EPSG:3857:29 232943657 286075907 301004054 345117990 EPSG:3857:30 465887314 572151815 602008108 690235980 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 5 EPSG:4326:3 2 4 8 10 EPSG:4326:4 5 9 17 20 EPSG:4326:5 11 18 35 41 EPSG:4326:6 23 36 71 82 EPSG:4326:7 47 72 143 164 EPSG:4326:8 95 144 287 329 EPSG:4326:9 190 289 574 658 EPSG:4326:10 380 578 1148 1316 EPSG:4326:11 760 1157 2296 2633 EPSG:4326:12 1521 2315 4592 5266 EPSG:4326:13 3042 4630 9185 10532 EPSG:4326:14 6085 9261 18371 21064 EPSG:4326:15 12170 18522 36743 42128 EPSG:4326:16 24341 37044 73487 84257 EPSG:4326:17 48683 74088 146974 168514 EPSG:4326:18 97367 148177 293949 337029 EPSG:4326:19 194735 296355 587898 674058 EPSG:4326:20 389471 592711 1175797 1348117 EPSG:4326:21 778942 1185423 2351594 2696234 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 6 8 8 10 EPSG:3857:5 13 17 17 20 EPSG:3857:6 27 34 35 41 EPSG:3857:7 55 68 71 82 EPSG:3857:8 111 136 143 164 EPSG:3857:9 222 272 287 329 EPSG:3857:10 444 545 574 658 EPSG:3857:11 888 1091 1148 1316 EPSG:3857:12 1777 2182 2296 2633 EPSG:3857:13 3554 4365 4592 5266 EPSG:3857:14 7108 8730 9185 10532 EPSG:3857:15 14217 17460 18371 21064 EPSG:3857:16 28435 34921 36743 42128 EPSG:3857:17 56871 69842 73487 84257 EPSG:3857:18 113742 139685 146974 168514 EPSG:3857:19 227484 279371 293949 337029 EPSG:3857:20 454968 558742 587898 674058 EPSG:3857:21 909936 1117484 1175797 1348117 EPSG:3857:22 1819872 2234968 2351594 2696234 EPSG:3857:23 3639744 4469936 4703188 5392468 EPSG:3857:24 7279489 8939872 9406376 10784937 EPSG:3857:25 14558978 17879744 18812753 21569874 EPSG:3857:26 29117957 35759488 37625506 43139748 EPSG:3857:27 58235914 71518976 75251013 86279497 EPSG:3857:28 116471828 143037953 150502027 172558995 EPSG:3857:29 232943657 286075907 301004054 345117990 EPSG:3857:30 465887314 572151815 602008108 690235980 Temperature (2meters) Anomaly 2020 (1991-2020) This variable is the temperature of air at 2m above the surface of land, sea or in-land waters. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. Credits: https://cds.climate.copernicus.eu/cdsapp#!/dataset/ecv-for-climate-change?tab=overview -179.875 -90.0 180.0 90.0 wesr_climat:12month_anomaly_Global_ea_2t_202001-202012_1991-2020_v02 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 1 4095 EPSG:3857:13 0 8191 2 8191 EPSG:3857:14 0 16383 5 16383 EPSG:3857:15 0 32767 11 32767 EPSG:3857:16 0 65535 22 65535 EPSG:3857:17 0 131071 45 131071 EPSG:3857:18 0 262143 91 262143 EPSG:3857:19 0 524287 182 524287 EPSG:3857:20 0 1048575 364 1048575 EPSG:3857:21 0 2097151 728 2097151 EPSG:3857:22 -1 4194303 1456 4194304 EPSG:3857:23 -1 8388607 2912 8388608 EPSG:3857:24 0 16777215 5825 16777215 EPSG:3857:25 0 33554431 11650 33554431 EPSG:3857:26 0 67108863 23301 67108863 EPSG:3857:27 0 134217727 46603 134217727 EPSG:3857:28 -1 268435455 93206 268435456 EPSG:3857:29 0 536870911 186413 536870911 EPSG:3857:30 0 1073741823 372826 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 255 0 511 EPSG:4326:9 0 511 0 1023 EPSG:4326:10 0 1023 0 2047 EPSG:4326:11 0 2047 1 4095 EPSG:4326:12 0 4095 2 8191 EPSG:4326:13 0 8191 5 16383 EPSG:4326:14 0 16383 11 32767 EPSG:4326:15 0 32767 22 65535 EPSG:4326:16 0 65535 45 131071 EPSG:4326:17 0 131071 91 262143 EPSG:4326:18 0 262143 182 524287 EPSG:4326:19 0 524287 364 1048575 EPSG:4326:20 0 1048575 728 2097151 EPSG:4326:21 0 2097151 1456 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 1 4095 EPSG:3857:13 0 8191 2 8191 EPSG:3857:14 0 16383 5 16383 EPSG:3857:15 0 32767 11 32767 EPSG:3857:16 0 65535 22 65535 EPSG:3857:17 0 131071 45 131071 EPSG:3857:18 0 262143 91 262143 EPSG:3857:19 0 524287 182 524287 EPSG:3857:20 0 1048575 364 1048575 EPSG:3857:21 -1 2097151 728 2097152 EPSG:3857:22 -1 4194303 1456 4194304 EPSG:3857:23 0 8388607 2912 8388607 EPSG:3857:24 0 16777215 5825 16777215 EPSG:3857:25 0 33554431 11650 33554431 EPSG:3857:26 0 67108863 23301 67108863 EPSG:3857:27 -1 134217727 46603 134217728 EPSG:3857:28 0 268435455 93206 268435455 EPSG:3857:29 0 536870911 186413 536870911 EPSG:3857:30 -1 1073741823 372826 1073741824 Physical Exposition To Landslides Triggered By Earthquakes This dataset includes an estimate of the annual physical exposition of landslide triggered by earthquakes. It depends on the combination of trigger and susceptibility defined by six parameters: slope factor, lithological (or geological) conditions, soil moisture condition, vegetation cover, precipitation and seismic conditions. A population grid for the year 2010, provided by LandScanTM Global Population Database (Oak Ridge, TN: Oak Ridge National Laboratory) has also been used. Unit is expected average annual population (2010 as the year of reference) exposed (inhabitants) . This product was designed by International Centre for Geohazards (NGI) for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards (NGI). -180.0 -90.0 180.0 90.0 wesr_risk:le1010ipey image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Economical Exposition To Tsunamis This dataset includes an estimation of the annual economical exposition to tsunamis. It is based on three sources: 1) A comprehensive list of reports and scientific papers compiled and utilized in producing tsunami hazard maps as well as finding return periods of future events. 2) Applying numerical tsunami models and zooming on selected areas. 3) A Global Domestic Product grid for the year 2010, provided by the World Bank. Unit is expected average annual GDP (2010 as the year of reference) exposed in (US $, year 2000 equivalent). This product was designed by International Centre for Geohazards (NGI) for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards (NGI) -180.0 -90.0 179.99999999985602 83.99999999993042 wesr_risk:ts_ecoexp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097151 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388608 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217727 EPSG:3857:28 8240909 268435455 0 268435456 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34952 1048575 0 2097151 EPSG:4326:21 69905 2097151 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097152 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388607 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217728 EPSG:3857:28 8240909 268435455 0 268435455 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741824 Central Congo Basin peatland map (2022, unsmoothed) Metadata for the file: Crezee_2022_Unsmoothed_Classification_Most_likely_class.tif This file is a simplified version of the map presented in Figure 1b of the paper: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This raster file is an unsmoothed version of the landcover classification map. For each pixel, the most likely class is displayed, based on the highest probability obtained from the 5 landcover classes presented in the Crezee_2022_Central_Congo_Peat_Probability_Layers.zip archive. The class values are: 0. No data 1. Open water 2. Savanna 3. Non-peat forming forest (Terra firme and seasonally inundated forest) 4. Palm-dominated peat swamp forest 5. Hardwood-dominated peat swamp forest Only class 4 and 5 are associated with the presence of peat. Total peatland area extent is obtained by summing class 4 and 5 areas. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 15.0 -4.999916949999999 25.72744828 3.30533333 peatlands:Crezee_2022_Unsmoothed_Classification_Most_likely_class_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 8 17 18 EPSG:4326:5 15 16 34 36 EPSG:4326:6 30 33 69 73 EPSG:4326:7 61 67 138 146 EPSG:4326:8 123 135 277 292 EPSG:4326:9 246 270 554 585 EPSG:4326:10 493 540 1109 1170 EPSG:4326:11 986 1080 2218 2340 EPSG:4326:12 1972 2161 4437 4681 EPSG:4326:13 3945 4323 8874 9362 EPSG:4326:14 7891 8647 17749 18725 EPSG:4326:15 15782 17294 35498 37451 EPSG:4326:16 31564 34588 70997 74903 EPSG:4326:17 63129 69176 141994 149806 EPSG:4326:18 126258 138353 283989 299612 EPSG:4326:19 252516 276707 567978 599224 EPSG:4326:20 505033 553414 1135957 1198449 EPSG:4326:21 1010066 1106829 2271914 2396898 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 Annual Precipitation - Anomaly [%] (2041-2060 vs 1979-2013) RCP8.5 - CIMP5 Anomaly [%] for the period 2041-2060 compared to climatological data (1979-2013) on the accumulated precipitation amount over 1 year based on RCP8.5. The layer is calculated at UNEP/GRID-Geneva from the layers on annual precipitation [mm/year] provided in the products CHELSA V1.2 and CHELSA-[CMIP5]. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. 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73291062 108681352 EPSG:3857:29 248738434 299889341 146582125 217362704 EPSG:3857:30 497476869 599778682 293164250 434725408 Forest Structual Condition Index (SCI) - South America The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> -81.70875583396088 -20.582447168229265 -34.24721833519705 13.047396176983916 MapX_UNDP:samericaSCI2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 3 EPSG:3857:4 7 8 4 6 EPSG:3857:5 14 17 8 12 EPSG:3857:6 29 35 17 25 EPSG:3857:7 59 71 34 51 EPSG:3857:8 118 142 69 103 EPSG:3857:9 237 285 139 207 EPSG:3857:10 474 571 279 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288007209 293786849 EPSG:3857:30 528746442 536764299 576014419 587573699 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 7 7 17 17 EPSG:4326:5 15 15 34 35 EPSG:4326:6 31 31 68 70 EPSG:4326:7 62 63 137 140 EPSG:4326:8 124 127 274 280 EPSG:4326:9 248 255 549 560 EPSG:4326:10 496 511 1098 1120 EPSG:4326:11 993 1023 2197 2241 EPSG:4326:12 1986 2047 4394 4482 EPSG:4326:13 3972 4094 8789 8965 EPSG:4326:14 7944 8188 17578 17931 EPSG:4326:15 15888 16377 35157 35862 EPSG:4326:16 31776 32754 70314 71725 EPSG:4326:17 63553 65509 140628 143450 EPSG:4326:18 127106 131019 281257 286901 EPSG:4326:19 254212 262039 562514 573802 EPSG:4326:20 508425 524079 1125028 1147604 EPSG:4326:21 1016851 1048159 2250056 2295209 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 15 15 17 17 EPSG:3857:6 31 31 34 35 EPSG:3857:7 63 63 68 70 EPSG:3857:8 126 127 137 140 EPSG:3857:9 252 255 274 280 EPSG:3857:10 504 511 549 560 EPSG:3857:11 1008 1023 1098 1120 EPSG:3857:12 2017 2047 2197 2241 EPSG:3857:13 4034 4095 4394 4482 EPSG:3857:14 8068 8190 8789 8965 EPSG:3857:15 16136 16380 17578 17931 EPSG:3857:16 32272 32761 35157 35862 EPSG:3857:17 64544 65522 70314 71725 EPSG:3857:18 129088 131045 140628 143450 EPSG:3857:19 258176 262091 281257 286901 EPSG:3857:20 516353 524183 562514 573802 EPSG:3857:21 1032707 1048367 1125028 1147604 EPSG:3857:22 2065415 2096735 2250056 2295209 EPSG:3857:23 4130831 4193471 4500112 4590419 EPSG:3857:24 8261663 8386942 9000225 9180839 EPSG:3857:25 16523326 16773884 18000450 18361678 EPSG:3857:26 33046652 33547768 36000901 36723356 EPSG:3857:27 66093305 67095537 72001802 73446712 EPSG:3857:28 132186610 134191074 144003604 146893424 EPSG:3857:29 264373221 268382149 288007209 293786849 EPSG:3857:30 528746442 536764299 576014419 587573699 Self-calibrating Palmer Drought Severity Index (scPDSI) 2017 (CRU) This layer shows the average values for 2017 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_17_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Crop Suitability Change 1981-2100 This dataset show general agricultural suitability at a spatial resolution of 30 arc-second (~1km), considering rainfed conditions and irrigation on currently irrigated areas. The agricultural suitability represents for each pixel the maximum suitability value of considered 16 plants, including: We show a subset of the data that covers three time periods (1981-2010, 2011-2040, 2071-2100), as well as changes in agricultural suitability over the same periods.<br><br>For futher details see: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107522">Zabel F., Putzenlechner B., Mauser W. (2014): Global agricultural land resources – a high resolution suitability evaluation and its perspectives until 2100 under climate change conditions</a><br/><br>Data can also be downloaded from <a href="http://geoportal-glues.ufz.de/stories/globalsuitability.html">here</a>.<br/> -180.0 -60.0 180.0 90.0 MapX_UNDP:overall_cropsuit_i_diff_19812010_20712100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 CobVeg_180615 Layer provided by Ministry of Environment of Peru. The following link has information on the methodology used to produce the national land use cover map. https://www.minam.gob.pe/patrimonio-natural/wp-content/uploads/sites/6/2013/10/MAPA-NACIONAL-DE-COBERTURA-VEGETAL-FINAL.compressed.pdf SDG Goal 15. Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss. -81.64209769673542 -18.40713299058302 -68.47323079023445 -0.038370914474849416 wesr_cca:CobVeg_180615 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 0 0 EPSG:3857:2 2 2 1 1 EPSG:3857:3 4 4 2 2 EPSG:3857:4 8 8 4 4 EPSG:3857:5 16 17 8 9 EPSG:3857:6 32 35 17 19 EPSG:3857:7 64 70 34 39 EPSG:3857:8 128 141 69 79 EPSG:3857:9 256 282 139 158 EPSG:3857:10 512 565 279 317 EPSG:3857:11 1024 1130 559 634 EPSG:3857:12 2048 2261 1119 1268 EPSG:3857:13 4096 4522 2238 2537 EPSG:3857:14 8193 9044 4476 5075 EPSG:3857:15 16387 18089 8952 10151 EPSG:3857:16 32774 36178 17905 20302 EPSG:3857:17 65549 72356 35811 40605 EPSG:3857:18 131099 144712 71622 81211 EPSG:3857:19 262199 289424 143244 162422 EPSG:3857:20 524399 578849 286488 324845 EPSG:3857:21 1048799 1157698 572976 649690 EPSG:3857:22 2097599 2315397 1145952 1299381 EPSG:3857:23 4195198 4630795 2291905 2598762 EPSG:3857:24 8390396 9261591 4583810 5197524 EPSG:3857:25 16780792 18523182 9167620 10395048 EPSG:3857:26 33561584 37046365 18335241 20790096 EPSG:3857:27 67123169 74092731 36670483 41580193 EPSG:3857:28 134246339 148185463 73340967 83160386 EPSG:3857:29 268492678 296370927 146681935 166320773 EPSG:3857:30 536985357 592741855 293363870 332641546 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 1 1 1 1 EPSG:4326:2 2 2 2 2 EPSG:4326:3 4 4 4 4 EPSG:4326:4 8 9 8 9 EPSG:4326:5 16 19 17 19 EPSG:4326:6 32 38 34 39 EPSG:4326:7 64 77 69 79 EPSG:4326:8 128 154 139 158 EPSG:4326:9 256 308 279 317 EPSG:4326:10 512 616 559 634 EPSG:4326:11 1024 1233 1119 1268 EPSG:4326:12 2048 2466 2238 2537 EPSG:4326:13 4097 4933 4476 5075 EPSG:4326:14 8195 9867 8952 10151 EPSG:4326:15 16390 19734 17905 20302 EPSG:4326:16 32781 39469 35811 40605 EPSG:4326:17 65563 78939 71622 81211 EPSG:4326:18 131127 157879 143244 162422 EPSG:4326:19 262255 315758 286488 324845 EPSG:4326:20 524511 631517 572976 649690 EPSG:4326:21 1049023 1263034 1145952 1299381 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 0 0 EPSG:3857:2 2 2 1 1 EPSG:3857:3 4 4 2 2 EPSG:3857:4 8 8 4 4 EPSG:3857:5 16 17 8 9 EPSG:3857:6 32 35 17 19 EPSG:3857:7 64 70 34 39 EPSG:3857:8 128 141 69 79 EPSG:3857:9 256 282 139 158 EPSG:3857:10 512 565 279 317 EPSG:3857:11 1024 1130 559 634 EPSG:3857:12 2048 2261 1119 1268 EPSG:3857:13 4096 4522 2238 2537 EPSG:3857:14 8193 9044 4476 5075 EPSG:3857:15 16387 18089 8952 10151 EPSG:3857:16 32774 36178 17905 20302 EPSG:3857:17 65549 72356 35811 40605 EPSG:3857:18 131099 144712 71622 81211 EPSG:3857:19 262199 289424 143244 162422 EPSG:3857:20 524399 578849 286488 324845 EPSG:3857:21 1048799 1157698 572976 649690 EPSG:3857:22 2097599 2315397 1145952 1299381 EPSG:3857:23 4195198 4630795 2291905 2598762 EPSG:3857:24 8390396 9261591 4583810 5197524 EPSG:3857:25 16780792 18523182 9167620 10395048 EPSG:3857:26 33561584 37046365 18335241 20790096 EPSG:3857:27 67123169 74092731 36670483 41580193 EPSG:3857:28 134246339 148185463 73340967 83160386 EPSG:3857:29 268492678 296370927 146681935 166320773 EPSG:3857:30 536985357 592741855 293363870 332641546 Tsunami hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:ts_phex image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Yearly emissions of N2O - 2010 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -90.0 180.0 90.0 wesr_climat:v60_N2O_2010_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_mambo_bado_20191227 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20191227 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 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272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Opened forest total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:forestofkm2a image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average year precipitations anomalies (2001-2010) over 1991-2020 climatology Average year precipitations anomalies in mm across the period 2001-2010 calculated over the average precipitations per year in the period 1991-2020 (climatology). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_01_10_anom9120 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone surge/ Mangroves at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_man6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 sld_cookbook_raster -180.0 -90.0 180.0 90.0 MAPX:sld_cookbook_raster image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 World Ecosystem Data - World Climate Regions Data Data modified for visualisation purpose from the original: World Climate Regions Data in World Ecosystem Data. Originally downloded from https://esri.maps.arcgis.com/home/item.html?id=3bfa1aa4cd9844d5a0922540210da25b Sayre et al. 2020. An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems - Global Ecology and Conservation. More information at: https://www.sciencedirect.com/science/article/pii/S2351989419307231?via%3Dihub Data reclassified based on the following schema: Existing classes from "Temp_Moist" -> New classes Boreal Desert, Boreal Dry, Boreal Moist, Polar Desert, Polar Dry, Polar Moist -> Boreal/Polar Cool Temperate Moist -> Cool Temperate Moist Cool Temperate Dry and Desert -> Cool Temperate Dry & Desert Warm Temperate Moist -> Warm Temperate Moist Warm Temperate Moist, Warm Temperate Desert -> Warm Temperate Dry & Desert Tropical Desert, Sub Tropical Desert -> Tropical & Sub Tropical Desert Tropical Dry, Sub Tropical Dry -> Tropical & Sub Tropical Dry Tropical Moist, Sub Tropical Moist -> Tropical & Sub Tropical Moist -179.999999 -55.99953000000001 179.999334901 83.624039629 NEAT_plus:WE_reclass_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 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552 EPSG:3857:11 1035 1047 1096 1105 EPSG:3857:12 2071 2094 2193 2211 EPSG:3857:13 4143 4188 4387 4422 EPSG:3857:14 8287 8376 8774 8845 EPSG:3857:15 16574 16753 17548 17690 EPSG:3857:16 33148 33506 35097 35380 EPSG:3857:17 66296 67012 70194 70760 EPSG:3857:18 132592 134025 140389 141521 EPSG:3857:19 265185 268051 280779 283043 EPSG:3857:20 530371 536102 561559 566087 EPSG:3857:21 1060742 1072205 1123118 1132175 EPSG:3857:22 2121484 2144410 2246236 2264351 EPSG:3857:23 4242968 4288821 4492473 4528702 EPSG:3857:24 8485937 8577642 8984947 9057404 EPSG:3857:25 16971875 17155284 17969895 18114809 EPSG:3857:26 33943750 34310568 35939790 36229618 EPSG:3857:27 67887500 68621137 71879580 72459237 EPSG:3857:28 135775000 137242275 143759161 144918474 EPSG:3857:29 271550000 274484551 287518322 289836949 EPSG:3857:30 543100001 548969102 575036644 579673899 Urban Assets -179.13 -53.1674 178.443 70.9927 wesr_risk:urban_assets image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 3 10 0 15 EPSG:3857:5 6 21 0 31 EPSG:3857:6 13 43 0 63 EPSG:3857:7 27 86 0 127 EPSG:3857:8 55 172 0 254 EPSG:3857:9 110 345 1 509 EPSG:3857:10 220 691 2 1019 EPSG:3857:11 441 1382 4 2039 EPSG:3857:12 882 2764 9 4078 EPSG:3857:13 1765 5529 19 8156 EPSG:3857:14 3531 11059 39 16313 EPSG:3857:15 7062 22119 79 32626 EPSG:3857:16 14125 44238 158 65252 EPSG:3857:17 28251 88476 316 130505 EPSG:3857:18 56502 176953 633 261010 EPSG:3857:19 113004 353906 1267 522020 EPSG:3857:20 226009 707812 2534 1044040 EPSG:3857:21 452018 1415624 5068 2088081 EPSG:3857:22 904036 2831248 10136 4176163 EPSG:3857:23 1808072 5662497 20272 8352327 EPSG:3857:24 3616145 11324995 40544 16704654 EPSG:3857:25 7232291 22649990 81089 33409309 EPSG:3857:26 14464582 45299981 162179 66818618 EPSG:3857:27 28929164 90599962 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EPSG:3857:7 27 86 0 127 EPSG:3857:8 55 172 0 254 EPSG:3857:9 110 345 1 509 EPSG:3857:10 220 691 2 1019 EPSG:3857:11 441 1382 4 2039 EPSG:3857:12 882 2764 9 4078 EPSG:3857:13 1765 5529 19 8156 EPSG:3857:14 3531 11059 39 16313 EPSG:3857:15 7062 22119 79 32626 EPSG:3857:16 14125 44238 158 65252 EPSG:3857:17 28251 88476 316 130505 EPSG:3857:18 56502 176953 633 261010 EPSG:3857:19 113004 353906 1267 522020 EPSG:3857:20 226009 707812 2534 1044040 EPSG:3857:21 452018 1415624 5068 2088081 EPSG:3857:22 904036 2831248 10136 4176163 EPSG:3857:23 1808072 5662497 20272 8352327 EPSG:3857:24 3616145 11324995 40544 16704654 EPSG:3857:25 7232291 22649990 81089 33409309 EPSG:3857:26 14464582 45299981 162179 66818618 EPSG:3857:27 28929164 90599962 324359 133637236 EPSG:3857:28 57858328 181199925 648719 267274472 EPSG:3857:29 115716656 362399851 1297438 534548945 EPSG:3857:30 231433312 724799703 2594876 1069097890 World Database of Key Biodiversity Areas (KBA) Key Biodiversity Areas (KBA) are 'sites contributing significantly to the global persistence of biodiversity’, in terrestrial, freshwater and marine ecosystems. <br> The Global Standard for the Identification of Key Biodiversity Areas (IUCN 2016) sets out globally agreed criteria for the identification of KBAs worldwide. The KBA Standard establishes a consultative, science-based process for KBA identification, founded on the consistent application of global criteria with quantitative thresholds that have been developed through an extensive consultation exercise spanning several years. The Standard is also available in French and Spanish. <br> Sites qualify as global KBAs if they meet one or more of 11 criteria, clustered into five categories: threatened biodiversity; geographically restricted biodiversity; ecological integrity; biological processes; and, irreplaceability. The KBA criteria can be applied to species and ecosystems in terrestrial, inland water and marine environments. Although not all KBA criteria may be relevant to all elements of biodiversity, the thresholds associated with each of the criteria may be applied across all taxonomic groups (other than micro-organisms) and ecosystems. <br> The KBA identification process is a highly inclusive, consultative and bottom-up exercise. Although anyone with appropriate scientific data may propose a site to qualify as a KBA, consultation with stakeholders at the national level (both non-governmental and governmental organizations) is required during the proposal process. KBA identification should build off the existing network of KBAs (including Important Bird and Biodiversity Areas and Alliance for Zero Extinction sites) and new data should seek to strengthen and expand the network of these sites. Any site proposal must undergo independent scientific review. This is followed by the official site nomination with full documentation meeting the Documentation Standards for KBAs. Sites confirmed by the KBA Secretariat to qualify as KBAs then appear on this website. <br> The consultation process to develop A Global Standard for the Identification of Key Biodiversity Areas was led by the IUCN WCPA-SSC Joint Task Force on Biodiversity and Protected Areas. It involved a Framing workshop; technical workshops on Criteria and Delineation, quantitative Thresholds, and Governance of the process to identify KBAs; a second Governance meeting; 14 separate regional consultations held around the world; and interviews with end users of KBA data. A first public consultation draft was posted in 2014, generating more than 1200 comments and responses. The second consultation draft on the Standard was posted in 2015, generating an additional 600 comments and responses. More information on the consultation process to develop the KBA Standard can be found on the Joint Task Force website. -180.0 -90.0 180.0 90.0 MapX_UNDP_nd:KBA_masked_v1 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burnt areas in Kedougou between 1995 and 2004 Forest fire hazard assessment is based on a retrospective analysis of burnt areas, using satellite data from different time periods. The methodology uses the Normalized Burn Ratio (NBR) index, calculated from the near-infrared (NIR) and short-wave infrared (SWIR) spectral bands of the Landsat. -13.238921499711449 12.308356696892037 -11.345452543844322 13.463410489212919 risk_southeast_senegal:burn_1995_2004 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30702 EPSG:3857:17 60588 61019 60715 61405 EPSG:3857:18 121176 122039 121431 122810 EPSG:3857:19 242353 244079 242863 245620 EPSG:3857:20 484707 488158 485726 491241 EPSG:3857:21 969414 976316 971453 982483 EPSG:3857:22 1938828 1952633 1942907 1964967 EPSG:3857:23 3877656 3905266 3885814 3929935 EPSG:3857:24 7755312 7810533 7771629 7859871 EPSG:3857:25 15510624 15621067 15543259 15719743 EPSG:3857:26 31021249 31242134 31086518 31439486 EPSG:3857:27 62042499 62484268 62173036 62878972 EPSG:3857:28 124084999 124968536 124346072 125757945 EPSG:3857:29 248169998 249937073 248692145 251515890 EPSG:3857:30 496339997 499874147 497384290 503031781 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30702 EPSG:4326:16 27866 28286 60715 61405 EPSG:4326:17 55732 56573 121431 122810 EPSG:4326:18 111464 113146 242863 245620 EPSG:4326:19 222928 226293 485726 491241 EPSG:4326:20 445857 452586 971453 982483 EPSG:4326:21 891715 905173 1942907 1964967 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30702 EPSG:3857:17 60588 61019 60715 61405 EPSG:3857:18 121176 122039 121431 122810 EPSG:3857:19 242353 244079 242863 245620 EPSG:3857:20 484707 488158 485726 491241 EPSG:3857:21 969414 976316 971453 982483 EPSG:3857:22 1938828 1952633 1942907 1964967 EPSG:3857:23 3877656 3905266 3885814 3929935 EPSG:3857:24 7755312 7810533 7771629 7859871 EPSG:3857:25 15510624 15621067 15543259 15719743 EPSG:3857:26 31021249 31242134 31086518 31439486 EPSG:3857:27 62042499 62484268 62173036 62878972 EPSG:3857:28 124084999 124968536 124346072 125757945 EPSG:3857:29 248169998 249937073 248692145 251515890 EPSG:3857:30 496339997 499874147 497384290 503031781 Tropical Cyclone Wind 50 Years Return Period (km/h) The tropical cyclonic strong wind and storm surge hazard model uses information from 2594 historical tropical cyclones besides data on topography, terrain roughness, and bathymetry. The historical tropical cyclones used in the cyclone wind and storm surge hazard model for the GAR Atlas cover the five different oceanic basins: Northeast Pacific, Northwest Pacific, South Pacific, North Indian, South Indian and North Atlantic. In all cases, the data associated to each track were obtained from the IBTrACS database (Knapp et al., 2010). Topography data from the Shuttle Radar Topography Mission (SRTM) of NASA, which provides terrain elevation grids at a 90 meters resolution, delivered by quadrants over the world was used and, additionally, to account for surface roughness, polygons of urban areas worldwide were obtained from the Socioeconomic Data and Applications Centre, SEDAC (CIESIN et al., 2011). A digital bathymetry model, with a spatial resolution of 30 arc-seconds, from the GEBCO_08 (General Bathymetric Chart of the Oceans) Grid Database of the British Oceanographic Data Centre (2009) was used. More information about the cyclone wind and storm surge hazard model can be found in Cardona et al., 2015. Hazard analysis was performed using the software CAPRA Team Tropical Cyclones Hazard Modeler (Bernal, 2014). -180.0 -55.13566066745048 179.9077507461337 59.904585330559826 wesr_risk:cy_hazard_50_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 0 15 EPSG:4326:4 2 12 0 31 EPSG:4326:5 5 25 0 63 EPSG:4326:6 10 51 0 127 EPSG:4326:7 21 103 0 255 EPSG:4326:8 42 206 0 511 EPSG:4326:9 85 412 0 1023 EPSG:4326:10 171 825 0 2047 EPSG:4326:11 342 1651 0 4094 EPSG:4326:12 684 3302 0 8189 EPSG:4326:13 1369 6605 0 16379 EPSG:4326:14 2739 13210 0 32759 EPSG:4326:15 5478 26421 0 65519 EPSG:4326:16 10957 52842 0 131038 EPSG:4326:17 21914 105684 0 262076 EPSG:4326:18 43829 211369 0 524153 EPSG:4326:19 87659 422738 0 1048307 EPSG:4326:20 175318 845476 0 2096614 EPSG:4326:21 350636 1690953 0 4193229 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 Satellite Mogadisho Urban Growth 2016 Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2016-02-14. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov. 45.195394649846214 1.955229029551538 45.47923060483454 2.141476613353127 MAPX:Mogadisho_Landsat7_20160214-531 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 10 10 EPSG:3857:5 15 15 20 20 EPSG:3857:6 31 31 40 40 EPSG:3857:7 63 63 80 80 EPSG:3857:8 126 126 160 160 EPSG:3857:9 252 253 320 320 EPSG:3857:10 505 506 640 641 EPSG:3857:11 1011 1012 1281 1282 EPSG:3857:12 2023 2025 2562 2565 EPSG:3857:13 4047 4051 5124 5130 EPSG:3857:14 8094 8102 10248 10261 EPSG:3857:15 16189 16205 20497 20523 EPSG:3857:16 32378 32411 40995 41047 EPSG:3857:17 64756 64823 81991 82094 EPSG:3857:18 129512 129647 163982 164188 EPSG:3857:19 259024 259295 327964 328377 EPSG:3857:20 518049 518591 655929 656755 EPSG:3857:21 1036098 1037183 1311858 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EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 Self-calibrating Palmer Drought Severity Index (scPDSI) 2020 (CRU) This layer shows the average values for 2020 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_20_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from Canadian Centre for Climate Modelling and Analysis, CGCM3.1 Model, T47 resolution Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_cccma_cgcm3_1_5km_2041-2060_debiasedmean_tas_av_12month_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Yearly emissions of CO2 (short cycle organic Carbon) - 1970 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -55.699999999992485 179.99999999997954 76.5 wesr_climat:v60_CO2_org_short-cycle_C_1970_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 10 0 15 EPSG:3857:5 5 21 0 31 EPSG:3857:6 10 43 0 63 EPSG:3857:7 20 87 0 127 EPSG:3857:8 41 175 0 255 EPSG:3857:9 82 351 0 511 EPSG:3857:10 164 703 0 1023 EPSG:3857:11 328 1407 0 2047 EPSG:3857:12 656 2814 0 4095 EPSG:3857:13 1313 5628 0 8191 EPSG:3857:14 2627 11257 0 16383 EPSG:3857:15 5254 22515 0 32767 EPSG:3857:16 10509 45031 0 65535 EPSG:3857:17 21018 90062 0 131071 EPSG:3857:18 42036 180124 0 262143 EPSG:3857:19 84072 360249 0 524287 EPSG:3857:20 168145 720499 0 1048575 EPSG:3857:21 336291 1440999 0 2097151 EPSG:3857:22 672583 2881999 0 4194304 EPSG:3857:23 1345167 5763998 0 8388608 EPSG:3857:24 2690335 11527997 0 16777215 EPSG:3857:25 5380671 23055994 0 33554431 EPSG:3857:26 10761342 46111988 0 67108863 EPSG:3857:27 21522685 92223977 0 134217727 EPSG:3857:28 43045370 184447955 0 268435456 EPSG:3857:29 86090740 368895911 0 536870911 EPSG:3857:30 172181481 737791822 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 0 31 EPSG:4326:5 2 25 0 63 EPSG:4326:6 4 51 0 127 EPSG:4326:7 9 103 0 255 EPSG:4326:8 19 207 0 511 EPSG:4326:9 38 414 0 1023 EPSG:4326:10 76 828 0 2047 EPSG:4326:11 153 1657 0 4095 EPSG:4326:12 307 3315 0 8191 EPSG:4326:13 614 6630 0 16383 EPSG:4326:14 1228 13261 0 32767 EPSG:4326:15 2457 26523 0 65535 EPSG:4326:16 4915 53047 0 131071 EPSG:4326:17 9830 106095 0 262143 EPSG:4326:18 19660 212191 0 524287 EPSG:4326:19 39321 424382 0 1048575 EPSG:4326:20 78643 848764 0 2097151 EPSG:4326:21 157286 1697528 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 10 0 15 EPSG:3857:5 5 21 0 31 EPSG:3857:6 10 43 0 63 EPSG:3857:7 20 87 0 127 EPSG:3857:8 41 175 0 255 EPSG:3857:9 82 351 0 511 EPSG:3857:10 164 703 0 1023 EPSG:3857:11 328 1407 0 2047 EPSG:3857:12 656 2814 0 4095 EPSG:3857:13 1313 5628 0 8191 EPSG:3857:14 2627 11257 0 16383 EPSG:3857:15 5254 22515 0 32767 EPSG:3857:16 10509 45031 0 65535 EPSG:3857:17 21018 90062 0 131071 EPSG:3857:18 42036 180124 0 262143 EPSG:3857:19 84072 360249 0 524287 EPSG:3857:20 168145 720499 0 1048575 EPSG:3857:21 336291 1440999 0 2097152 EPSG:3857:22 672583 2881999 0 4194304 EPSG:3857:23 1345167 5763998 0 8388607 EPSG:3857:24 2690335 11527997 0 16777215 EPSG:3857:25 5380671 23055994 0 33554431 EPSG:3857:26 10761342 46111988 0 67108863 EPSG:3857:27 21522685 92223977 0 134217728 EPSG:3857:28 43045370 184447955 0 268435455 EPSG:3857:29 86090740 368895911 0 536870911 EPSG:3857:30 172181481 737791822 0 1073741824 Tropical Cyclones Population Exposure This dataset includes an estimation of the annual physical exposition to tropical cyclones of Saffir-Simpson category 5. It is based on three sources: 1) IBTrACS v02r01 (1969 - 2008, http://www.ncdc.noaa.gov/oa/ibtracs/), year 2009 completed by online data from JMA, JTWC, UNISYS, Meteo France and data sent by Alan Sharp from the Australian Bureau of Meteorology. 2) A GIS modeling based on an initial equation from Greg Holland, which was further modified to take into consideration the movement of the cyclones through time. 3) A population grid for the year 2010, provided by LandScanTM Global Population Database (Oak Ridge, TN: Oak Ridge National Laboratory). Unit is expected average annual population (2010 as the year of reference) exposed (inhabitants). This product was designed by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: Raw data: IBTrACS, compilation and GIS processing UNEP/GRID-Geneva. -180.0 -90.0 179.99999999985602 83.99999999993042 wesr_risk:cy_physexp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097151 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388608 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217727 EPSG:3857:28 8240909 268435455 0 268435456 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34952 1048575 0 2097151 EPSG:4326:21 69905 2097151 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097152 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388607 EPSG:3857:24 515056 16777215 0 16777215 EPSG:3857:25 1030113 33554431 0 33554431 EPSG:3857:26 2060227 67108863 0 67108863 EPSG:3857:27 4120454 134217727 0 134217728 EPSG:3857:28 8240909 268435455 0 268435455 EPSG:3857:29 16481819 536870911 0 536870911 EPSG:3857:30 32963639 1073741823 0 1073741824 Bare Ground Change 1982 - 2016 This analysis of 35 years’ worth of satellite data (at approximately 25 square kilometer resolution at the equator) provides a comprehensive record of global land-change dynamics during the period 1982–2016. Contrary to the prevailing view that forest area has declined globally — tree cover has increased by 2.24 million km2 (+7.1% relative to the 1982 level), largely the result of a net loss in the tropics being outweighed by a net gain in the extratropics. Global bare ground cover has decreased by 1.16 million km2 (−3.1%), most notably in agricultural regions in Asia. Of all land changes, 60% are associated with direct human activities and 40% with indirect drivers such as climate change. Land-use change exhibits regional dominance, including tropical deforestation and agricultural expansion, temperate reforestation or afforestation, cropland intensification and urbanization. Consistently across all climate domains, montane systems have gained tree cover and many arid and semi-arid ecosystems have lost vegetation cover.<br><br>For full details see: <a href="https://doi.org/10.1038/s41586-018-0411-9">Song, X.-P., Hansen, M.C., Stehman, S.V., Potapov, P.V., Tyukavina, A., Vermote, E.F., Townshend, J.R., 2018. Global land change from 1982 to 2016. Nature 1</a><br/>. -180.0 -90.0 180.0 90.0 MapX_UNDP:Bare_ground_change_1982-2016 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 TZA_kilombero_sequest_fut_BAUwc 34.553167266769464 -10.038048450490551 37.239835341004294 -7.663994368030097 TEEB:sequest_fut_BAUwc_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 19 19 EPSG:4326:5 17 17 38 38 EPSG:4326:6 34 35 76 77 EPSG:4326:7 69 71 152 154 EPSG:4326:8 138 142 305 308 EPSG:4326:9 277 284 610 617 EPSG:4326:10 555 569 1220 1235 EPSG:4326:11 1111 1138 2441 2471 EPSG:4326:12 2222 2276 4882 4943 EPSG:4326:13 4444 4552 9764 9886 EPSG:4326:14 8889 9105 19529 19773 EPSG:4326:15 17779 18211 39058 39547 EPSG:4326:16 35558 36422 78116 79094 EPSG:4326:17 71116 72845 156232 158189 EPSG:4326:18 142233 145690 312465 316378 EPSG:4326:19 284467 291381 624931 632756 EPSG:4326:20 568934 582763 1249862 1265513 EPSG:4326:21 1137868 1165527 2499725 2531027 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 19 19 EPSG:3857:6 33 33 38 38 EPSG:3857:7 66 67 76 77 EPSG:3857:8 133 135 152 154 EPSG:3857:9 266 270 305 308 EPSG:3857:10 533 540 610 617 EPSG:3857:11 1067 1081 1220 1235 EPSG:3857:12 2135 2162 2441 2471 EPSG:3857:13 4270 4325 4882 4943 EPSG:3857:14 8541 8651 9764 9886 EPSG:3857:15 17083 17302 19529 19773 EPSG:3857:16 34167 34604 39058 39547 EPSG:3857:17 68334 69209 78116 79094 EPSG:3857:18 136669 138419 156232 158189 EPSG:3857:19 273338 276838 312465 316378 EPSG:3857:20 546677 553676 624931 632756 EPSG:3857:21 1093355 1107353 1249862 1265513 EPSG:3857:22 2186711 2214706 2499725 2531027 EPSG:3857:23 4373422 4429413 4999451 5062055 EPSG:3857:24 8746845 8858826 9998902 10124110 EPSG:3857:25 17493691 17717653 19997804 20248220 EPSG:3857:26 34987383 35435306 39995609 40496440 EPSG:3857:27 69974767 70870613 79991218 80992880 EPSG:3857:28 139949534 141741226 159982436 161985761 EPSG:3857:29 279899068 283482452 319964873 323971523 EPSG:3857:30 559798137 566964904 639929747 647943047 Self-calibrating Palmer Drought Severity Index (scPDSI) 1980-1989 (CRU) This layer shows the average values over the 1980 to 1989 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901 to 2018. Original data were subset and processed using QGIS at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> The dataset has been updated each year using newer versions of CRU TS input data, currently to the end of 2018 using a preliminary version of CRU TS 4.03 (0.5° resolution). <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 UN_Sahel:scPDSI.cru_ts403_1980-1989 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Historical Generalized Difference Vegetation Index of emerging Northwest Mining Region of Ghana (2019) The Generalized Normalised Difference Vegetation Index (GNDVI) is a modification of the Normalised Difference Vegetation Index (NDVI), which has been proposed by Weicheng Wu (2014) for the assessment of dryland environments due to the inadequacy of the NDVI in these areas. The Generalised Normalised Difference Vegetation Index (GNDVI) 2019 highlights the effects of the Government of Ghana's fight against illegal mining on vegetation and 'blue mining'. These data can be used to monitor the health of vegetation before and after the fight against galamsey. Further, the data can be used to assess the success or failure of the combat against dessertation initiative of the government of Ghana in the Northwest region as against its approval for large-scale industrial mining in the same area -2.941804951 9.626453977 -1.42736896 11.030613419 MAPX:GHA_GNDVI2019 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1828 4029 4063 EPSG:4326:13 3593 3657 8058 8127 EPSG:4326:14 7187 7315 16116 16254 EPSG:4326:15 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2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 GHA_Stream_Order -2.942754639 9.62256316 -1.420219031 11.034631553 MAPX:GHA_Stream_Order image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30746 31007 32232 32509 EPSG:3857:17 61493 62015 64464 65018 EPSG:3857:18 122986 124031 128929 130037 EPSG:3857:19 245973 248063 257858 260075 EPSG:3857:20 491946 496127 515716 520151 EPSG:3857:21 983893 992255 1031433 1040302 EPSG:3857:22 1967787 1984510 2062866 2080605 EPSG:3857:23 3935574 3969020 4125732 4161210 EPSG:3857:24 7871148 7938040 8251465 8322420 EPSG:3857:25 15742296 15876081 16502931 16644841 EPSG:3857:26 31484592 31752163 33005862 33289683 EPSG:3857:27 62969184 63504327 66011725 66579367 EPSG:3857:28 125938369 127008655 132023451 133158735 EPSG:3857:29 251876738 254017310 264046902 266317471 EPSG:3857:30 503753476 508034621 528093804 532634943 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1829 4029 4063 EPSG:4326:13 3593 3658 8058 8127 EPSG:4326:14 7187 7316 16116 16254 EPSG:4326:15 14375 14632 32232 32509 EPSG:4326:16 28750 29264 64464 65018 EPSG:4326:17 57500 58529 128929 130037 EPSG:4326:18 115001 117058 257858 260075 EPSG:4326:19 230003 234116 515716 520151 EPSG:4326:20 460006 468232 1031433 1040302 EPSG:4326:21 920013 936465 2062866 2080605 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30746 31007 32232 32509 EPSG:3857:17 61493 62015 64464 65018 EPSG:3857:18 122986 124031 128929 130037 EPSG:3857:19 245973 248063 257858 260075 EPSG:3857:20 491946 496127 515716 520151 EPSG:3857:21 983893 992255 1031433 1040302 EPSG:3857:22 1967787 1984510 2062866 2080605 EPSG:3857:23 3935574 3969020 4125732 4161210 EPSG:3857:24 7871148 7938040 8251465 8322420 EPSG:3857:25 15742296 15876081 16502931 16644841 EPSG:3857:26 31484592 31752163 33005862 33289683 EPSG:3857:27 62969184 63504327 66011725 66579367 EPSG:3857:28 125938369 127008655 132023451 133158735 EPSG:3857:29 251876738 254017310 264046902 266317471 EPSG:3857:30 503753476 508034621 528093804 532634943 Global Terrestrial Human Footprint (HFP) - 2013 (subset) This update to the Human Footprint (HFP) provides a measure of the direct and indirect human pressures on the environment globally in years 2000, 2005, 2010, and 2013. Per the orinal Human Footprint, this dataset is derived from remotely-sensed and bottom-up survey information compiled on eight measured variables. This represents not only the most current information of its type, but also the first temporally-consistent set of Human Footprint maps. Data on human pressures were acquired or developed for: 1) built environments, 2) population density, 3) electric infrastructure, 4) crop lands, 5) pasture lands, 6) roads, 7) railways, and 8) navigable waterways. This update incorporates updated and higher resolution population, nightlights, pasture, road, and railway input datasets. The Human Footprint maps find a range of uses as proxies for human disturbance of natural systems and can provide an increased understanding of the human pressures that drive macro-ecological patterns, as well as for tracking environmental change and informing conservation science and application. HFP values range from 0 (no human impact) to 50 (heavily human impacted).<br><br>See: <a href="https://www.nature.com/articles/ncomms12558" target="_blank">Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11</a>.<br/><br>This dataset can be downloaded uniquly from UN Biodiversity Lab. <br> Updated data is made available only to FIP pilot countires at present - rasters are clipped to other FIP data extents. -81.71613729134685 -20.618092964606667 153.42326553667291 26.043388408099844 MapX_UNDP:hfp2013_merisINT_subsetsGlobal image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27854 36605 17892 60697 EPSG:3857:17 55709 73210 35784 121395 EPSG:3857:18 111418 146420 71568 242791 EPSG:3857:19 222837 292841 143136 485582 EPSG:3857:20 445675 585682 286272 971165 EPSG:3857:21 891350 1171364 572544 1942331 EPSG:3857:22 1782701 2342729 1145089 3884662 EPSG:3857:23 3565403 4685458 2290179 7769325 EPSG:3857:24 7130806 9370916 4580359 15538650 EPSG:3857:25 14261613 18741832 9160719 31077300 EPSG:3857:26 28523227 37483665 18321439 62154601 EPSG:3857:27 57046454 74967331 36642879 124309203 EPSG:3857:28 114092909 149934663 73285759 248618406 EPSG:3857:29 228185818 299869326 146571519 497236812 EPSG:3857:30 456371636 599738652 293143038 994473625 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 90 157 139 474 EPSG:4326:9 181 314 279 948 EPSG:4326:10 363 629 559 1896 EPSG:4326:11 727 1258 1118 3793 EPSG:4326:12 1455 2517 2236 7587 EPSG:4326:13 2910 5034 4473 15174 EPSG:4326:14 5821 10068 8946 30348 EPSG:4326:15 11642 20137 17892 60697 EPSG:4326:16 23285 40274 35784 121395 EPSG:4326:17 46571 80549 71568 242791 EPSG:4326:18 93143 161099 143136 485582 EPSG:4326:19 186287 322198 286272 971165 EPSG:4326:20 372574 644397 572544 1942331 EPSG:4326:21 745148 1288794 1145089 3884662 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27854 36605 17892 60697 EPSG:3857:17 55709 73210 35784 121395 EPSG:3857:18 111418 146420 71568 242791 EPSG:3857:19 222837 292841 143136 485582 EPSG:3857:20 445675 585682 286272 971165 EPSG:3857:21 891350 1171364 572544 1942331 EPSG:3857:22 1782701 2342729 1145089 3884662 EPSG:3857:23 3565403 4685458 2290179 7769325 EPSG:3857:24 7130806 9370916 4580359 15538650 EPSG:3857:25 14261613 18741832 9160719 31077300 EPSG:3857:26 28523227 37483665 18321439 62154601 EPSG:3857:27 57046454 74967331 36642879 124309203 EPSG:3857:28 114092909 149934663 73285759 248618406 EPSG:3857:29 228185818 299869326 146571519 497236812 EPSG:3857:30 456371636 599738652 293143038 994473625 Precipitation trend (% of change) April to Jun (Gu wet Season) 2008-2018 in Somalia (ICPAC) Seasonal trends expressed as percentage of change of rainfall time series (Gu season April to June 2008-2018) reconstructed from station observations, remote sensing and other proxies. The rainfall data were created by combining quality-controlled station observations with satellite rainfall estimates and were reconstructed over land areas on a 0.05 x 0.05 lat/lon grid. Data downloaded from http://digilib.icpac.net/maproom/Climatology/Climate_Analysis/Seasonal_Trend.html.en 40.93000030517578 -1.7000011578202248 51.43000124394894 11.999999046325684 wesr_cca:SOM_ICPAC_prec_trend_perc_Apr_Jun_2008_2018_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 7 8 9 10 EPSG:3857:5 14 16 19 20 EPSG:3857:6 29 32 39 41 EPSG:3857:7 59 64 78 82 EPSG:3857:8 119 129 157 164 EPSG:3857:9 238 258 314 329 EPSG:3857:10 477 516 628 658 EPSG:3857:11 955 1033 1256 1316 EPSG:3857:12 1910 2067 2513 2633 EPSG:3857:13 3820 4134 5027 5266 EPSG:3857:14 7641 8269 10054 10532 EPSG:3857:15 15283 16538 20109 21065 EPSG:3857:16 30567 33077 40219 42130 EPSG:3857:17 61134 66155 80438 84261 EPSG:3857:18 122269 132310 160876 168522 EPSG:3857:19 244538 264620 321752 337044 EPSG:3857:20 489077 529240 643505 674088 EPSG:3857:21 978154 1058480 1287010 1348177 EPSG:3857:22 1956308 2116961 2574021 2696354 EPSG:3857:23 3912616 4233922 5148042 5392709 EPSG:3857:24 7825233 8467845 10296084 10785419 EPSG:3857:25 15650467 16935690 20592168 21570839 EPSG:3857:26 31300934 33871381 41184337 43141679 EPSG:3857:27 62601868 67742763 82368674 86283358 EPSG:3857:28 125203737 135485526 164737348 172566716 EPSG:3857:29 250407474 270971053 329474696 345133432 EPSG:3857:30 500814949 541942107 658949393 690266865 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 5 EPSG:4326:3 3 4 9 10 EPSG:4326:4 6 8 19 20 EPSG:4326:5 13 16 39 41 EPSG:4326:6 27 32 78 82 EPSG:4326:7 55 65 157 164 EPSG:4326:8 110 130 314 329 EPSG:4326:9 221 260 628 658 EPSG:4326:10 443 521 1256 1316 EPSG:4326:11 887 1043 2513 2633 EPSG:4326:12 1774 2086 5027 5266 EPSG:4326:13 3549 4173 10054 10532 EPSG:4326:14 7099 8346 20109 21065 EPSG:4326:15 14199 16693 40219 42130 EPSG:4326:16 28398 33386 80438 84261 EPSG:4326:17 56797 66773 160876 168522 EPSG:4326:18 113595 133547 321752 337044 EPSG:4326:19 227191 267095 643505 674088 EPSG:4326:20 454382 534191 1287010 1348177 EPSG:4326:21 908765 1068382 2574021 2696354 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 7 8 9 10 EPSG:3857:5 14 16 19 20 EPSG:3857:6 29 32 39 41 EPSG:3857:7 59 64 78 82 EPSG:3857:8 119 129 157 164 EPSG:3857:9 238 258 314 329 EPSG:3857:10 477 516 628 658 EPSG:3857:11 955 1033 1256 1316 EPSG:3857:12 1910 2067 2513 2633 EPSG:3857:13 3820 4134 5027 5266 EPSG:3857:14 7641 8269 10054 10532 EPSG:3857:15 15283 16538 20109 21065 EPSG:3857:16 30567 33077 40219 42130 EPSG:3857:17 61134 66155 80438 84261 EPSG:3857:18 122269 132310 160876 168522 EPSG:3857:19 244538 264620 321752 337044 EPSG:3857:20 489077 529240 643505 674088 EPSG:3857:21 978154 1058480 1287010 1348177 EPSG:3857:22 1956308 2116961 2574021 2696354 EPSG:3857:23 3912616 4233922 5148042 5392709 EPSG:3857:24 7825233 8467845 10296084 10785419 EPSG:3857:25 15650467 16935690 20592168 21570839 EPSG:3857:26 31300934 33871381 41184337 43141679 EPSG:3857:27 62601868 67742763 82368674 86283358 EPSG:3857:28 125203737 135485526 164737348 172566716 EPSG:3857:29 250407474 270971053 329474696 345133432 EPSG:3857:30 500814949 541942107 658949393 690266865 Combination Tropical cyclone surge/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Spring precipitations change (%) for the period 2040 - 2059 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_mam_MIDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Historical Generalized Difference Vegetation Index of emerging Northwest Mining Region of Ghana (2010) The Generalized Normalised Difference Vegetation Index (GNDVI) is a modification of the Normalised Difference Vegetation Index (NDVI), which has been proposed by Weicheng Wu (2014) for the assessment of dryland environments due to the inadequacy of the NDVI in these areas. The Generalised Normalised Difference Vegetation Index (GNDVI) 2010 presents a wider outlook of the environmental effects of illegal artisanal small-scale gold mining (galamsey) in the Northwest region of Ghana. However, vegetation displacement in the area cannot entirely be attributed to galamsey. There has been a fast urban growth that is leading to vegetation clearance. The question is, can the trends of urban growth and vegetation depletion be associated to illegal mining? These are some of the scientific questions that these data will help to address. This notwithstanding, how could the looming large-scale gold mining excerbate the observed trends of environmental and land cover change in the Northwest region of Ghana? These data help to address all these relevant questions. -2.941804951 9.626453977 -1.42736896 11.030613419 MAPX:GHA_GNDVI2010 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1828 4029 4063 EPSG:4326:13 3593 3657 8058 8127 EPSG:4326:14 7187 7315 16116 16254 EPSG:4326:15 14375 14631 32232 32508 EPSG:4326:16 28751 29263 64464 65016 EPSG:4326:17 57503 58526 128929 130032 EPSG:4326:18 115007 117052 257859 260065 EPSG:4326:19 230015 234104 515719 520130 EPSG:4326:20 460030 468209 1031438 1040260 EPSG:4326:21 920060 936419 2062877 2080521 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 Mangroves total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:mangrokm2a image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Flood Hazard 25 Years (cm) The GAR Atlas global flood hazard assessment uses a probabilistic approach for modelling riverine flood major river basins around the globe. This has been possible after compiling a global database of stream-flow data, merging different sources and gathering more than 8000 stations over the globe in order to calculate the range of possible discharges from very low to the maximum possible scales at different locations along the rivers. The calculated discharges were introduced in the river sections to model water levels downstream. This procedure allowed for the determination of stochastic event-sets of riverine floods from which hazard maps for several return periods (25, 50, 100, 200, 500, 1000 years) were obtained. The hazard maps are developed at 1kmx1km resolution and have been validated against satellite flood footprints from different sources (DFO archive, UNOSAT flood portal) performing well especially for big events For smaller events (lower return periods), the GAR Atlas flood hazard maps tend to overestimate with respect to similar maps produced locally (hazard maps where available for some countries and were used as benchmark). The main issue being that, due to the resolution, the GAR Atlas flood hazard maps do not take into account flood defenses that are normally present to preserve the value exposed to floods. More information about the flood hazard assessment can be found in the background paper (Rudari et al., 2015). -141.09900045782885 -56.085762831133565 180.0 60.09233546603441 wesr_risk:fl_hazard_25_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 1 15 EPSG:3857:5 9 22 3 31 EPSG:3857:6 18 44 6 63 EPSG:3857:7 37 88 13 127 EPSG:3857:8 74 176 27 255 EPSG:3857:9 148 352 55 511 EPSG:3857:10 296 705 110 1023 EPSG:3857:11 593 1411 221 2047 EPSG:3857:12 1187 2822 442 4095 EPSG:3857:13 2374 5644 885 8191 EPSG:3857:14 4749 11289 1770 16383 EPSG:3857:15 9498 22578 3540 32767 EPSG:3857:16 18997 45156 7081 65535 EPSG:3857:17 37995 90312 14163 131071 EPSG:3857:18 75991 180625 28326 262143 EPSG:3857:19 151983 361251 56653 524287 EPSG:3857:20 303967 722503 113307 1048575 EPSG:3857:21 607934 1445007 226614 2097151 EPSG:3857:22 1215869 2890014 453229 4194304 EPSG:3857:23 2431739 5780029 906458 8388608 EPSG:3857:24 4863479 11560058 1812917 16777215 EPSG:3857:25 9726958 23120116 3625835 33554431 EPSG:3857:26 19453916 46240233 7251671 67108863 EPSG:3857:27 38907833 92480467 14503343 134217727 EPSG:3857:28 77815666 184960934 29006687 268435456 EPSG:3857:29 155631333 369921868 58013375 536870911 EPSG:3857:30 311262667 739843736 116026750 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 1 15 EPSG:4326:4 2 12 3 31 EPSG:4326:5 5 25 6 63 EPSG:4326:6 10 51 13 127 EPSG:4326:7 21 103 27 255 EPSG:4326:8 42 207 55 511 EPSG:4326:9 85 415 110 1023 EPSG:4326:10 170 831 221 2047 EPSG:4326:11 340 1662 442 4095 EPSG:4326:12 680 3324 885 8191 EPSG:4326:13 1361 6648 1770 16383 EPSG:4326:14 2722 13297 3540 32767 EPSG:4326:15 5444 26594 7081 65535 EPSG:4326:16 10889 53188 14163 131071 EPSG:4326:17 21778 106376 28326 262143 EPSG:4326:18 43556 212752 56653 524287 EPSG:4326:19 87112 425505 113307 1048575 EPSG:4326:20 174224 851011 226614 2097151 EPSG:4326:21 348449 1702022 453229 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 1 15 EPSG:3857:5 9 22 3 31 EPSG:3857:6 18 44 6 63 EPSG:3857:7 37 88 13 127 EPSG:3857:8 74 176 27 255 EPSG:3857:9 148 352 55 511 EPSG:3857:10 296 705 110 1023 EPSG:3857:11 593 1411 221 2047 EPSG:3857:12 1187 2822 442 4095 EPSG:3857:13 2374 5644 885 8191 EPSG:3857:14 4749 11289 1770 16383 EPSG:3857:15 9498 22578 3540 32767 EPSG:3857:16 18997 45156 7081 65535 EPSG:3857:17 37995 90312 14163 131071 EPSG:3857:18 75991 180625 28326 262143 EPSG:3857:19 151983 361251 56653 524287 EPSG:3857:20 303967 722503 113307 1048575 EPSG:3857:21 607934 1445007 226614 2097152 EPSG:3857:22 1215869 2890014 453229 4194304 EPSG:3857:23 2431739 5780029 906458 8388607 EPSG:3857:24 4863479 11560058 1812917 16777215 EPSG:3857:25 9726958 23120116 3625835 33554431 EPSG:3857:26 19453916 46240233 7251671 67108863 EPSG:3857:27 38907833 92480467 14503343 134217728 EPSG:3857:28 77815666 184960934 29006687 268435455 EPSG:3857:29 155631333 369921868 58013375 536870911 EPSG:3857:30 311262667 739843736 116026750 1073741824 Combination Tropical cyclone / Forest at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcw_for6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Flood/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_flo_for6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mean temperatures 2008 - Central African Republic Mean observed temperatures in 2008 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2008_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Global Emissions NOx 2010 - EDGARD Global Emissions EDGAR v4.3.1 (January 2016) In EDGARv4.3.1 emissions are calculated for gaseous and particulate air pollutants per sector and country. For the energy related sectors the activity data are mainly based on the energy balance statistics of IEA (2014) Emission gridmaps are expressed in ton substance / 0.1degree x 0.1degree / year -180.0 -77.95 179.95 88.15000000000002 unea_pollution:edg10_nx image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 13 0 15 EPSG:900913:5 0 27 0 31 EPSG:900913:6 0 54 0 63 EPSG:900913:7 0 109 0 127 EPSG:900913:8 0 219 0 255 EPSG:900913:9 0 439 0 511 EPSG:900913:10 0 878 0 1023 EPSG:900913:11 0 1756 0 2047 EPSG:900913:12 0 3513 0 4095 EPSG:900913:13 0 7027 0 8190 EPSG:900913:14 0 14055 0 16381 EPSG:900913:15 0 28110 0 32763 EPSG:900913:16 0 56221 0 65526 EPSG:900913:17 0 112443 0 131053 EPSG:900913:18 0 224887 0 262107 EPSG:900913:19 0 449775 0 524215 EPSG:900913:20 0 899550 0 1048430 EPSG:900913:21 0 1799100 0 2096860 EPSG:900913:22 0 3598201 0 4193721 EPSG:900913:23 0 7196402 0 8387442 EPSG:900913:24 0 14392805 0 16774885 EPSG:900913:25 0 28785610 0 33549771 EPSG:900913:26 0 57571220 0 67099543 EPSG:900913:27 0 115142440 0 134199086 EPSG:900913:28 0 230284881 0 268398173 EPSG:900913:29 0 460569763 0 536796346 EPSG:900913:30 0 921139526 0 1073592693 Areas exposed to extreme heat in Kedougou between 2005 and 2014 Extreme heat is studied by calculating the Land Surface Temperature (LST), defined as the temperature felt when the earth's surface is touched with the hands, or the temperature of the skin on the ground. This temperature estimate is influenced by several parameters, including vegetation and surface emissivity. LST was estimated in relation to Normalized Difference Vegetation Index (NDVI) values determined from red and near-infrared bands. Land surface emissivity (LSE) is recovered directly from thermal infrared bands. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:heat_2005_2014 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491251 EPSG:4326:20 445870 452589 971450 982502 EPSG:4326:21 891741 905179 1942901 1965005 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 tsm_col_zaragoza_20210925 -74.8651063820499 7.579889039548307 -74.7899249680916 7.640072688469066 rs_for_asgm:tsm_col_zaragoza_20210925 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7496 7502 9569 9576 EPSG:4326:15 14993 15004 19139 19152 EPSG:4326:16 29986 30008 38278 38305 EPSG:4326:17 59972 60016 76556 76611 EPSG:4326:18 119945 120032 153113 153223 EPSG:4326:19 239890 240065 306227 306446 EPSG:4326:20 479781 480131 612455 612893 EPSG:4326:21 959562 960263 1224910 1225786 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 Drought-affected areas in Kedougou between 2005 and 2014 The TCI, VCI and VHI indices are used to identify areas affected by drought. They are characterized as vegetation indices because they describe the state of vegetation in a specific area. The VCI is widely used to detect changes in vegetation from poor to favorable conditions. TCI detects vegetative stress induced by high temperatures and high humidity. VHI, on the other hand, is the combination of TCI (temperature) and VCI (vegetation condition) that describes vegetation health. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:vhi_2005_2014 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 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4515 4559 EPSG:3857:14 5985 6091 9030 9118 EPSG:3857:15 11970 12183 18061 18236 EPSG:3857:16 23941 24366 36123 36472 EPSG:3857:17 47883 48732 72247 72945 EPSG:3857:18 95766 97465 144494 145891 EPSG:3857:19 191532 194930 288989 291783 EPSG:3857:20 383064 389860 577979 583567 EPSG:3857:21 766128 779720 1155959 1167135 EPSG:3857:22 1532257 1559441 2311918 2334270 EPSG:3857:23 3064515 3118882 4623837 4668541 EPSG:3857:24 6129030 6237765 9247674 9337082 EPSG:3857:25 12258061 12475531 18495348 18674165 EPSG:3857:26 24516123 24951063 36990696 37348330 EPSG:3857:27 49032246 49902127 73981393 74696661 EPSG:3857:28 98064493 99804255 147962786 149393323 EPSG:3857:29 196128987 199608511 295925572 298786647 EPSG:3857:30 392257975 399217023 591851145 597573294 Forest Integrity Index (FI) - Africa The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> 4.291832979587211 -7.903071018846619 35.40579740803462 6.8343008700661745 MapX_UNDP:africaFI image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 16 19 EPSG:3857:6 30 33 32 38 EPSG:3857:7 61 66 65 76 EPSG:3857:8 123 133 131 153 EPSG:3857:9 246 267 262 306 EPSG:3857:10 492 534 524 612 EPSG:3857:11 985 1069 1048 1225 EPSG:3857:12 1970 2138 2096 2450 EPSG:3857:13 3940 4276 4193 4901 EPSG:3857:14 7880 8552 8387 9803 EPSG:3857:15 15760 17105 16774 19606 EPSG:3857:16 31520 34211 33549 39213 EPSG:3857:17 63041 68422 67098 78426 EPSG:3857:18 126083 136845 134197 156853 EPSG:3857:19 252167 273690 268394 313707 EPSG:3857:20 504334 547380 536788 627414 EPSG:3857:21 1008668 1094761 1073577 1254829 EPSG:3857:22 2017337 2189522 2147155 2509659 EPSG:3857:23 4034674 4379045 4294310 5019318 EPSG:3857:24 8069348 8758091 8588621 10038637 EPSG:3857:25 16138697 17516182 17177243 20077275 EPSG:3857:26 32277394 35032365 34354487 40154551 EPSG:3857:27 64554788 70064730 68708975 80309102 EPSG:3857:28 129109576 140129460 137417950 160618204 EPSG:3857:29 258219152 280258921 274835901 321236408 EPSG:3857:30 516438305 560517843 549671802 642472816 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 8 16 19 EPSG:4326:5 14 17 32 38 EPSG:4326:6 29 34 65 76 EPSG:4326:7 59 69 131 153 EPSG:4326:8 118 139 262 306 EPSG:4326:9 236 278 524 612 EPSG:4326:10 473 556 1048 1225 EPSG:4326:11 946 1113 2096 2450 EPSG:4326:12 1892 2227 4193 4901 EPSG:4326:13 3784 4455 8387 9803 EPSG:4326:14 7569 8911 16774 19606 EPSG:4326:15 15139 17822 33549 39213 EPSG:4326:16 30279 35645 67098 78426 EPSG:4326:17 60559 71290 134197 156853 EPSG:4326:18 121118 142581 268394 313707 EPSG:4326:19 242237 285163 536788 627414 EPSG:4326:20 484475 570326 1073577 1254829 EPSG:4326:21 968950 1140653 2147155 2509659 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 16 19 EPSG:3857:6 30 33 32 38 EPSG:3857:7 61 66 65 76 EPSG:3857:8 123 133 131 153 EPSG:3857:9 246 267 262 306 EPSG:3857:10 492 534 524 612 EPSG:3857:11 985 1069 1048 1225 EPSG:3857:12 1970 2138 2096 2450 EPSG:3857:13 3940 4276 4193 4901 EPSG:3857:14 7880 8552 8387 9803 EPSG:3857:15 15760 17105 16774 19606 EPSG:3857:16 31520 34211 33549 39213 EPSG:3857:17 63041 68422 67098 78426 EPSG:3857:18 126083 136845 134197 156853 EPSG:3857:19 252167 273690 268394 313707 EPSG:3857:20 504334 547380 536788 627414 EPSG:3857:21 1008668 1094761 1073577 1254829 EPSG:3857:22 2017337 2189522 2147155 2509659 EPSG:3857:23 4034674 4379045 4294310 5019318 EPSG:3857:24 8069348 8758091 8588621 10038637 EPSG:3857:25 16138697 17516182 17177243 20077275 EPSG:3857:26 32277394 35032365 34354487 40154551 EPSG:3857:27 64554788 70064730 68708975 80309102 EPSG:3857:28 129109576 140129460 137417950 160618204 EPSG:3857:29 258219152 280258921 274835901 321236408 EPSG:3857:30 516438305 560517843 549671802 642472816 Population Based Global Carbon Emissions Dataset in 0.1°Resolution (2014) Since mid of 20th century, anthropogenic greenhouse gas emissions have increased, it is very possible of being driven largely by economic and population growth, and causing the global warming. Based on the global carbon emissions data of 2014 in each country from CDIAC (Carbon Dioxide Information Analysis Center) and population density data in 2015 from SEDAC (Socioeconomic Data and Applications Center), the population based global carbon emissions dataset in 0.1° resolution (2014) was developed by the model of integrating population density as an economic-population composite indicator to weighted carbon emissions. The result shows the main carbon emission areas are located in the eastern United States, eastern China, Japan, Korea, India, Southeast Asia and Europe, and there are spatial differences in each region. The result can reflect spatial distribution of the current global carbon emissions and provide basic data for global change research. The dataset was archived in .tif data format with the data size of 22.7 MB (3.92MB in compressed file). Foundation Item： Ministry of Science and Technology of P. R. China (2016YFA0602704) Data Citation： FAN Zhixin,SU Yun*,FANG Xiuqi.2017.Population Based Global Carbon Emissions Dataset in 0.1°Resolution (2014) ( GlobalPopCarbonEmis2014 ) ,Global Change Research Data Publishing & Repository,DOI:10.3974/geodb.2017.03.12.V1 -180.0 -59.99999999999177 180.0 83.60000000000822 unea_pollution:GlobalPopCarbonEmis2014 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 9 213 0 511 EPSG:4326:9 18 426 0 1023 EPSG:4326:10 36 853 0 2047 EPSG:4326:11 72 1706 0 4095 EPSG:4326:12 145 3413 0 8191 EPSG:4326:13 291 6826 0 16383 EPSG:4326:14 582 13653 0 32767 EPSG:4326:15 1165 27306 0 65535 EPSG:4326:16 2330 54613 0 131071 EPSG:4326:17 4660 109226 0 262143 EPSG:4326:18 9320 218453 0 524287 EPSG:4326:19 18641 436906 0 1048575 EPSG:4326:20 37282 873813 0 2097151 EPSG:4326:21 74565 1747626 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 1 22 0 31 EPSG:900913:6 2 45 0 63 EPSG:900913:7 5 90 0 127 EPSG:900913:8 10 181 0 255 EPSG:900913:9 20 363 0 511 EPSG:900913:10 41 726 0 1023 EPSG:900913:11 83 1453 0 2047 EPSG:900913:12 167 2906 0 4095 EPSG:900913:13 335 5813 0 8191 EPSG:900913:14 671 11626 0 16383 EPSG:900913:15 1343 23252 0 32767 EPSG:900913:16 2686 46504 0 65535 EPSG:900913:17 5372 93008 0 131071 EPSG:900913:18 10745 186017 0 262143 EPSG:900913:19 21491 372034 0 524287 EPSG:900913:20 42982 744069 0 1048575 EPSG:900913:21 85965 1488139 0 2097151 EPSG:900913:22 171930 2976279 0 4194303 EPSG:900913:23 343861 5952559 0 8388607 EPSG:900913:24 687722 11905118 0 16777215 EPSG:900913:25 1375445 23810236 0 33554431 EPSG:900913:26 2750891 47620473 0 67108863 EPSG:900913:27 5501782 95240947 0 134217727 EPSG:900913:28 11003564 190481895 0 268435455 EPSG:900913:29 22007129 380963791 0 536870911 EPSG:900913:30 44014258 761927583 0 1073741823 Yearly emissions of CO2 (short cycle organic Carbon) - 1990 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -55.899999999992474 179.99999999997954 76.5 wesr_climat:v60_CO2_org_short-cycle_C_1990_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 11 0 15 EPSG:3857:5 5 22 0 31 EPSG:3857:6 10 44 0 63 EPSG:3857:7 20 88 0 127 EPSG:3857:8 41 176 0 255 EPSG:3857:9 82 352 0 511 EPSG:3857:10 164 704 0 1023 EPSG:3857:11 328 1409 0 2047 EPSG:3857:12 656 2818 0 4095 EPSG:3857:13 1313 5637 0 8191 EPSG:3857:14 2627 11274 0 16383 EPSG:3857:15 5254 22548 0 32767 EPSG:3857:16 10509 45096 0 65535 EPSG:3857:17 21018 90192 0 131071 EPSG:3857:18 42036 180384 0 262143 EPSG:3857:19 84072 360768 0 524287 EPSG:3857:20 168145 721536 0 1048575 EPSG:3857:21 336291 1443072 0 2097151 EPSG:3857:22 672583 2886144 0 4194304 EPSG:3857:23 1345167 5772289 0 8388608 EPSG:3857:24 2690335 11544579 0 16777215 EPSG:3857:25 5380671 23089159 0 33554431 EPSG:3857:26 10761342 46178318 0 67108863 EPSG:3857:27 21522685 92356637 0 134217727 EPSG:3857:28 43045370 184713274 0 268435456 EPSG:3857:29 86090740 369426548 0 536870911 EPSG:3857:30 172181481 738853097 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 0 31 EPSG:4326:5 2 25 0 63 EPSG:4326:6 4 51 0 127 EPSG:4326:7 9 103 0 255 EPSG:4326:8 19 207 0 511 EPSG:4326:9 38 415 0 1023 EPSG:4326:10 76 830 0 2047 EPSG:4326:11 153 1660 0 4095 EPSG:4326:12 307 3320 0 8191 EPSG:4326:13 614 6640 0 16383 EPSG:4326:14 1228 13280 0 32767 EPSG:4326:15 2457 26560 0 65535 EPSG:4326:16 4915 53120 0 131071 EPSG:4326:17 9830 106241 0 262143 EPSG:4326:18 19660 212482 0 524287 EPSG:4326:19 39321 424964 0 1048575 EPSG:4326:20 78643 849929 0 2097151 EPSG:4326:21 157286 1699858 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 11 0 15 EPSG:3857:5 5 22 0 31 EPSG:3857:6 10 44 0 63 EPSG:3857:7 20 88 0 127 EPSG:3857:8 41 176 0 255 EPSG:3857:9 82 352 0 511 EPSG:3857:10 164 704 0 1023 EPSG:3857:11 328 1409 0 2047 EPSG:3857:12 656 2818 0 4095 EPSG:3857:13 1313 5637 0 8191 EPSG:3857:14 2627 11274 0 16383 EPSG:3857:15 5254 22548 0 32767 EPSG:3857:16 10509 45096 0 65535 EPSG:3857:17 21018 90192 0 131071 EPSG:3857:18 42036 180384 0 262143 EPSG:3857:19 84072 360768 0 524287 EPSG:3857:20 168145 721536 0 1048575 EPSG:3857:21 336291 1443072 0 2097152 EPSG:3857:22 672583 2886144 0 4194304 EPSG:3857:23 1345167 5772289 0 8388607 EPSG:3857:24 2690335 11544579 0 16777215 EPSG:3857:25 5380671 23089159 0 33554431 EPSG:3857:26 10761342 46178318 0 67108863 EPSG:3857:27 21522685 92356637 0 134217728 EPSG:3857:28 43045370 184713274 0 268435455 EPSG:3857:29 86090740 369426548 0 536870911 EPSG:3857:30 172181481 738853097 0 1073741824 Combination Tropical cyclone surge/ Coral reefs at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_cor6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Self-calibrating Palmer Drought Severity Index (scPDSI) 2019 (CRU) This layer shows the average values for 2019 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_19_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from IPSL/LMD/LSCE, France, CM4 V1 Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_ipsl_cm4_5km_2041-2060_debiasedmean_tas_av_12m_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Population distribution (GHSL) 2020 The GHS-POP depicts the distribution of human population, expressed as the number of people per cell. Residential population are derived from the raw global census data harmonized by CIESIN for the Gridded Population of the World, version 4.11 (GPWv4.11) at polygon level, and disaggregated from census or administrative units to grid cells, informed by the distribution, classification and density of built-up as mapped in the GHSL global layers. More information at JRC: Global Human Settlement Layer (GHSL) – original source: GHS_POP_E2020_GLOBE_R2022A_54009_1000_V1_0. Dataset: Schiavina M., Freire S., MacManus K. (2022): GHS-POP R2022A - GHS population grid multitemporal (1975-2030).European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/d6d86a90-4351-4508-99c1-cb074b022c4a, doi:10.2905/D6D86A90-4351-4508-99C1-CB074B022C4A Concept & Methodology: Freire S., MacManus K., Pesaresi M., Doxsey-Whitfield E., Mills J. (2016) Development of new open and free multi-temporal global population grids at 250 m resolution. Geospatial Data in a Changing World; Association of Geographic Information Laboratories in Europe (AGILE), AGILE 2016 -180.0 -60.01666666090665 180.0 84.01666667236907 grid_data_core_pro:GHS_POP_E2020_GLOBE_R2022A_54009_1000_V1_0_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 45 0 63 EPSG:3857:7 3 90 0 127 EPSG:3857:8 7 181 0 255 EPSG:3857:9 15 363 0 511 EPSG:3857:10 30 726 0 1023 EPSG:3857:11 61 1453 0 2047 EPSG:3857:12 123 2906 0 4095 EPSG:3857:13 247 5813 0 8191 EPSG:3857:14 495 11627 0 16383 EPSG:3857:15 991 23255 0 32767 EPSG:3857:16 1982 46510 0 65535 EPSG:3857:17 3965 93020 0 131071 EPSG:3857:18 7931 186041 0 262143 EPSG:3857:19 15862 372083 0 524287 EPSG:3857:20 31725 744167 0 1048575 EPSG:3857:21 63451 1488334 0 2097151 EPSG:3857:22 126903 2976668 0 4194304 EPSG:3857:23 253807 5953336 0 8388608 EPSG:3857:24 507615 11906672 0 16777215 EPSG:3857:25 1015231 23813344 0 33554431 EPSG:3857:26 2030463 47626689 0 67108863 EPSG:3857:27 4060926 95253378 0 134217727 EPSG:3857:28 8121853 190506757 0 268435456 EPSG:3857:29 16243706 381013514 0 536870911 EPSG:3857:30 32487412 762027029 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 8 213 0 511 EPSG:4326:9 17 426 0 1023 EPSG:4326:10 34 853 0 2047 EPSG:4326:11 68 1706 0 4095 EPSG:4326:12 136 3413 0 8191 EPSG:4326:13 272 6827 0 16383 EPSG:4326:14 544 13654 0 32767 EPSG:4326:15 1089 27309 0 65535 EPSG:4326:16 2178 54619 0 131071 EPSG:4326:17 4356 109238 0 262143 EPSG:4326:18 8713 218477 0 524287 EPSG:4326:19 17427 436955 0 1048575 EPSG:4326:20 34855 873910 0 2097151 EPSG:4326:21 69710 1747820 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 45 0 63 EPSG:3857:7 3 90 0 127 EPSG:3857:8 7 181 0 255 EPSG:3857:9 15 363 0 511 EPSG:3857:10 30 726 0 1023 EPSG:3857:11 61 1453 0 2047 EPSG:3857:12 123 2906 0 4095 EPSG:3857:13 247 5813 0 8191 EPSG:3857:14 495 11627 0 16383 EPSG:3857:15 991 23255 0 32767 EPSG:3857:16 1982 46510 0 65535 EPSG:3857:17 3965 93020 0 131071 EPSG:3857:18 7931 186041 0 262143 EPSG:3857:19 15862 372083 0 524287 EPSG:3857:20 31725 744167 0 1048575 EPSG:3857:21 63451 1488334 0 2097152 EPSG:3857:22 126903 2976668 0 4194304 EPSG:3857:23 253807 5953336 0 8388607 EPSG:3857:24 507615 11906672 0 16777215 EPSG:3857:25 1015231 23813344 0 33554431 EPSG:3857:26 2030463 47626689 0 67108863 EPSG:3857:27 4060926 95253378 0 134217728 EPSG:3857:28 8121853 190506757 0 268435455 EPSG:3857:29 16243706 381013514 0 536870911 EPSG:3857:30 32487412 762027029 0 1073741824 Histtorical Generalized Difference Vegetation Index of emerging Northwest Mining Region of Ghana (2000) The Generalized Normalised Difference Vegetation Index (GNDVI) is a modification of the Normalised Difference Vegetation Index (NDVI), which has been proposed by Weicheng Wu (2014) for the assessment of dryland environments due to the inadequacy of the NDVI in these areas. The Generalised Normalised Difference Vegetation Index (GNDVI) of 2000 shows the trends and patterns of vegetation health and degradation in the area. The data further shows the elements contributing to the fast approaching dessertification of the area. The data further sets the baseline analysis and the amount of cost-benefit analysis that must be triggered in view of the fast approaching dessertification and looming large-scale mining in the Northwest Region of Ghana -2.941804951 9.626453977 -1.42736896 11.030613419 MAPX:GHA_GNDVI2000 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1828 4029 4063 EPSG:4326:13 3593 3657 8058 8127 EPSG:4326:14 7187 7315 16116 16254 EPSG:4326:15 14375 14631 32232 32508 EPSG:4326:16 28751 29263 64464 65016 EPSG:4326:17 57503 58526 128929 130032 EPSG:4326:18 115007 117052 257859 260065 EPSG:4326:19 230015 234104 515719 520130 EPSG:4326:20 460030 468209 1031438 1040260 EPSG:4326:21 920060 936419 2062877 2080521 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 Ksat-based Soil Erodibility The modified global soil erodibility map (Kksat factor) where the measured Ksat values were incorporated into the Wischmeier and Smith (1978) soil texture-based K factor equation. This dataset encompasses global soil erodibility (K) factor maps, with the K factor being estimated through the Wischmeier and Smith (1978) method. The equation incorporates permeability information crudely and indirectly, mainly relying on soil texture details, potentially overlooking factors like vegetation, biopores, and clay minerals. To address this limitation, we integrated measured Ksat values, representing soil hydraulic properties, into the Wischmeier and Smith (1978) soil texture-based K factor equation (referred to as KWischmeier factor) to formulate the Ksat-based soil erodibility (Kksat factor). Credits: Gupta, S., Borrelli, P., Panagos, P., Alewell, C., 2024. An advanced global soil erodibility (K) assessment including the effects of saturated hydraulic conductivity. 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20190927_843_QG_copy_mos_opt 149.66386433258654 -36.214355797728665 150.97478007537504 -32.49681353198739 wesr_swipe:20190927_843_QG_copy_mos_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 3 3 EPSG:3857:3 4 4 7 7 EPSG:3857:4 9 9 14 14 EPSG:3857:5 19 19 29 29 EPSG:3857:6 38 38 58 58 EPSG:3857:7 76 77 117 117 EPSG:3857:8 152 155 234 235 EPSG:3857:9 304 311 468 470 EPSG:3857:10 609 622 937 941 EPSG:3857:11 1219 1245 1875 1882 EPSG:3857:12 2439 2490 3750 3765 EPSG:3857:13 4878 4981 7501 7531 EPSG:3857:14 9757 9962 15003 15063 EPSG:3857:15 19514 19924 30006 30126 EPSG:3857:16 39029 39849 60013 60252 EPSG:3857:17 78058 79698 120026 120504 EPSG:3857:18 156116 159396 240053 241008 EPSG:3857:19 312233 318793 480107 482016 EPSG:3857:20 624467 637587 960215 964033 EPSG:3857:21 1248934 1275175 1920431 1928067 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EPSG:3857:25 19982952 20402815 30726899 30849085 EPSG:3857:26 39965905 40805630 61453798 61698170 EPSG:3857:27 79931811 81611260 122907596 123396341 EPSG:3857:28 159863623 163222521 245815193 246792683 EPSG:3857:29 319727247 326445042 491630387 493585366 EPSG:3857:30 639454495 652890084 983260775 987170733 Central Congo Basin peat carbon density uncertainty (2022) Metadata for the file: Crezee_2022_Uncertainty_Carbon_density_2000runs.tif This is the file used to create Figure 4b of the paper: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This is a raster file representing relative uncertainty (in %) around the median carbon density estimate (Fig. 4a of the paper). For each pixel, the width of the 95% confidence interval was calculated from 2,000 carbon density estimates by substracting the 2.5th from the 97.5th percentile. Relative uncertainty was then calculated as ± half the width of the 95% confidence interval, expressed as percentage of the median carbon density estimate. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 14.999619457 -5.015743389 24.000289446 3.511065288 peatlands:Crezee_2022_Uncertainty_Carbon_density_2000runs_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 72 EPSG:3857:8 125 131 138 145 EPSG:3857:9 251 263 277 290 EPSG:3857:10 502 526 554 580 EPSG:3857:11 1004 1052 1109 1160 EPSG:3857:12 2008 2105 2218 2321 EPSG:3857:13 4016 4210 4437 4642 EPSG:3857:14 8032 8420 8874 9284 EPSG:3857:15 16064 16841 17749 18568 EPSG:3857:16 32128 33682 35498 37137 EPSG:3857:17 64256 67364 70997 74274 EPSG:3857:18 128513 134729 141994 148548 EPSG:3857:19 257027 269458 283988 297096 EPSG:3857:20 514054 538916 567977 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9087640 9507102 EPSG:3857:25 16449755 17245315 18175281 19014205 EPSG:3857:26 32899511 34490630 36350563 38028410 EPSG:3857:27 65799023 68981261 72701127 76056820 EPSG:3857:28 131598047 137962523 145402254 152113640 EPSG:3857:29 263196095 275925046 290804509 304227281 EPSG:3857:30 526392191 551850093 581609019 608454563 Year precipitations 2011 - Central African Republic Total precipitations observed in 2011 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2011_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 gab_wb_buffer_100m 8.705816679771605 -3.801030948400662 14.383836049311741 2.3177509999999604 mapx_chemobs:gab_wb_buffer_100m image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 8 EPSG:3857:5 15 16 16 17 EPSG:3857:6 31 32 33 34 EPSG:3857:7 63 65 67 69 EPSG:3857:8 126 130 134 138 EPSG:3857:9 252 261 268 276 EPSG:3857:10 505 522 536 552 EPSG:3857:11 1010 1045 1073 1105 EPSG:3857:12 2021 2091 2147 2211 EPSG:3857:13 4043 4182 4294 4423 EPSG:3857:14 8086 8365 8588 8846 EPSG:3857:15 16172 16730 17176 17693 EPSG:3857:16 32345 33460 34352 35386 EPSG:3857:17 64691 66920 68705 70772 EPSG:3857:18 129383 133841 137411 141545 EPSG:3857:19 258767 267683 274822 283091 EPSG:3857:20 517535 535367 549645 566183 EPSG:3857:21 1035070 1070734 1099291 1132367 EPSG:3857:22 2070140 2141469 2198582 2264735 EPSG:3857:23 4140281 4282939 4397164 4529471 EPSG:3857:24 8280563 8565878 8794328 9058943 EPSG:3857:25 16561127 17131757 17588656 18117886 EPSG:3857:26 33122254 34263515 35177313 36235773 EPSG:3857:27 66244508 68527031 70354627 72471546 EPSG:3857:28 132489016 137054063 140709255 144943093 EPSG:3857:29 264978032 274108126 281418510 289886187 EPSG:3857:30 529956064 548216253 562837021 579772374 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 8 EPSG:4326:4 7 8 16 17 EPSG:4326:5 15 16 33 34 EPSG:4326:6 31 33 67 69 EPSG:4326:7 62 66 134 138 EPSG:4326:8 124 133 268 276 EPSG:4326:9 249 266 536 552 EPSG:4326:10 498 533 1073 1105 EPSG:4326:11 997 1067 2147 2211 EPSG:4326:12 1995 2134 4294 4423 EPSG:4326:13 3990 4268 8588 8846 EPSG:4326:14 7981 8537 17176 17693 EPSG:4326:15 15962 17075 34352 35386 EPSG:4326:16 31924 34151 68705 70772 EPSG:4326:17 63848 68303 137411 141545 EPSG:4326:18 127696 136607 274822 283091 EPSG:4326:19 255393 273215 549645 566183 EPSG:4326:20 510786 546430 1099291 1132367 EPSG:4326:21 1021572 1092861 2198582 2264735 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 8 EPSG:3857:5 15 16 16 17 EPSG:3857:6 31 32 33 34 EPSG:3857:7 63 65 67 69 EPSG:3857:8 126 130 134 138 EPSG:3857:9 252 261 268 276 EPSG:3857:10 505 522 536 552 EPSG:3857:11 1010 1045 1073 1105 EPSG:3857:12 2021 2091 2147 2211 EPSG:3857:13 4043 4182 4294 4423 EPSG:3857:14 8086 8365 8588 8846 EPSG:3857:15 16172 16730 17176 17693 EPSG:3857:16 32345 33460 34352 35386 EPSG:3857:17 64691 66920 68705 70772 EPSG:3857:18 129383 133841 137411 141545 EPSG:3857:19 258767 267683 274822 283091 EPSG:3857:20 517535 535367 549645 566183 EPSG:3857:21 1035070 1070734 1099291 1132367 EPSG:3857:22 2070140 2141469 2198582 2264735 EPSG:3857:23 4140281 4282939 4397164 4529471 EPSG:3857:24 8280563 8565878 8794328 9058943 EPSG:3857:25 16561127 17131757 17588656 18117886 EPSG:3857:26 33122254 34263515 35177313 36235773 EPSG:3857:27 66244508 68527031 70354627 72471546 EPSG:3857:28 132489016 137054063 140709255 144943093 EPSG:3857:29 264978032 274108126 281418510 289886187 EPSG:3857:30 529956064 548216253 562837021 579772374 wesr_climate_rcp45 -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_rcp45 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Precipitation averages (mm) 1986-2005 (RCP4.5) Yearly precipitation averages in the reference period 1986-2005 based on the climate scenario RCP4.5. -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:pr_45_86_05 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 6 11 EPSG:4326:4 3 8 13 22 EPSG:4326:5 7 17 27 45 EPSG:4326:6 15 34 54 90 EPSG:4326:7 31 68 109 181 EPSG:4326:8 63 137 218 363 EPSG:4326:9 127 275 436 726 EPSG:4326:10 255 550 872 1453 EPSG:4326:11 510 1101 1745 2906 EPSG:4326:12 1021 2203 3490 5813 EPSG:4326:13 2043 4406 6980 11626 EPSG:4326:14 4086 8812 13960 23252 EPSG:4326:15 8173 17625 27921 46505 EPSG:4326:16 16347 35251 55843 93010 EPSG:4326:17 32695 70502 111687 186020 EPSG:4326:18 65390 141004 223375 372040 EPSG:4326:19 130780 282008 446751 744081 EPSG:4326:20 261561 564017 893503 1488162 EPSG:4326:21 523122 1128034 1787006 2976324 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 Average year temperature anomalies (2021-2022) against 1901-1920 Average year temperature anomalies in °Celsius across the period 2021-2022 calculated over the average temperatures per year in the period 1901-1920 (as close as possible to the pre-industrial era). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_21_22_anom_1901_1920 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcw_for6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Spectral Acceleration 1.0 Sec 2475 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_10_s_2475_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 exposure_pesato_02_03 -5.3554163761242854 30.264583696518883 35.977083623875714 45.50708369651888 Medicip:exposure_pesato_02_03 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 31 38 EPSG:3857:7 45 52 62 76 EPSG:3857:8 91 105 124 153 EPSG:3857:9 183 210 248 307 EPSG:3857:10 366 421 496 614 EPSG:3857:11 732 843 993 1228 EPSG:3857:12 1465 1686 1987 2457 EPSG:3857:13 2930 3372 3974 4914 EPSG:3857:14 5860 6745 7948 9829 EPSG:3857:15 11721 13491 15896 19658 EPSG:3857:16 23443 26982 31793 39317 EPSG:3857:17 46887 53965 63586 78634 EPSG:3857:18 93775 107931 127172 157269 EPSG:3857:19 187550 215862 254344 314539 EPSG:3857:20 375100 431725 508689 629078 EPSG:3857:21 750201 863450 1017378 1258157 EPSG:3857:22 1500403 1726901 2034756 2516315 EPSG:3857:23 3000807 3453803 4069513 5032630 EPSG:3857:24 6001615 6907606 8139027 10065261 EPSG:3857:25 12003230 13815212 16278055 20130523 EPSG:3857:26 24006460 27630425 32556110 40261046 EPSG:3857:27 48012920 55260850 65112220 80522092 EPSG:3857:28 96025840 110521701 130224440 161044185 EPSG:3857:29 192051680 221043403 260448880 322088371 EPSG:3857:30 384103360 442086806 520897760 644176743 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 15 19 EPSG:4326:5 7 10 31 38 EPSG:4326:6 15 21 62 76 EPSG:4326:7 31 42 124 153 EPSG:4326:8 63 84 248 307 EPSG:4326:9 126 169 496 614 EPSG:4326:10 253 339 993 1228 EPSG:4326:11 506 679 1987 2457 EPSG:4326:12 1012 1359 3974 4914 EPSG:4326:13 2024 2718 7948 9829 EPSG:4326:14 4049 5437 15896 19658 EPSG:4326:15 8099 10874 31793 39317 EPSG:4326:16 16199 21749 63586 78634 EPSG:4326:17 32398 43498 127172 157269 EPSG:4326:18 64797 86996 254344 314539 EPSG:4326:19 129595 173992 508689 629078 EPSG:4326:20 259190 347984 1017378 1258157 EPSG:4326:21 518380 695968 2034756 2516315 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 31 38 EPSG:3857:7 45 52 62 76 EPSG:3857:8 91 105 124 153 EPSG:3857:9 183 210 248 307 EPSG:3857:10 366 421 496 614 EPSG:3857:11 732 843 993 1228 EPSG:3857:12 1465 1686 1987 2457 EPSG:3857:13 2930 3372 3974 4914 EPSG:3857:14 5860 6745 7948 9829 EPSG:3857:15 11721 13491 15896 19658 EPSG:3857:16 23443 26982 31793 39317 EPSG:3857:17 46887 53965 63586 78634 EPSG:3857:18 93775 107931 127172 157269 EPSG:3857:19 187550 215862 254344 314539 EPSG:3857:20 375100 431725 508689 629078 EPSG:3857:21 750201 863450 1017378 1258157 EPSG:3857:22 1500403 1726901 2034756 2516315 EPSG:3857:23 3000807 3453803 4069513 5032630 EPSG:3857:24 6001615 6907606 8139027 10065261 EPSG:3857:25 12003230 13815212 16278055 20130523 EPSG:3857:26 24006460 27630425 32556110 40261046 EPSG:3857:27 48012920 55260850 65112220 80522092 EPSG:3857:28 96025840 110521701 130224440 161044185 EPSG:3857:29 192051680 221043403 260448880 322088371 EPSG:3857:30 384103360 442086806 520897760 644176743 Combination Tsunami/Coral reefs at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_cor6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Winter precipitations change (%) for the period 2040 - 2059 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_djf_MIDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 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16380 38703 38758 EPSG:4326:16 32640 32760 77407 77517 EPSG:4326:17 65281 65520 154815 155034 EPSG:4326:18 130562 131041 309631 310068 EPSG:4326:19 261124 262082 619262 620137 EPSG:4326:20 522249 524165 1238524 1240274 EPSG:4326:21 1044498 1048330 2477049 2480548 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 37 37 EPSG:3857:7 63 63 75 75 EPSG:3857:8 127 127 151 151 EPSG:3857:9 255 255 302 302 EPSG:3857:10 511 511 604 605 EPSG:3857:11 1022 1023 1209 1211 EPSG:3857:12 2044 2047 2418 2422 EPSG:3857:13 4088 4095 4837 4844 EPSG:3857:14 8176 8191 9675 9689 EPSG:3857:15 16352 16382 19351 19379 EPSG:3857:16 32704 32764 38703 38758 EPSG:3857:17 65408 65528 77407 77517 EPSG:3857:18 130817 131056 154815 155034 EPSG:3857:19 261634 262113 309631 310068 EPSG:3857:20 523268 524226 619262 620137 EPSG:3857:21 1046537 1048453 1238524 1240274 EPSG:3857:22 2093074 2096906 2477049 2480548 EPSG:3857:23 4186148 4193813 4954099 4961097 EPSG:3857:24 8372296 8387627 9908198 9922195 EPSG:3857:25 16744593 16775255 19816396 19844390 EPSG:3857:26 33489187 33550510 39632793 39688780 EPSG:3857:27 66978375 67101021 79265586 79377561 EPSG:3857:28 133956751 134202043 158531172 158755123 EPSG:3857:29 267913502 268404087 317062345 317510247 EPSG:3857:30 535827005 536808174 634124691 635020494 Central Congo Basin hardwood-dominated peat swamp forest probability (2022) Metadata for files in the zip archive: Crezee_2022_Central_Congo_Peat_Probability_Layers.zip This folder contains 5 probability layers, the output of 1000 classification runs using a random 2/3 subset of training data, that was used to produce the peatland extent estimates and probability map (Figure 1b) in: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This folder contains 5 layers: - Probability_2022_HardwoodDominatedPeatSwamp.tif - Probability_2022_PalmDominatedPeatSwamp.tif - Probability_2022_NonPeatFormingForest.tif - Probability_2022_Savanna.tif - Probability_2022_Water.tif Each layer has pixel values from 0-1000, representing the number of times that class was given as the most likely class for that pixel in 1000 Maximum Likelihood classifications using a random 2/3 subset of the training data. For example, a value of 995 in the Probability_2022_Water.tif file means that in 995 of the 1000 runs this pixel was mapped as 'water'. Conversely, a value of 4 in the Probability_2022_Savanna.tif would mean that that pixel was only mapped as savanna 4 times in the 1000 runs. As an approximation, dividing these values by 1000 gives the probability that that pixel contains a majority of vegetation of that class. Total peat swamp forest probability is obtained by summing the probabilities of the hardwood and palm-dominated peat swamp forest files. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 15.0 -4.999916949999999 25.72744828 3.30533333 peatlands:Crezee_2022_Probability_HardwoodDominatedPeatSwamp_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 8 17 18 EPSG:4326:5 15 16 34 36 EPSG:4326:6 30 33 69 73 EPSG:4326:7 61 67 138 146 EPSG:4326:8 123 135 277 292 EPSG:4326:9 246 270 554 585 EPSG:4326:10 493 540 1109 1170 EPSG:4326:11 986 1080 2218 2340 EPSG:4326:12 1972 2161 4437 4681 EPSG:4326:13 3945 4323 8874 9362 EPSG:4326:14 7891 8647 17749 18725 EPSG:4326:15 15782 17294 35498 37451 EPSG:4326:16 31564 34588 70997 74903 EPSG:4326:17 63129 69176 141994 149806 EPSG:4326:18 126258 138353 283989 299612 EPSG:4326:19 252516 276707 567978 599224 EPSG:4326:20 505033 553414 1135957 1198449 EPSG:4326:21 1010066 1106829 2271914 2396898 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 Atmospheric mercury emissions from anthropogenic sources (2010) Dataset of gridded (0.5 x 0.5 degree) global emissions inventory of mercury emissions to the atmosphere in 2010 from anthropogenic sources. Units: g/km2 -180.0 -55.0 180.0 84.5 unea_pollution:mercure_em image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 0 25 0 63 EPSG:4326:6 1 51 0 127 EPSG:4326:7 3 103 0 255 EPSG:4326:8 7 206 0 511 EPSG:4326:9 15 412 0 1023 EPSG:4326:10 31 824 0 2047 EPSG:4326:11 62 1649 0 4095 EPSG:4326:12 125 3299 0 8191 EPSG:4326:13 250 6599 0 16383 EPSG:4326:14 500 13198 0 32767 EPSG:4326:15 1001 26396 0 65535 EPSG:4326:16 2002 52792 0 131071 EPSG:4326:17 4004 105585 0 262143 EPSG:4326:18 8009 211171 0 524287 EPSG:4326:19 16019 422343 0 1048575 EPSG:4326:20 32039 844686 0 2097151 EPSG:4326:21 64079 1689372 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 10 0 15 EPSG:900913:5 0 21 0 31 EPSG:900913:6 1 43 0 63 EPSG:900913:7 2 87 0 127 EPSG:900913:8 4 175 0 255 EPSG:900913:9 8 350 0 511 EPSG:900913:10 17 700 0 1023 EPSG:900913:11 34 1400 0 2047 EPSG:900913:12 68 2800 0 4095 EPSG:900913:13 137 5600 0 8191 EPSG:900913:14 275 11201 0 16383 EPSG:900913:15 551 22403 0 32767 EPSG:900913:16 1102 44807 0 65535 EPSG:900913:17 2205 89614 0 131071 EPSG:900913:18 4411 179228 0 262143 EPSG:900913:19 8822 358456 0 524287 EPSG:900913:20 17645 716913 0 1048575 EPSG:900913:21 35291 1433827 0 2097151 EPSG:900913:22 70582 2867654 0 4194303 EPSG:900913:23 141165 5735309 0 8388607 EPSG:900913:24 282330 11470618 0 16777215 EPSG:900913:25 564661 22941236 0 33554431 EPSG:900913:26 1129323 45882473 0 67108863 EPSG:900913:27 2258647 91764947 0 134217727 EPSG:900913:28 4517294 183529894 0 268435455 EPSG:900913:29 9034588 367059788 0 536870911 EPSG:900913:30 18069176 734119577 0 1073741823 Forest Integrity Index (2019) (Montana State University) The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/><br>To download a subset of the FII data clipped to your country please click <a href="https://app.box.com/s/380mxwzhuqece2v9fy8ovhcv3s5cb82g/folder/71324555438"target="_blank">here</a>.<br/> -81.70887178141503 -20.582648947388527 153.4281182773073 25.91783325130279 MapX_UNDP:FSII_merged image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 871 1143 559 1896 EPSG:3857:12 1742 2287 1118 3793 EPSG:3857:13 3485 4574 2236 7587 EPSG:3857:14 6970 9149 4473 15174 EPSG:3857:15 13940 18299 8946 30349 EPSG:3857:16 27880 36598 17893 60698 EPSG:3857:17 55760 73196 35786 121397 EPSG:3857:18 111520 146392 71573 242794 EPSG:3857:19 223041 292785 143146 485589 EPSG:3857:20 446082 585571 286293 971179 EPSG:3857:21 892164 1171143 572587 1942359 EPSG:3857:22 1784328 2342287 1145174 3884719 EPSG:3857:23 3568657 4684575 2290349 7769438 EPSG:3857:24 7137315 9369151 4580698 15538876 EPSG:3857:25 14274631 18738303 9161397 31077753 EPSG:3857:26 28549263 37476607 18322794 62155506 EPSG:3857:27 57098527 74953214 36645588 124311012 EPSG:3857:28 114197054 149906428 73291177 248622024 EPSG:3857:29 228394108 299812857 146582354 497244049 EPSG:3857:30 456788217 599625715 293164709 994488099 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 91 157 139 474 EPSG:4326:9 182 314 279 948 EPSG:4326:10 364 629 559 1896 EPSG:4326:11 729 1258 1118 3793 EPSG:4326:12 1458 2516 2236 7587 EPSG:4326:13 2916 5032 4473 15174 EPSG:4326:14 5832 10065 8946 30349 EPSG:4326:15 11665 20130 17893 60698 EPSG:4326:16 23331 40261 35786 121397 EPSG:4326:17 46663 80523 71573 242794 EPSG:4326:18 93326 161047 143146 485589 EPSG:4326:19 186652 322095 286293 971179 EPSG:4326:20 373305 644190 572587 1942359 EPSG:4326:21 746611 1288381 1145174 3884719 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 871 1143 559 1896 EPSG:3857:12 1742 2287 1118 3793 EPSG:3857:13 3485 4574 2236 7587 EPSG:3857:14 6970 9149 4473 15174 EPSG:3857:15 13940 18299 8946 30349 EPSG:3857:16 27880 36598 17893 60698 EPSG:3857:17 55760 73196 35786 121397 EPSG:3857:18 111520 146392 71573 242794 EPSG:3857:19 223041 292785 143146 485589 EPSG:3857:20 446082 585571 286293 971179 EPSG:3857:21 892164 1171143 572587 1942359 EPSG:3857:22 1784328 2342287 1145174 3884719 EPSG:3857:23 3568657 4684575 2290349 7769438 EPSG:3857:24 7137315 9369151 4580698 15538876 EPSG:3857:25 14274631 18738303 9161397 31077753 EPSG:3857:26 28549263 37476607 18322794 62155506 EPSG:3857:27 57098527 74953214 36645588 124311012 EPSG:3857:28 114197054 149906428 73291177 248622024 EPSG:3857:29 228394108 299812857 146582354 497244049 EPSG:3857:30 456788217 599625715 293164709 994488099 Combination Tropical cyclone surge/ Sea grasses at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_sea6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Flood/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_flo_for6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tsunami/Forest at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_for6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Barcelona UA2012 - Warsaw 1.5574475003518657 41.185901499757 2.670868499618607 41.760135499971355 unep_storymap:Barcelona_ua2012_wgs_Warsaw image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 2 8 8 EPSG:4326:4 4 4 16 16 EPSG:4326:5 8 8 32 32 EPSG:4326:6 17 17 64 64 EPSG:4326:7 34 34 129 129 EPSG:4326:8 68 69 258 259 EPSG:4326:9 137 138 516 519 EPSG:4326:10 274 277 1032 1039 EPSG:4326:11 548 555 2065 2078 EPSG:4326:12 1097 1110 4131 4156 EPSG:4326:13 2195 2221 8262 8313 EPSG:4326:14 4390 4443 16525 16627 EPSG:4326:15 8781 8886 33051 33254 EPSG:4326:16 17563 17772 66103 66508 EPSG:4326:17 35127 35545 132206 133016 EPSG:4326:18 70254 71090 264412 266033 EPSG:4326:19 140508 142181 528824 532067 EPSG:4326:20 281017 284362 1057648 1064134 EPSG:4326:21 562035 568725 2115297 2128269 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 2 2 4 4 EPSG:900913:4 5 5 8 8 EPSG:900913:5 11 11 16 16 EPSG:900913:6 23 23 32 32 EPSG:900913:7 47 47 64 64 EPSG:900913:8 95 95 129 129 EPSG:900913:9 190 191 258 259 EPSG:900913:10 381 383 516 519 EPSG:900913:11 762 766 1032 1039 EPSG:900913:12 1524 1532 2065 2078 EPSG:900913:13 3048 3065 4131 4156 EPSG:900913:14 6096 6131 8262 8313 EPSG:900913:15 12193 12263 16525 16627 EPSG:900913:16 24386 24526 33051 33254 EPSG:900913:17 48773 49052 66103 66508 EPSG:900913:18 97546 98104 132206 133016 EPSG:900913:19 195093 196209 264412 266033 EPSG:900913:20 390187 392419 528824 532067 EPSG:900913:21 780375 784839 1057648 1064134 EPSG:900913:22 1560750 1569679 2115297 2128269 EPSG:900913:23 3121501 3139359 4230595 4256539 EPSG:900913:24 6243002 6278719 8461190 8513079 EPSG:900913:25 12486004 12557438 16922380 17026158 EPSG:900913:26 24972009 25114876 33844761 34052317 EPSG:900913:27 49944018 50229753 67689522 68104635 EPSG:900913:28 99888036 100459507 135379045 136209271 EPSG:900913:29 199776073 200919015 270758090 272418543 EPSG:900913:30 399552147 401838030 541516180 544837087 Combination Tropical cyclone surge/ Coral reefs at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_cor9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Annual Precipitation - Climatology (1979-2013) [mm/year] Accumulated precipitation amount over 1 year [mm/year]. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_bio10_12_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 Combination Landslides/Forest at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_lds_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mean temperatures 2015 - Central African Republic Mean observed temperatures in 2015 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2015_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Dogondoutchi_Severity_78_T50 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Severity_78_T50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 6 6 16 16 EPSG:4326:5 13 13 32 33 EPSG:4326:6 26 27 64 66 EPSG:4326:7 52 55 129 132 EPSG:4326:8 105 111 259 264 EPSG:4326:9 211 222 518 529 EPSG:4326:10 423 444 1037 1058 EPSG:4326:11 846 888 2075 2117 EPSG:4326:12 1693 1776 4151 4234 EPSG:4326:13 3387 3552 8302 8468 EPSG:4326:14 6774 7105 16605 16936 EPSG:4326:15 13549 14211 33210 33872 EPSG:4326:16 27099 28423 66421 67745 EPSG:4326:17 54199 56847 132842 135490 EPSG:4326:18 108399 113695 265685 270981 EPSG:4326:19 216798 227390 531371 541962 EPSG:4326:20 433596 454780 1062742 1083925 EPSG:4326:21 867193 909560 2125484 2167851 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 Combination Tropical cyclone surge/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_for6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Spring temperature change (°C) for the period 2040 - 2059 under the RCP 8.5 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_mam_MIDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Human Pressures in Protected Areas (2018) In an era of massive biodiversity loss, the greatest conservation success story has been the growth of protected land globally. Protected areas are the primary defense against biodiversity loss, but extensive human activity within their boundaries can undermine this. Using the most comprehensive global map of human pressure, we show that 6 million square kilometers (32.8%) of protected land is under intense human pressure. For protected areas designated before the Convention on Biological Diversity was ratified in 1992, 55% have since experienced human pressure increases. These increases were lowest in large, strict protected areas, showing that they are potentially effective, at least in some nations. Transparent reporting on human pressure within protected areas is now critical, as are global targets aimed at efforts required to halt biodiversity loss. One-third of global protected land is under intense human pressure Kendall R. Jones1,2,*, Oscar Venter3, Richard A. Fuller2,4, James R. Allan1,2, Sean L. Maxwell1,2, Pablo Jose Negret1,2, James E. M. Watson1,2,5 See all authors and affiliations Science 18 May 2018: Vol. 360, Issue 6390, pp. 788-791 DOI: 10.1126/science.aap9565 -179.99998854073996 -69.47709354376937 179.99795085448952 83.70375566498902 MapX_UNDP:int_pct_conv_in_pas_wgs image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 12 0 15 EPSG:3857:5 1 24 0 31 EPSG:3857:6 2 49 0 63 EPSG:3857:7 4 98 0 127 EPSG:3857:8 9 197 0 255 EPSG:3857:9 19 395 0 511 EPSG:3857:10 39 790 0 1023 EPSG:3857:11 78 1581 0 2047 EPSG:3857:12 157 3162 0 4095 EPSG:3857:13 314 6324 0 8191 EPSG:3857:14 628 12648 0 16383 EPSG:3857:15 1257 25297 0 32767 EPSG:3857:16 2515 50594 0 65535 EPSG:3857:17 5031 101188 0 131071 EPSG:3857:18 10062 202376 0 262142 EPSG:3857:19 20124 404753 0 524285 EPSG:3857:20 40249 809506 0 1048570 EPSG:3857:21 80498 1619012 0 2097140 EPSG:3857:22 160997 3238025 0 4194280 EPSG:3857:23 321995 6476050 0 8388560 EPSG:3857:24 643990 12952100 0 16777120 EPSG:3857:25 1287980 25904200 1 33554241 EPSG:3857:26 2575960 51808401 2 67108482 EPSG:3857:27 5151921 103616802 4 134216964 EPSG:3857:28 10303843 207233604 8 268433928 EPSG:3857:29 20607686 414467209 17 536867856 EPSG:3857:30 41215372 828934418 34 1073735712 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 1 28 0 63 EPSG:4326:6 2 56 0 127 EPSG:4326:7 4 113 0 255 EPSG:4326:8 8 226 0 511 EPSG:4326:9 17 453 0 1023 EPSG:4326:10 35 907 0 2047 EPSG:4326:11 71 1814 0 4095 EPSG:4326:12 143 3628 0 8191 EPSG:4326:13 286 7257 0 16383 EPSG:4326:14 573 14515 0 32767 EPSG:4326:15 1146 29031 0 65535 EPSG:4326:16 2292 58063 0 131071 EPSG:4326:17 4584 116127 0 262142 EPSG:4326:18 9169 232255 0 524285 EPSG:4326:19 18339 464510 0 1048570 EPSG:4326:20 36678 929021 0 2097140 EPSG:4326:21 73356 1858042 0 4194280 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 12 0 15 EPSG:900913:5 1 24 0 31 EPSG:900913:6 2 49 0 63 EPSG:900913:7 4 98 0 127 EPSG:900913:8 9 197 0 255 EPSG:900913:9 19 395 0 511 EPSG:900913:10 39 790 0 1023 EPSG:900913:11 78 1581 0 2047 EPSG:900913:12 157 3162 0 4095 EPSG:900913:13 314 6324 0 8191 EPSG:900913:14 628 12648 0 16383 EPSG:900913:15 1257 25297 0 32767 EPSG:900913:16 2515 50594 0 65535 EPSG:900913:17 5031 101188 0 131071 EPSG:900913:18 10062 202376 0 262142 EPSG:900913:19 20124 404753 0 524285 EPSG:900913:20 40249 809506 0 1048570 EPSG:900913:21 80498 1619012 0 2097140 EPSG:900913:22 160997 3238025 0 4194280 EPSG:900913:23 321995 6476050 0 8388560 EPSG:900913:24 643990 12952100 0 16777120 EPSG:900913:25 1287980 25904200 1 33554241 EPSG:900913:26 2575960 51808401 2 67108482 EPSG:900913:27 5151921 103616802 4 134216964 EPSG:900913:28 10303843 207233604 8 268433928 EPSG:900913:29 20607686 414467209 17 536867856 EPSG:900913:30 41215372 828934418 34 1073735712 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 12 0 15 EPSG:3857:5 1 24 0 31 EPSG:3857:6 2 49 0 63 EPSG:3857:7 4 98 0 127 EPSG:3857:8 9 197 0 255 EPSG:3857:9 19 395 0 511 EPSG:3857:10 39 790 0 1023 EPSG:3857:11 78 1581 0 2047 EPSG:3857:12 157 3162 0 4095 EPSG:3857:13 314 6324 0 8191 EPSG:3857:14 628 12648 0 16383 EPSG:3857:15 1257 25297 0 32767 EPSG:3857:16 2515 50594 0 65535 EPSG:3857:17 5031 101188 0 131071 EPSG:3857:18 10062 202376 0 262142 EPSG:3857:19 20124 404753 0 524285 EPSG:3857:20 40249 809506 0 1048570 EPSG:3857:21 80498 1619012 0 2097140 EPSG:3857:22 160997 3238025 0 4194280 EPSG:3857:23 321995 6476050 0 8388560 EPSG:3857:24 643990 12952100 0 16777120 EPSG:3857:25 1287980 25904200 1 33554241 EPSG:3857:26 2575960 51808401 2 67108482 EPSG:3857:27 5151921 103616802 4 134216964 EPSG:3857:28 10303843 207233604 8 268433928 EPSG:3857:29 20607686 414467209 17 536867856 EPSG:3857:30 41215372 828934418 34 1073735712 Modeled Exposures of PM2.5 - WHO The recently developed Data Integration Model for Air Quality (DIMAQ) has produced estimates based on data from ground measurements together with information from other sources including data from satellite retrievals of aerosol optical depth and chemical transport models. It provides estimates of annual exposures of PM2.5 levels at high spatial resolution (0.1° × 0.1°, which equates to approximately 11x11km at the equator) globally. The sources of data include: Ground measurements from 6 003 monitoring locations around the world, satellite remote sensing; population estimates; topography; and information on local monitoring networks and measures of specific contributors of air pollution from chemical transport models. The DIMAQ model calibrates data from these sources with ground measurements. This model has provided produced estimates of air quality, expressed in terms of median concentrations of PM2.5, for all regions of the world, including areas in which PM2.5 monitoring is not available. -180.0 -55.93333333333335 179.96666666673863 70.06666666669184 unea_pollution:who25 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 0 31 EPSG:4326:5 3 25 0 63 EPSG:4326:6 7 51 0 127 EPSG:4326:7 14 103 0 255 EPSG:4326:8 28 207 0 511 EPSG:4326:9 56 415 0 1023 EPSG:4326:10 113 830 0 2047 EPSG:4326:11 226 1660 0 4095 EPSG:4326:12 453 3320 0 8191 EPSG:4326:13 907 6641 0 16382 EPSG:4326:14 1814 13283 0 32764 EPSG:4326:15 3628 26566 0 65529 EPSG:4326:16 7257 53132 0 131059 EPSG:4326:17 14515 106265 0 262119 EPSG:4326:18 29030 212530 0 524239 EPSG:4326:19 58060 425061 0 1048478 EPSG:4326:20 116120 850123 0 2096957 EPSG:4326:21 232240 1700246 0 4193915 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 1 5 0 7 EPSG:900913:4 3 11 0 15 EPSG:900913:5 7 22 0 31 EPSG:900913:6 14 44 0 63 EPSG:900913:7 28 88 0 127 EPSG:900913:8 57 176 0 255 EPSG:900913:9 114 352 0 511 EPSG:900913:10 228 704 0 1023 EPSG:900913:11 457 1409 0 2047 EPSG:900913:12 914 2819 0 4095 EPSG:900913:13 1828 5638 0 8191 EPSG:900913:14 3657 11276 0 16382 EPSG:900913:15 7315 22553 0 32764 EPSG:900913:16 14631 45106 0 65529 EPSG:900913:17 29262 90213 0 131059 EPSG:900913:18 58525 180427 0 262119 EPSG:900913:19 117051 360854 0 524239 EPSG:900913:20 234102 721709 0 1048478 EPSG:900913:21 468205 1443418 0 2096957 EPSG:900913:22 936411 2886837 0 4193915 EPSG:900913:23 1872822 5773675 0 8387831 EPSG:900913:24 3745644 11547351 0 16775662 EPSG:900913:25 7491288 23094703 0 33551325 EPSG:900913:26 14982576 46189406 0 67102650 EPSG:900913:27 29965152 92378813 0 134205300 EPSG:900913:28 59930305 184757626 0 268410600 EPSG:900913:29 119860611 369515253 0 536821201 EPSG:900913:30 239721222 739030507 0 1073642403 frac_cats_transition_2017_2018_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_transition_2017_2018_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Combination Landslide/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_lds_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 site_0028 103.74690500699275 10.653176807974434 105.74039483165863 12.48209622646687 hotspots:site_0028 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 3 3 EPSG:3857:3 3 3 6 6 EPSG:3857:4 7 7 12 12 EPSG:3857:5 14 15 25 25 EPSG:3857:6 29 30 50 50 EPSG:3857:7 59 60 100 101 EPSG:3857:8 119 120 201 203 EPSG:3857:9 238 240 403 406 EPSG:3857:10 476 481 807 812 EPSG:3857:11 952 963 1614 1625 EPSG:3857:12 1904 1926 3228 3251 EPSG:3857:13 3809 3852 6456 6502 EPSG:3857:14 7619 7704 12913 13004 EPSG:3857:15 15238 15408 25827 26008 EPSG:3857:16 30477 30817 51654 52017 EPSG:3857:17 60955 61634 103309 104034 EPSG:3857:18 121910 123269 206618 208069 EPSG:3857:19 243820 246539 413236 416139 EPSG:3857:20 487640 493078 826472 832279 EPSG:3857:21 975280 986156 1652945 1664558 EPSG:3857:22 1950560 1972312 3305891 3329116 EPSG:3857:23 3901121 3944624 6611782 6658233 EPSG:3857:24 7802243 7889248 13223564 13316467 EPSG:3857:25 15604486 15778496 26447128 26632935 EPSG:3857:26 31208973 31556993 52894256 53265870 EPSG:3857:27 62417947 63113987 105788513 106531740 EPSG:3857:28 124835895 126227974 211577027 213063481 EPSG:3857:29 249671790 252455948 423154054 426126962 EPSG:3857:30 499343581 504911897 846308109 852253924 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 3 3 EPSG:4326:2 1 1 6 6 EPSG:4326:3 3 3 12 12 EPSG:4326:4 6 7 25 25 EPSG:4326:5 13 14 50 50 EPSG:4326:6 27 28 100 101 EPSG:4326:7 55 56 201 203 EPSG:4326:8 110 112 403 406 EPSG:4326:9 220 225 807 812 EPSG:4326:10 440 451 1614 1625 EPSG:4326:11 881 902 3228 3251 EPSG:4326:12 1763 1805 6456 6502 EPSG:4326:13 3527 3611 12913 13004 EPSG:4326:14 7055 7222 25827 26008 EPSG:4326:15 14111 14444 51654 52017 EPSG:4326:16 28223 28889 103309 104034 EPSG:4326:17 56446 57778 206618 208069 EPSG:4326:18 112893 115557 413236 416139 EPSG:4326:19 225787 231114 826472 832279 EPSG:4326:20 451574 462228 1652945 1664558 EPSG:4326:21 903149 924457 3305891 3329116 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 3 3 EPSG:3857:3 3 3 6 6 EPSG:3857:4 7 7 12 12 EPSG:3857:5 14 15 25 25 EPSG:3857:6 29 30 50 50 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38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Projected timing of annual severe bleaching (annual exceedance of 8 Degree Heating Weeks of thermal stress in reef areas) under SSP5-8.5 using CMIP6 models The data and complementary report have two purposes, and are intended for use by the global coral reef scientific and management community, which had these 2 objectives. Objective 1. To present projections of coral bleaching conditions (i.e., exposure to the primary climate threat to coral reefs) and potential adaptation at a spatial scale that enables use of the data in management and conservation planning and in support of other decisions influencing coral reefs and reef use. Objective 2. To evaluate the implications of the Paris Agreement as well as failure to achieve its goal, by comparing the projected timing of annual severe bleaching between Shared Socioeconomic Pathways SSP5-8.5 and SSP2-4.5. Data source used: Intergovernmental Panel on Climate Change (IPCC) Coupled Model Interpolation Project Phase 6 (CMIP6) model outputs for sea surface temperature (https://www.ipcc-data.org/), combined with United States National Oceanic and Atmospheric Administration (NOAA) CoralTemp data from NOAA Coral Reef Watch (https://www.coralreefwatch.noaa.gov/product/5km/index_5km_sst.php). -180.0 -90.0 180.0 90.0 wesr_climat:asb_year_0_ssp585 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Low Elevation Coastal Zone (LECZ) of the Adriatic sub-region LECZ, i.e. areas at less then 5 m above sea level with highest risk to be impacted by flooding. 12.114305555555555 39.64486111111111 20.265138888888888 45.89486111111111 medqsr:below_5m_asl image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml 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224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Change in cumulative human impact to marine ecosystems Human pressures on the ocean are thought to be increasing globally, yet we know little about their patterns of cumulative change, which pressures are most responsible for change, and which places are experiencing the greatest increases. Managers and policymakers require such information to make strategic decisions and monitor progress towards management objectives. Here we calculate and map recent change over 5 years in cumulative impacts to marine ecosystems globally from fishing, climate change, and ocean- and land-based stressors. Nearly 66% of the ocean and 77% of national jurisdictions show increased human impact, driven mostly by climate change pressures. Five percent of the ocean is heavily impacted with increasing pressures, requiring management attention. Ten percent has very low impact with decreasing pressures. Our results provide large-scale guidance about where to prioritize management efforts and affirm the importance of addressing climate change to maintain and improve the condition of marine ecosystems. Authors: Halpern, B. S. et al. Spatial and temporal changes in cumulative human impacts on the world’s ocean. Nat. Commun. 6:7615 doi: 10.1038/ncomms8615 (2015). Source: https://www.nature.com/articles/ncomms8615#s1 -180.0 -79.0 180.0 84.0 MapX_UNDP:global_cumul_impact_2013_minus_2008_wgs image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 1 55 0 63 EPSG:3857:7 3 111 0 127 EPSG:3857:8 7 223 0 255 EPSG:3857:9 15 446 0 511 EPSG:3857:10 31 893 0 1023 EPSG:3857:11 62 1786 0 2047 EPSG:3857:12 125 3573 0 4095 EPSG:3857:13 251 7147 0 8191 EPSG:3857:14 502 14294 0 16383 EPSG:3857:15 1005 28589 0 32767 EPSG:3857:16 2011 57179 0 65535 EPSG:3857:17 4023 114358 0 131071 EPSG:3857:18 8047 228717 0 262143 EPSG:3857:19 16095 457434 0 524287 EPSG:3857:20 32191 914868 0 1048575 EPSG:3857:21 64382 1829736 0 2097151 EPSG:3857:22 128764 3659472 0 4194304 EPSG:3857:23 257528 7318945 0 8388608 EPSG:3857:24 515056 14637891 0 16777215 EPSG:3857:25 1030113 29275783 0 33554431 EPSG:3857:26 2060227 58551567 0 67108863 EPSG:3857:27 4120454 117103134 0 134217727 EPSG:3857:28 8240909 234206268 0 268435456 EPSG:3857:29 16481819 468412536 0 536870911 EPSG:3857:30 32963639 936825073 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 30 0 63 EPSG:4326:6 2 60 0 127 EPSG:4326:7 4 120 0 255 EPSG:4326:8 8 240 0 511 EPSG:4326:9 17 480 0 1023 EPSG:4326:10 34 961 0 2047 EPSG:4326:11 68 1922 0 4095 EPSG:4326:12 136 3845 0 8191 EPSG:4326:13 273 7691 0 16383 EPSG:4326:14 546 15382 0 32767 EPSG:4326:15 1092 30765 0 65535 EPSG:4326:16 2184 61531 0 131071 EPSG:4326:17 4369 123062 0 262143 EPSG:4326:18 8738 246124 0 524287 EPSG:4326:19 17476 492248 0 1048575 EPSG:4326:20 34952 984496 0 2097151 EPSG:4326:21 69905 1968992 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 13 0 15 EPSG:900913:5 0 27 0 31 EPSG:900913:6 1 55 0 63 EPSG:900913:7 3 111 0 127 EPSG:900913:8 7 223 0 255 EPSG:900913:9 15 446 0 511 EPSG:900913:10 31 893 0 1023 EPSG:900913:11 62 1786 0 2047 EPSG:900913:12 125 3573 0 4095 EPSG:900913:13 251 7147 0 8191 EPSG:900913:14 502 14294 0 16383 EPSG:900913:15 1005 28589 0 32767 EPSG:900913:16 2011 57179 0 65535 EPSG:900913:17 4023 114358 0 131071 EPSG:900913:18 8047 228717 0 262143 EPSG:900913:19 16095 457434 0 524287 EPSG:900913:20 32191 914868 0 1048575 EPSG:900913:21 64382 1829736 0 2097151 EPSG:900913:22 128764 3659472 0 4194303 EPSG:900913:23 257528 7318945 0 8388607 EPSG:900913:24 515056 14637891 0 16777215 EPSG:900913:25 1030113 29275783 0 33554431 EPSG:900913:26 2060227 58551567 0 67108863 EPSG:900913:27 4120454 117103134 0 134217727 EPSG:900913:28 8240909 234206268 0 268435455 EPSG:900913:29 16481819 468412536 0 536870911 EPSG:900913:30 32963639 936825073 0 1073741823 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 1 55 0 63 EPSG:3857:7 3 111 0 127 EPSG:3857:8 7 223 0 255 EPSG:3857:9 15 446 0 511 EPSG:3857:10 31 893 0 1023 EPSG:3857:11 62 1786 0 2047 EPSG:3857:12 125 3573 0 4095 EPSG:3857:13 251 7147 0 8191 EPSG:3857:14 502 14294 0 16383 EPSG:3857:15 1005 28589 0 32767 EPSG:3857:16 2011 57179 0 65535 EPSG:3857:17 4023 114358 0 131071 EPSG:3857:18 8047 228717 0 262143 EPSG:3857:19 16095 457434 0 524287 EPSG:3857:20 32191 914868 0 1048575 EPSG:3857:21 64382 1829736 0 2097152 EPSG:3857:22 128764 3659472 0 4194304 EPSG:3857:23 257528 7318945 0 8388607 EPSG:3857:24 515056 14637891 0 16777215 EPSG:3857:25 1030113 29275783 0 33554431 EPSG:3857:26 2060227 58551567 0 67108863 EPSG:3857:27 4120454 117103134 0 134217728 EPSG:3857:28 8240909 234206268 0 268435455 EPSG:3857:29 16481819 468412536 0 536870911 EPSG:3857:30 32963639 936825073 0 1073741824 Total built-up surface in 1975 The spatial raster dataset depicts the distribution of built-up surfaces, expressed as number of square metres. Credits: Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA -23.264767173073253 16.259077704195818 52.90404528839234 51.21395264452012 paprac:ghs_built_surf_100m_1975 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 5 EPSG:4326:3 1 3 6 10 EPSG:4326:4 3 6 13 20 EPSG:4326:5 6 13 27 41 EPSG:4326:6 13 26 55 82 EPSG:4326:7 27 52 111 165 EPSG:4326:8 55 104 222 331 EPSG:4326:9 110 209 445 662 EPSG:4326:10 220 419 891 1324 EPSG:4326:11 441 839 1783 2649 EPSG:4326:12 882 1678 3566 5299 EPSG:4326:13 1765 3356 7133 10599 EPSG:4326:14 3530 6712 14266 21199 EPSG:4326:15 7060 13424 28532 42398 EPSG:4326:16 14121 26848 57065 84797 EPSG:4326:17 28243 53696 114131 169595 EPSG:4326:18 56486 107393 228262 339191 EPSG:4326:19 112972 214786 456524 678382 EPSG:4326:20 225945 429572 913048 1356764 EPSG:4326:21 451890 859144 1826097 2713528 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 5 EPSG:3857:4 5 7 6 10 EPSG:3857:5 10 14 13 20 EPSG:3857:6 21 29 27 41 EPSG:3857:7 42 58 55 82 EPSG:3857:8 85 116 111 165 EPSG:3857:9 170 232 222 331 EPSG:3857:10 341 465 445 662 EPSG:3857:11 683 930 891 1324 EPSG:3857:12 1367 1860 1783 2649 EPSG:3857:13 2734 3720 3566 5299 EPSG:3857:14 5469 7441 7133 10599 EPSG:3857:15 10938 14883 14266 21199 EPSG:3857:16 21877 29767 28532 42398 EPSG:3857:17 43755 59535 57065 84797 EPSG:3857:18 87511 119070 114131 169595 EPSG:3857:19 175023 238140 228262 339191 EPSG:3857:20 350047 476281 456524 678382 EPSG:3857:21 700094 952562 913048 1356764 EPSG:3857:22 1400188 1905125 1826097 2713528 EPSG:3857:23 2800377 3810250 3652195 5427057 EPSG:3857:24 5600754 7620500 7304391 10854115 EPSG:3857:25 11201508 15241001 14608782 21708230 EPSG:3857:26 22403016 30482002 29217565 43416460 EPSG:3857:27 44806032 60964005 58435130 86832921 EPSG:3857:28 89612065 121928011 116870260 173665843 EPSG:3857:29 179224131 243856022 233740520 347331686 EPSG:3857:30 358448262 487712044 467481041 694663373 Areas of Global Significance for Biodiversity Conservation and Water Provision <span style="font-size:1em"> This map is the result of a global joint optimization of valuable biodiversity and water regulation. This analysis collated distribution data for over 180000 terrestrial vertebrate and plant species globally, removing unsuitable areas using information on species' habitat preferences and species' known altitudinal limits or, where unknown, by removing anthropogenically modified land. <br /> <br /> Given existing biases in taxonomic coverage for plant species, we calculated 10 representative sets of species, containing approximately 10% of species of each taxonomic group. For water we took potential water regulation outputs from the WaterWorld model normalized by water basin. We then determined those areas globally that jointly contributed the most to biodiversity and water conservation if up to 10%, 20%, or 100% of the Earth were to be protected. <br> <br> <u>References:</u> <ul> <li> Jung, M., et al. (2020). Areas of global importance for terrestrial biodiversity, carbon, and water. BioRxiv. <a href="https://www.biorxiv.org/content/10.1101/2020.04.16.021444v1" target="_blank">biorxiv.org/content/10.1101/2020.04.16.021444v1</a>. </li> </ul> </span> -179.995201157628 -84.69466806618583 179.8859620772232 85.91771612300938 MapX_UNDP:conservation_biodiversity_water_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 126 0 127 EPSG:3857:8 0 253 0 255 EPSG:3857:9 0 506 0 511 EPSG:3857:10 0 1012 0 1023 EPSG:3857:11 0 2025 0 2047 EPSG:3857:12 0 4050 0 4094 EPSG:3857:13 0 8101 0 8189 EPSG:3857:14 0 16202 0 16378 EPSG:3857:15 0 32404 0 32757 EPSG:3857:16 0 64809 0 65515 EPSG:3857:17 0 129619 1 131030 EPSG:3857:18 0 259238 3 262060 EPSG:3857:19 0 518476 6 524121 EPSG:3857:20 0 1036953 13 1048243 EPSG:3857:21 0 2073906 27 2096487 EPSG:3857:22 -1 4147812 55 4192975 EPSG:3857:23 -1 8295624 111 8385950 EPSG:3857:24 0 16591249 223 16771901 EPSG:3857:25 0 33182499 447 33543802 EPSG:3857:26 0 66364998 894 67087605 EPSG:3857:27 0 132729997 1789 134175211 EPSG:3857:28 -1 265459994 3578 268350423 EPSG:3857:29 0 530919989 7156 536700846 EPSG:3857:30 0 1061839978 14313 1073401692 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 62 0 127 EPSG:4326:7 2 124 0 255 EPSG:4326:8 5 248 0 511 EPSG:4326:9 11 496 0 1023 EPSG:4326:10 23 993 0 2047 EPSG:4326:11 46 1987 0 4094 EPSG:4326:12 92 3975 0 8189 EPSG:4326:13 185 7950 0 16378 EPSG:4326:14 371 15901 0 32757 EPSG:4326:15 743 31802 0 65515 EPSG:4326:16 1486 63604 1 131030 EPSG:4326:17 2972 127208 3 262060 EPSG:4326:18 5945 254417 6 524121 EPSG:4326:19 11890 508835 13 1048243 EPSG:4326:20 23781 1017670 27 2096487 EPSG:4326:21 47562 2035340 55 4192975 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 126 0 127 EPSG:3857:8 0 253 0 255 EPSG:3857:9 0 506 0 511 EPSG:3857:10 0 1012 0 1023 EPSG:3857:11 0 2025 0 2047 EPSG:3857:12 0 4050 0 4094 EPSG:3857:13 0 8101 0 8189 EPSG:3857:14 0 16202 0 16378 EPSG:3857:15 0 32404 0 32757 EPSG:3857:16 0 64809 0 65515 EPSG:3857:17 0 129619 1 131030 EPSG:3857:18 0 259238 3 262060 EPSG:3857:19 0 518476 6 524121 EPSG:3857:20 0 1036953 13 1048243 EPSG:3857:21 -1 2073906 27 2096487 EPSG:3857:22 -1 4147812 55 4192975 EPSG:3857:23 0 8295624 111 8385950 EPSG:3857:24 0 16591249 223 16771901 EPSG:3857:25 0 33182499 447 33543802 EPSG:3857:26 0 66364998 894 67087605 EPSG:3857:27 -1 132729997 1789 134175211 EPSG:3857:28 0 265459994 3578 268350423 EPSG:3857:29 0 530919989 7156 536700846 EPSG:3857:30 -1 1061839978 14313 1073401692 International Boundaries Lines Level 0 - UNGIWG International boundary resources are prepared by United Nations Cartographic Section. The 1:1million dataset derived initially from VMAP0 has been corrected to better reflect the cartographic practise of UN Cartographic Section. -133.207870483398 -52.3656349182129 142.383773803711 70.7053146362305 grid_data_core_pro:_2012_ungiwg_bnd_ln_01 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 1 7 EPSG:4326:3 0 6 2 14 EPSG:4326:4 1 12 4 28 EPSG:4326:5 3 25 8 57 EPSG:4326:6 6 50 16 114 EPSG:4326:7 13 101 33 229 EPSG:4326:8 27 202 66 458 EPSG:4326:9 54 404 133 917 EPSG:4326:10 109 809 266 1834 EPSG:4326:11 219 1619 532 3668 EPSG:4326:12 439 3239 1064 7336 EPSG:4326:13 878 6479 2129 14672 EPSG:4326:14 1756 12958 4259 29344 EPSG:4326:15 3512 25916 8518 58688 EPSG:4326:16 7024 51833 17036 117376 EPSG:4326:17 14049 103667 34072 234752 EPSG:4326:18 28099 207334 68145 469505 EPSG:4326:19 56199 414669 136291 939010 EPSG:4326:20 112399 829339 272583 1878021 EPSG:4326:21 224799 1658679 545167 3756043 EPSG:900913 Frequency of Landslides Triggered By Precipitations This dataset includes an estimate of the annual frequency of landslide triggered by precipitations. It depends on the combination of trigger and susceptibility defined by six parameters: slope factor, lithological (or geological) conditions, soil moisture condition, vegetation cover, precipitation and seismic conditions. Unit is expected annual probability and percentage of pixel of occurrence of a potentially destructive landslide event x 1000000. This product was designed by International Centre for Geohazards (NGI) for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards (NGI). -180.0 -56.01339243789985 179.9916666666665 89.99494089543342 wesr_risk:ls_pr image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 44 0 63 EPSG:3857:7 0 88 0 127 EPSG:3857:8 0 176 0 255 EPSG:3857:9 0 352 0 511 EPSG:3857:10 0 705 0 1023 EPSG:3857:11 0 1410 0 2047 EPSG:3857:12 0 2820 0 4095 EPSG:3857:13 0 5641 0 8191 EPSG:3857:14 0 11283 0 16383 EPSG:3857:15 0 22566 0 32767 EPSG:3857:16 0 45132 0 65534 EPSG:3857:17 0 90265 0 131068 EPSG:3857:18 0 180531 0 262137 EPSG:3857:19 0 361063 0 524275 EPSG:3857:20 0 722126 0 1048551 EPSG:3857:21 0 1444252 0 2097103 EPSG:3857:22 -1 2888504 0 4194206 EPSG:3857:23 -1 5777009 0 8388413 EPSG:3857:24 0 11554019 0 16776827 EPSG:3857:25 0 23108038 0 33553655 EPSG:3857:26 0 46216077 0 67107310 EPSG:3857:27 0 92432154 0 134214621 EPSG:3857:28 -1 184864308 0 268429242 EPSG:3857:29 0 369728616 0 536858484 EPSG:3857:30 0 739457232 0 1073716968 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 0 25 0 63 EPSG:4326:6 0 51 0 127 EPSG:4326:7 0 103 0 255 EPSG:4326:8 0 207 0 511 EPSG:4326:9 0 415 0 1023 EPSG:4326:10 0 830 0 2047 EPSG:4326:11 0 1661 0 4095 EPSG:4326:12 0 3322 0 8191 EPSG:4326:13 0 6645 0 16383 EPSG:4326:14 0 13290 0 32767 EPSG:4326:15 0 26580 0 65534 EPSG:4326:16 1 53161 0 131068 EPSG:4326:17 3 106323 0 262137 EPSG:4326:18 7 212647 0 524275 EPSG:4326:19 14 425294 0 1048551 EPSG:4326:20 29 850589 0 2097103 EPSG:4326:21 58 1701179 0 4194206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 44 0 63 EPSG:3857:7 0 88 0 127 EPSG:3857:8 0 176 0 255 EPSG:3857:9 0 352 0 511 EPSG:3857:10 0 705 0 1023 EPSG:3857:11 0 1410 0 2047 EPSG:3857:12 0 2820 0 4095 EPSG:3857:13 0 5641 0 8191 EPSG:3857:14 0 11283 0 16383 EPSG:3857:15 0 22566 0 32767 EPSG:3857:16 0 45132 0 65534 EPSG:3857:17 0 90265 0 131068 EPSG:3857:18 0 180531 0 262137 EPSG:3857:19 0 361063 0 524275 EPSG:3857:20 0 722126 0 1048551 EPSG:3857:21 -1 1444252 0 2097103 EPSG:3857:22 -1 2888504 0 4194206 EPSG:3857:23 0 5777009 0 8388413 EPSG:3857:24 0 11554019 0 16776827 EPSG:3857:25 0 23108038 0 33553655 EPSG:3857:26 0 46216077 0 67107310 EPSG:3857:27 -1 92432154 0 134214621 EPSG:3857:28 0 184864308 0 268429242 EPSG:3857:29 0 369728616 0 536858484 EPSG:3857:30 -1 739457232 0 1073716968 Self-calibrating Palmer Drought Severity Index (scPDSI) 2012 (CRU) This layer shows the average values for 2012 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_12_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Phospate (winter) - WOA13 World Ocean Atlas 2013 (WOA13) is a long-term set of objectively analyzed climatologies of temperature, salinity, oxygen, phosphate, silicate, and nitrate for annual, seasonal, and monthly periods for the World Ocean. Data (at surface) are expressed in µmol/l -180.0 -78.0 180.0 90.0 unea_pollution:ph_win image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 0 119 0 255 EPSG:4326:8 0 238 0 511 EPSG:4326:9 0 477 0 1023 EPSG:4326:10 0 955 0 2047 EPSG:4326:11 0 1911 0 4095 EPSG:4326:12 0 3822 0 8191 EPSG:4326:13 0 7645 0 16383 EPSG:4326:14 0 15291 0 32767 EPSG:4326:15 0 30583 0 65535 EPSG:4326:16 0 61166 0 131071 EPSG:4326:17 0 122333 0 262143 EPSG:4326:18 0 244667 0 524287 EPSG:4326:19 0 489335 0 1048575 EPSG:4326:20 0 978670 0 2097151 EPSG:4326:21 0 1957341 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 6 0 7 EPSG:900913:4 0 13 0 15 EPSG:900913:5 0 27 0 31 EPSG:900913:6 0 54 0 63 EPSG:900913:7 0 109 0 127 EPSG:900913:8 0 219 0 255 EPSG:900913:9 0 439 0 511 EPSG:900913:10 0 879 0 1023 EPSG:900913:11 0 1758 0 2047 EPSG:900913:12 0 3516 0 4095 EPSG:900913:13 0 7033 0 8191 EPSG:900913:14 0 14066 0 16383 EPSG:900913:15 0 28132 0 32767 EPSG:900913:16 0 56265 0 65535 EPSG:900913:17 0 112531 0 131071 EPSG:900913:18 0 225062 0 262143 EPSG:900913:19 0 450124 0 524287 EPSG:900913:20 0 900249 0 1048575 EPSG:900913:21 0 1800498 0 2097151 EPSG:900913:22 0 3600997 0 4194303 EPSG:900913:23 0 7201994 0 8388607 EPSG:900913:24 0 14403989 0 16777215 EPSG:900913:25 0 28807979 0 33554431 EPSG:900913:26 0 57615958 0 67108863 EPSG:900913:27 0 115231917 0 134217727 EPSG:900913:28 0 230463834 0 268435455 EPSG:900913:29 0 460927668 0 536870911 EPSG:900913:30 0 921855337 0 1073741823 Travel time composite The problem of maternal mortality is a recurring problem in Sub-Saharan Africa and the poorest population and residing away from health centers is the most affected. AccessMod is a computer program designed to help these countries examine the geographical aspect of their health system. And so to map the physical accessibility in terms of travel time to the health center. The accessibility map helps to guide decision-makers by showing them areas of low access, ie places where the population must walk to reach health centers. 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EPSG:4326:18 96802 165544 236579 334907 EPSG:4326:19 193605 331089 473158 669815 EPSG:4326:20 387211 662179 946316 1339630 EPSG:4326:21 774422 1324358 1892633 2679261 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 3 4 3 5 EPSG:3857:4 6 9 7 10 EPSG:3857:5 13 18 14 20 EPSG:3857:6 27 36 28 40 EPSG:3857:7 55 72 57 81 EPSG:3857:8 110 145 115 163 EPSG:3857:9 221 290 231 327 EPSG:3857:10 443 581 462 654 EPSG:3857:11 886 1162 924 1308 EPSG:3857:12 1772 2325 1848 2616 EPSG:3857:13 3544 4650 3696 5232 EPSG:3857:14 7089 9301 7393 10465 EPSG:3857:15 14179 18602 14786 20931 EPSG:3857:16 28358 37205 29572 41863 EPSG:3857:17 56717 74410 59144 83726 EPSG:3857:18 113434 148820 118289 167453 EPSG:3857:19 226868 297641 236579 334907 EPSG:3857:20 453737 595282 473158 669815 EPSG:3857:21 907474 1190565 946316 1339630 EPSG:3857:22 1814949 2381131 1892633 2679261 EPSG:3857:23 3629899 4762262 3785267 5358523 EPSG:3857:24 7259798 9524525 7570535 10717047 EPSG:3857:25 14519596 19049050 15141070 21434095 EPSG:3857:26 29039192 38098101 30282141 42868191 EPSG:3857:27 58078384 76196202 60564283 85736383 EPSG:3857:28 116156768 152392404 121128566 171472766 EPSG:3857:29 232313536 304784808 242257133 342945533 EPSG:3857:30 464627073 609569616 484514267 685891067 World Multi Study Crop Mask -180.0 -90.0 180.0 90.0 MAPX:wld_multi_study_crop_mask image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 zambia_remote_site_screening_res50 21.994957999999993 -18.079247604999956 33.70545799999999 -8.192247604999954 mapx_chemobs:zambia_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 8 9 EPSG:3857:5 16 17 17 18 EPSG:3857:6 33 35 35 37 EPSG:3857:7 66 70 71 75 EPSG:3857:8 133 141 143 151 EPSG:3857:9 267 282 287 303 EPSG:3857:10 535 564 574 607 EPSG:3857:11 1070 1128 1149 1215 EPSG:3857:12 2141 2257 2298 2431 EPSG:3857:13 4283 4514 4596 4862 EPSG:3857:14 8566 9028 9193 9725 EPSG:3857:15 17132 18057 18386 19451 EPSG:3857:16 34264 36115 36772 38903 EPSG:3857:17 68528 72230 73544 77807 EPSG:3857:18 137057 144460 147088 155615 EPSG:3857:19 274115 288921 294176 311231 EPSG:3857:20 548231 577843 588352 622462 EPSG:3857:21 1096462 1155687 1176705 1244924 EPSG:3857:22 2192925 2311375 2353411 2489849 EPSG:3857:23 4385850 4622751 4706823 4979698 EPSG:3857:24 8771701 9245502 9413647 9959396 EPSG:3857:25 17543403 18491004 18827294 19918792 EPSG:3857:26 35086807 36982008 37654589 39837584 EPSG:3857:27 70173615 73964017 75309178 79675169 EPSG:3857:28 140347231 147928035 150618357 159350339 EPSG:3857:29 280694462 295856070 301236714 318700678 EPSG:3857:30 561388925 591712140 602473429 637401356 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 8 9 EPSG:4326:4 8 9 17 18 EPSG:4326:5 17 19 35 37 EPSG:4326:6 34 38 71 75 EPSG:4326:7 69 76 143 151 EPSG:4326:8 139 153 287 303 EPSG:4326:9 279 307 574 607 EPSG:4326:10 558 614 1149 1215 EPSG:4326:11 1117 1229 2298 2431 EPSG:4326:12 2234 2459 4596 4862 EPSG:4326:13 4468 4918 9193 9725 EPSG:4326:14 8937 9837 18386 19451 EPSG:4326:15 17875 19675 36772 38903 EPSG:4326:16 35750 39350 73544 77807 EPSG:4326:17 71501 78700 147088 155615 EPSG:4326:18 143002 157401 294176 311231 EPSG:4326:19 286005 314803 588352 622462 EPSG:4326:20 572011 629607 1176705 1244924 EPSG:4326:21 1144022 1259214 2353411 2489849 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 8 9 EPSG:3857:5 16 17 17 18 EPSG:3857:6 33 35 35 37 EPSG:3857:7 66 70 71 75 EPSG:3857:8 133 141 143 151 EPSG:3857:9 267 282 287 303 EPSG:3857:10 535 564 574 607 EPSG:3857:11 1070 1128 1149 1215 EPSG:3857:12 2141 2257 2298 2431 EPSG:3857:13 4283 4514 4596 4862 EPSG:3857:14 8566 9028 9193 9725 EPSG:3857:15 17132 18057 18386 19451 EPSG:3857:16 34264 36115 36772 38903 EPSG:3857:17 68528 72230 73544 77807 EPSG:3857:18 137057 144460 147088 155615 EPSG:3857:19 274115 288921 294176 311231 EPSG:3857:20 548231 577843 588352 622462 EPSG:3857:21 1096462 1155687 1176705 1244924 EPSG:3857:22 2192925 2311375 2353411 2489849 EPSG:3857:23 4385850 4622751 4706823 4979698 EPSG:3857:24 8771701 9245502 9413647 9959396 EPSG:3857:25 17543403 18491004 18827294 19918792 EPSG:3857:26 35086807 36982008 37654589 39837584 EPSG:3857:27 70173615 73964017 75309178 79675169 EPSG:3857:28 140347231 147928035 150618357 159350339 EPSG:3857:29 280694462 295856070 301236714 318700678 EPSG:3857:30 561388925 591712140 602473429 637401356 Mean temperatures 2009 - Central African Republic Mean observed temperatures in 2009 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2009_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Year precipitations 2004 - Central African Republic Total precipitations observed in 2004 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2004_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Mean temperatures 2016 - Central African Republic Mean observed temperatures in 2016 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2016_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Global Terrestrial Human Footprint (HFP) - 2010 (subset) This update to the Human Footprint (HFP) provides a measure of the direct and indirect human pressures on the environment globally in years 2000, 2005, 2010, and 2013. Per the orinal Human Footprint, this dataset is derived from remotely-sensed and bottom-up survey information compiled on eight measured variables. This represents not only the most current information of its type, but also the first temporally-consistent set of Human Footprint maps. Data on human pressures were acquired or developed for: 1) built environments, 2) population density, 3) electric infrastructure, 4) crop lands, 5) pasture lands, 6) roads, 7) railways, and 8) navigable waterways. This update incorporates updated and higher resolution population, nightlights, pasture, road, and railway input datasets. The Human Footprint maps find a range of uses as proxies for human disturbance of natural systems and can provide an increased understanding of the human pressures that drive macro-ecological patterns, as well as for tracking environmental change and informing conservation science and application. HFP values range from 0 (no human impact) to 50 (heavily human impacted).<br><br>See: <a href="https://www.nature.com/articles/ncomms12558" target="_blank">Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11</a>.<br/><br>This dataset can be downloaded uniquly from UN Biodiversity Lab. <br> Updated data is made available only to FIP pilot countires at present - rasters are clipped to other FIP data extents. -81.71613729134685 -20.618092964606667 153.42326553667291 26.043388408099844 MapX_UNDP:hfp2010_merisINT_subsetsGlobal image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27854 36605 17892 60697 EPSG:3857:17 55709 73210 35784 121395 EPSG:3857:18 111418 146420 71568 242791 EPSG:3857:19 222837 292841 143136 485582 EPSG:3857:20 445675 585682 286272 971165 EPSG:3857:21 891350 1171364 572544 1942331 EPSG:3857:22 1782701 2342729 1145089 3884662 EPSG:3857:23 3565403 4685458 2290179 7769325 EPSG:3857:24 7130806 9370916 4580359 15538650 EPSG:3857:25 14261613 18741832 9160719 31077300 EPSG:3857:26 28523227 37483665 18321439 62154601 EPSG:3857:27 57046454 74967331 36642879 124309203 EPSG:3857:28 114092909 149934663 73285759 248618406 EPSG:3857:29 228185818 299869326 146571519 497236812 EPSG:3857:30 456371636 599738652 293143038 994473625 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 90 157 139 474 EPSG:4326:9 181 314 279 948 EPSG:4326:10 363 629 559 1896 EPSG:4326:11 727 1258 1118 3793 EPSG:4326:12 1455 2517 2236 7587 EPSG:4326:13 2910 5034 4473 15174 EPSG:4326:14 5821 10068 8946 30348 EPSG:4326:15 11642 20137 17892 60697 EPSG:4326:16 23285 40274 35784 121395 EPSG:4326:17 46571 80549 71568 242791 EPSG:4326:18 93143 161099 143136 485582 EPSG:4326:19 186287 322198 286272 971165 EPSG:4326:20 372574 644397 572544 1942331 EPSG:4326:21 745148 1288794 1145089 3884662 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 870 1143 559 1896 EPSG:3857:12 1740 2287 1118 3793 EPSG:3857:13 3481 4575 2236 7587 EPSG:3857:14 6963 9151 4473 15174 EPSG:3857:15 13927 18302 8946 30348 EPSG:3857:16 27854 36605 17892 60697 EPSG:3857:17 55709 73210 35784 121395 EPSG:3857:18 111418 146420 71568 242791 EPSG:3857:19 222837 292841 143136 485582 EPSG:3857:20 445675 585682 286272 971165 EPSG:3857:21 891350 1171364 572544 1942331 EPSG:3857:22 1782701 2342729 1145089 3884662 EPSG:3857:23 3565403 4685458 2290179 7769325 EPSG:3857:24 7130806 9370916 4580359 15538650 EPSG:3857:25 14261613 18741832 9160719 31077300 EPSG:3857:26 28523227 37483665 18321439 62154601 EPSG:3857:27 57046454 74967331 36642879 124309203 EPSG:3857:28 114092909 149934663 73285759 248618406 EPSG:3857:29 228185818 299869326 146571519 497236812 EPSG:3857:30 456371636 599738652 293143038 994473625 International Boundaries Lines Level 0 - UNmap UNmap is a global multi-scale geospatial dataset that is designed to serve as a base geodatabase for map production and web mapping to meet the needs of the United Nations Secretariat in supporting the work of the Security Council and field operations. It consists of basic geospatial information at different scales. -142.412094116211 -55.743522644043 142.429565429688 70.7178955078125 grid_data_core_pro:ungiwg_bnd_ln_01m image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 1 14 EPSG:4326:4 1 12 3 28 EPSG:4326:5 3 25 6 57 EPSG:4326:6 6 51 13 114 EPSG:4326:7 13 103 26 229 EPSG:4326:8 27 207 53 458 EPSG:4326:9 54 414 106 917 EPSG:4326:10 109 829 213 1834 EPSG:4326:11 219 1658 427 3668 EPSG:4326:12 438 3316 855 7337 EPSG:4326:13 877 6632 1710 14674 EPSG:4326:14 1755 13265 3421 29348 EPSG:4326:15 3510 26531 6842 58696 EPSG:4326:16 7020 53063 13685 117393 EPSG:4326:17 14040 106127 27370 234786 EPSG:4326:18 28081 212254 54741 469572 EPSG:4326:19 56163 424508 109482 939144 EPSG:4326:20 112326 849017 218965 1878288 EPSG:4326:21 224652 1698035 437930 3756576 EPSG:900913 2011-2020 Average year precipitations change since previous decade (2001-2010) Average year precipitations anomalies in mm across the period 2011-2020 calculated over the average precipitations per year in the period 2001-2010. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_11_20_anom_01_10 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone/Forest at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcw_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Gridded Livestock of the World – Sheep This updated layer of The Gridded Livestock of the World (GLW)database provided modelled livestock densities of the world, adjusted to match official (FAOSTAT)national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 565 km at the equator).Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analyticalprocedure has been revised and extended to include a more systematic assessment of model accuracy and therepresentation of uncertainties associated with the predictions.<br><br>For further details on mapping methods see: Robinson, T.P., Wint, G.R.W., Conchedda, G., Van Boeckel, T.P., Ercoli, V., Palamara, E., Cinardi, G., D’Aietti, L., Hay, S.I., Gilbert, M., 2014. Mapping the Global Distribution of Livestock. PLoS ONE 9, e96084. <a href=\"https://doi.org/10.1371/journal.pone.0096084\"target=_blank>https://doi.org/10.1371/journal.pone.0096084</a><br/><br>These digital layers are made publically available via the Livestock Geo-Wiki (<a href=\"http://www.livestock.geo-wiki.org\"target=_blank>livestock.geo-wiki.org</a><br/> -180.0 -90.0 180.0 90.0 MapX_UNDP:Glb_SHAD_2006 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Forest opportunities to reduce flood risk This dataset shows the areas where forest restoration (open and closed forests, as well as woodlands) could be undertaken for reducing flood exposure. Restoration opportunities areas were considered for areas where the ecosystem coverage was below the median. -180.0 -90.0 180.0 90.0 ECO-DRR:Forest_flood_all image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 botswana_remote_site_screening_res50 19.99936526400007 -26.90059308399997 29.36086526400007 -17.77859308399997 mapx_chemobs:botswana_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 9 8 9 EPSG:3857:5 17 18 17 18 EPSG:3857:6 35 36 35 37 EPSG:3857:7 70 73 71 74 EPSG:3857:8 140 147 142 148 EPSG:3857:9 281 295 284 297 EPSG:3857:10 563 591 568 595 EPSG:3857:11 1126 1182 1137 1191 EPSG:3857:12 2253 2365 2275 2382 EPSG:3857:13 4507 4731 4551 4764 EPSG:3857:14 9014 9463 9102 9528 EPSG:3857:15 18028 18927 18204 19056 EPSG:3857:16 36057 37855 36408 38112 EPSG:3857:17 72115 75711 72817 76225 EPSG:3857:18 144230 151422 145635 152451 EPSG:3857:19 288461 302844 291270 304903 EPSG:3857:20 576923 605689 582540 609807 EPSG:3857:21 1153846 1211379 1165080 1219615 EPSG:3857:22 2307693 2422759 2330161 2439230 EPSG:3857:23 4615387 4845518 4660322 4878461 EPSG:3857:24 9230775 9691037 9320645 9756923 EPSG:3857:25 18461551 19382075 18641291 19513846 EPSG:3857:26 36923102 38764150 37282583 39027693 EPSG:3857:27 73846204 77528300 74565167 78055387 EPSG:3857:28 147692408 155056600 149130335 156110775 EPSG:3857:29 295384816 310113201 298260671 312221551 EPSG:3857:30 590769633 620226403 596521342 624443103 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 5 8 9 EPSG:4326:4 9 10 17 18 EPSG:4326:5 19 20 35 37 EPSG:4326:6 38 41 71 74 EPSG:4326:7 76 83 142 148 EPSG:4326:8 153 166 284 297 EPSG:4326:9 306 332 568 595 EPSG:4326:10 613 665 1137 1191 EPSG:4326:11 1226 1330 2275 2382 EPSG:4326:12 2452 2660 4551 4764 EPSG:4326:13 4905 5320 9102 9528 EPSG:4326:14 9810 10640 18204 19056 EPSG:4326:15 19620 21281 36408 38112 EPSG:4326:16 39240 42562 72817 76225 EPSG:4326:17 78481 85124 145635 152451 EPSG:4326:18 156963 170248 291270 304903 EPSG:4326:19 313927 340497 582540 609807 EPSG:4326:20 627855 680995 1165080 1219615 EPSG:4326:21 1255711 1361990 2330161 2439230 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 9 8 9 EPSG:3857:5 17 18 17 18 EPSG:3857:6 35 36 35 37 EPSG:3857:7 70 73 71 74 EPSG:3857:8 140 147 142 148 EPSG:3857:9 281 295 284 297 EPSG:3857:10 563 591 568 595 EPSG:3857:11 1126 1182 1137 1191 EPSG:3857:12 2253 2365 2275 2382 EPSG:3857:13 4507 4731 4551 4764 EPSG:3857:14 9014 9463 9102 9528 EPSG:3857:15 18028 18927 18204 19056 EPSG:3857:16 36057 37855 36408 38112 EPSG:3857:17 72115 75711 72817 76225 EPSG:3857:18 144230 151422 145635 152451 EPSG:3857:19 288461 302844 291270 304903 EPSG:3857:20 576923 605689 582540 609807 EPSG:3857:21 1153846 1211379 1165080 1219615 EPSG:3857:22 2307693 2422759 2330161 2439230 EPSG:3857:23 4615387 4845518 4660322 4878461 EPSG:3857:24 9230775 9691037 9320645 9756923 EPSG:3857:25 18461551 19382075 18641291 19513846 EPSG:3857:26 36923102 38764150 37282583 39027693 EPSG:3857:27 73846204 77528300 74565167 78055387 EPSG:3857:28 147692408 155056600 149130335 156110775 EPSG:3857:29 295384816 310113201 298260671 312221551 EPSG:3857:30 590769633 620226403 596521342 624443103 Year precipitations 2010 - Central African Republic Total precipitations observed in 2010 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2010_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Yearly emissions of CH4 - 2000 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -88.79999999998984 179.99999999997954 90.0 wesr_climat:v60_CH4_2000_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 254 0 511 EPSG:4326:9 0 508 0 1023 EPSG:4326:10 0 1017 0 2047 EPSG:4326:11 0 2034 0 4095 EPSG:4326:12 0 4068 0 8191 EPSG:4326:13 0 8137 0 16383 EPSG:4326:14 0 16274 0 32767 EPSG:4326:15 0 32549 0 65535 EPSG:4326:16 0 65099 0 131071 EPSG:4326:17 0 130198 0 262143 EPSG:4326:18 0 260396 0 524287 EPSG:4326:19 0 520792 0 1048575 EPSG:4326:20 0 1041585 0 2097151 EPSG:4326:21 0 2083170 0 4194303 EPSG:900913 EPSG:3857_512 Temperature averages (°C) 1986-2005 (RCP8.5) Temperatures averages in the reference period 1986-2005 based on the climate scenario RCP8.5. -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:tas_85_86_05 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 6 11 EPSG:4326:4 3 8 13 22 EPSG:4326:5 7 17 27 45 EPSG:4326:6 15 34 54 90 EPSG:4326:7 31 68 109 181 EPSG:4326:8 63 137 218 363 EPSG:4326:9 127 275 436 726 EPSG:4326:10 255 550 872 1453 EPSG:4326:11 510 1101 1745 2906 EPSG:4326:12 1021 2203 3490 5813 EPSG:4326:13 2043 4406 6980 11626 EPSG:4326:14 4086 8812 13960 23252 EPSG:4326:15 8173 17625 27921 46505 EPSG:4326:16 16347 35251 55843 93010 EPSG:4326:17 32695 70502 111687 186020 EPSG:4326:18 65390 141004 223375 372040 EPSG:4326:19 130780 282008 446751 744081 EPSG:4326:20 261561 564017 893503 1488162 EPSG:4326:21 523122 1128034 1787006 2976324 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 Dogondoutchi_Intensity_78_T100 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Intensity_78_T100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 6 6 16 16 EPSG:4326:5 13 13 32 33 EPSG:4326:6 26 27 64 66 EPSG:4326:7 52 55 129 132 EPSG:4326:8 105 111 259 264 EPSG:4326:9 211 222 518 529 EPSG:4326:10 423 444 1037 1058 EPSG:4326:11 846 888 2075 2117 EPSG:4326:12 1693 1776 4151 4234 EPSG:4326:13 3387 3552 8302 8468 EPSG:4326:14 6774 7105 16605 16936 EPSG:4326:15 13549 14211 33210 33872 EPSG:4326:16 27099 28423 66421 67745 EPSG:4326:17 54199 56847 132842 135490 EPSG:4326:18 108399 113695 265685 270981 EPSG:4326:19 216798 227390 531371 541962 EPSG:4326:20 433596 454780 1062742 1083925 EPSG:4326:21 867193 909560 2125484 2167851 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 Global Human Modification Index 2015 Detailed global datasets for 1990, 2015, and 2017 for land use modification of terrestrial lands (excluding Antarctica) are provided here. These data were calculated using the degree of human modification approach that combines the proportion of a pixel of a given stressor (i.e. footprint) times the intensity of that stressor (ranging from 0 to 1.0). Our novel datasets are detailed (~300m resolution), temporally consistent (for 1990-2015), comprehensive (11 change stressors, 14 current), robust (using an established framework and incorporating classification errors and parameter uncertainty), and strongly validated. A dataset for ~2017 is also provide, that is derived from 14 stressors, for an even more comprehensive dataset, but it should not be used to calculate change with the other datasets (1990-2015). Theobald, D. M., Kennedy, C., Chen, B., Oakleaf, J., Baruch-Mordo, S., and Kiesecker, J.: Earth transformed: detailed mapping of global human modification from 1990 to 2017, Earth Syst. Sci. Data., https://doi.org/10.5194/essd-2019-252, 2020 Source: https://zenodo.org/record/3963013#.X5ChM0JKjUI -180.0 -75.00027807853427 179.99932064640564 85.00013997386212 MapX_UNDP:gHMv1_2015_wgs image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 26 0 31 EPSG:3857:6 0 52 0 63 EPSG:3857:7 0 105 0 127 EPSG:3857:8 0 210 0 255 EPSG:3857:9 0 421 0 511 EPSG:3857:10 1 842 0 1023 EPSG:3857:11 3 1684 0 2047 EPSG:3857:12 6 3369 0 4095 EPSG:3857:13 13 6739 0 8191 EPSG:3857:14 26 13479 0 16383 EPSG:3857:15 53 26958 0 32767 EPSG:3857:16 107 53916 0 65535 EPSG:3857:17 214 107833 0 131071 EPSG:3857:18 428 215666 0 262143 EPSG:3857:19 856 431333 0 524287 EPSG:3857:20 1712 862667 0 1048574 EPSG:3857:21 3425 1725335 0 2097148 EPSG:3857:22 6851 3450670 0 4194296 EPSG:3857:23 13702 6901340 0 8388592 EPSG:3857:24 27404 13802680 0 16777184 EPSG:3857:25 54809 27605360 0 33554368 EPSG:3857:26 109619 55210721 0 67108737 EPSG:3857:27 219238 110421443 0 134217474 EPSG:3857:28 438476 220842886 0 268434949 EPSG:3857:29 876953 441685773 0 536869898 EPSG:3857:30 1753907 883371547 0 1073739797 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 1 58 0 127 EPSG:4326:7 3 117 0 255 EPSG:4326:8 7 234 0 511 EPSG:4326:9 14 469 0 1023 EPSG:4326:10 28 938 0 2047 EPSG:4326:11 56 1877 0 4095 EPSG:4326:12 113 3754 0 8191 EPSG:4326:13 227 7509 0 16383 EPSG:4326:14 455 15018 0 32767 EPSG:4326:15 910 30037 0 65535 EPSG:4326:16 1820 60074 0 131071 EPSG:4326:17 3640 120149 0 262143 EPSG:4326:18 7281 240299 0 524287 EPSG:4326:19 14563 480598 0 1048574 EPSG:4326:20 29126 961196 0 2097148 EPSG:4326:21 58252 1922392 0 4194296 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 26 0 31 EPSG:3857:6 0 52 0 63 EPSG:3857:7 0 105 0 127 EPSG:3857:8 0 210 0 255 EPSG:3857:9 0 421 0 511 EPSG:3857:10 1 842 0 1023 EPSG:3857:11 3 1684 0 2047 EPSG:3857:12 6 3369 0 4095 EPSG:3857:13 13 6739 0 8191 EPSG:3857:14 26 13479 0 16383 EPSG:3857:15 53 26958 0 32767 EPSG:3857:16 107 53916 0 65535 EPSG:3857:17 214 107833 0 131071 EPSG:3857:18 428 215666 0 262143 EPSG:3857:19 856 431333 0 524287 EPSG:3857:20 1712 862667 0 1048574 EPSG:3857:21 3425 1725335 0 2097148 EPSG:3857:22 6851 3450670 0 4194296 EPSG:3857:23 13702 6901340 0 8388592 EPSG:3857:24 27404 13802680 0 16777184 EPSG:3857:25 54809 27605360 0 33554368 EPSG:3857:26 109619 55210721 0 67108737 EPSG:3857:27 219238 110421443 0 134217474 EPSG:3857:28 438476 220842886 0 268434949 EPSG:3857:29 876953 441685773 0 536869898 EPSG:3857:30 1753907 883371547 0 1073739797 Temperature Seasonality [standard deviation] (2041-2060) RCP8.5 - CIMP5 Standard deviation of the monthly mean temperatures [standard deviation] for the period 2041-2060 based on RCP8.5. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_bio_mon_ACCESS1-0_rcp85_r1i1p1_g025.nc_4_2041-2060_V1.2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 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116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 Central Congo Basin Savanna probability (2022) Metadata for files in the zip archive: Crezee_2022_Central_Congo_Peat_Probability_Layers.zip This folder contains 5 probability layers, the output of 1000 classification runs using a random 2/3 subset of training data, that was used to produce the peatland extent estimates and probability map (Figure 1b) in: Crezee et al. (2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This folder contains 5 layers: - Probability_2022_HardwoodDominatedPeatSwamp.tif - Probability_2022_PalmDominatedPeatSwamp.tif - Probability_2022_NonPeatFormingForest.tif - Probability_2022_Savanna.tif - Probability_2022_Water.tif Each layer has pixel values from 0-1000, representing the number of times that class was given as the most likely class for that pixel in 1000 Maximum Likelihood classifications using a random 2/3 subset of the training data. For example, a value of 995 in the Probability_2022_Water.tif file means that in 995 of the 1000 runs this pixel was mapped as 'water'. Conversely, a value of 4 in the Probability_2022_Savanna.tif would mean that that pixel was only mapped as savanna 4 times in the 1000 runs. As an approximation, dividing these values by 1000 gives the probability that that pixel contains a majority of vegetation of that class. Total peat swamp forest probability is obtained by summing the probabilities of the hardwood and palm-dominated peat swamp forest files. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. For questions about these data layers please contact Edward Mitchard at edward.mitchard@ed.ac.uk 15.0 -4.999916949999999 25.72744828 3.30533333 peatlands:Crezee_2022_Probability_Savanna image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 8 17 18 EPSG:4326:5 15 16 34 36 EPSG:4326:6 30 33 69 73 EPSG:4326:7 61 67 138 146 EPSG:4326:8 123 135 277 292 EPSG:4326:9 246 270 554 585 EPSG:4326:10 493 540 1109 1170 EPSG:4326:11 986 1080 2218 2340 EPSG:4326:12 1972 2161 4437 4681 EPSG:4326:13 3945 4323 8874 9362 EPSG:4326:14 7891 8647 17749 18725 EPSG:4326:15 15782 17294 35498 37451 EPSG:4326:16 31564 34588 70997 74903 EPSG:4326:17 63129 69176 141994 149806 EPSG:4326:18 126258 138353 283989 299612 EPSG:4326:19 252516 276707 567978 599224 EPSG:4326:20 505033 553414 1135957 1198449 EPSG:4326:21 1010066 1106829 2271914 2396898 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 17 18 EPSG:3857:6 31 32 34 36 EPSG:3857:7 62 65 69 73 EPSG:3857:8 125 131 138 146 EPSG:3857:9 251 263 277 292 EPSG:3857:10 502 526 554 585 EPSG:3857:11 1005 1052 1109 1170 EPSG:3857:12 2010 2104 2218 2340 EPSG:3857:13 4020 4209 4437 4681 EPSG:3857:14 8041 8419 8874 9362 EPSG:3857:15 16082 16839 17749 18725 EPSG:3857:16 32165 33679 35498 37451 EPSG:3857:17 64331 67358 70997 74903 EPSG:3857:18 128663 134717 141994 149806 EPSG:3857:19 257327 269434 283989 299612 EPSG:3857:20 514655 538869 567978 599224 EPSG:3857:21 1029310 1077739 1135957 1198449 EPSG:3857:22 2058620 2155479 2271914 2396898 EPSG:3857:23 4117241 4310958 4543829 4793796 EPSG:3857:24 8234482 8621917 9087658 9587593 EPSG:3857:25 16468965 17243834 18175317 19175187 EPSG:3857:26 32937931 34487669 36350634 38350375 EPSG:3857:27 65875862 68975338 72701269 76700751 EPSG:3857:28 131751724 137950677 145402538 153401503 EPSG:3857:29 263503449 275901354 290805077 306803007 EPSG:3857:30 527006898 551802708 581610154 613606015 Self-calibrating Palmer Drought Severity Index (scPDSI) 1981-1990 (CRU) This layer shows the average values over the 1981 to 1990 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_81_90_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tsunami/Coral reefs at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_cor9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcw_for6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average year precipitations anomalies (2001-2010) against 1901-1920 Average year precipitations anomalies in mm across the period 2001-2010 calculated over the average precipitations per year in the period 1901-1920 (as close as possible to the pre-industrial era). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_01_10_anom_1901_1920 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 npl_ls_susceptibility_dd 84.3751220733584 26.895844097850706 86.69125415435332 28.776169868535888 MAPX_nd:npl_ls_susceptibility_dd image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 11 11 EPSG:3857:5 13 13 23 23 EPSG:3857:6 26 27 47 47 EPSG:3857:7 53 54 94 94 EPSG:3857:8 106 108 188 189 EPSG:3857:9 213 216 376 379 EPSG:3857:10 426 432 752 758 EPSG:3857:11 852 865 1504 1517 EPSG:3857:12 1705 1730 3008 3034 EPSG:3857:13 3411 3460 6016 6068 EPSG:3857:14 6823 6920 12032 12137 EPSG:3857:15 13647 13840 24064 24274 EPSG:3857:16 27294 27681 48128 48549 EPSG:3857:17 54588 55362 96256 97099 EPSG:3857:18 109176 110725 192512 194198 EPSG:3857:19 218353 221450 385024 388397 EPSG:3857:20 436707 442901 770048 776794 EPSG:3857:21 873415 885803 1540096 1553589 EPSG:3857:22 1746830 1771606 3080193 3107178 EPSG:3857:23 3493661 3543213 6160386 6214356 EPSG:3857:24 6987323 7086426 12320773 12428713 EPSG:3857:25 13974647 14172853 24641547 24857426 EPSG:3857:26 27949294 28345706 49283094 49714853 EPSG:3857:27 55898588 56691412 98566189 99429706 EPSG:3857:28 111797176 113382825 197132379 198859412 EPSG:3857:29 223594352 226765651 394264758 397718824 EPSG:3857:30 447188704 453531303 788529516 795437649 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 2 2 11 11 EPSG:4326:4 5 5 23 23 EPSG:4326:5 10 11 47 47 EPSG:4326:6 21 22 94 94 EPSG:4326:7 43 44 188 189 EPSG:4326:8 87 89 376 379 EPSG:4326:9 174 179 752 758 EPSG:4326:10 348 358 1504 1517 EPSG:4326:11 696 717 3008 3034 EPSG:4326:12 1393 1435 6016 6068 EPSG:4326:13 2786 2871 12032 12137 EPSG:4326:14 5572 5743 24064 24274 EPSG:4326:15 11145 11487 48128 48549 EPSG:4326:16 22290 22975 96256 97099 EPSG:4326:17 44581 45951 192512 194198 EPSG:4326:18 89163 91902 385024 388397 EPSG:4326:19 178327 183804 770048 776794 EPSG:4326:20 356654 367608 1540096 1553589 EPSG:4326:21 713309 735216 3080193 3107178 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 0 1 1 EPSG:900913:2 1 1 2 2 EPSG:900913:3 3 3 5 5 EPSG:900913:4 6 6 11 11 EPSG:900913:5 13 13 23 23 EPSG:900913:6 26 27 47 47 EPSG:900913:7 53 54 94 94 EPSG:900913:8 106 108 188 189 EPSG:900913:9 213 216 376 379 EPSG:900913:10 426 432 752 758 EPSG:900913:11 852 865 1504 1517 EPSG:900913:12 1705 1730 3008 3034 EPSG:900913:13 3411 3460 6016 6068 EPSG:900913:14 6823 6920 12032 12137 EPSG:900913:15 13647 13840 24064 24274 EPSG:900913:16 27294 27681 48128 48549 EPSG:900913:17 54588 55362 96256 97099 EPSG:900913:18 109176 110725 192512 194198 EPSG:900913:19 218353 221450 385024 388397 EPSG:900913:20 436707 442901 770048 776794 EPSG:900913:21 873415 885803 1540096 1553589 EPSG:900913:22 1746830 1771606 3080193 3107178 EPSG:900913:23 3493661 3543213 6160386 6214356 EPSG:900913:24 6987323 7086426 12320773 12428713 EPSG:900913:25 13974647 14172853 24641547 24857426 EPSG:900913:26 27949294 28345706 49283094 49714853 EPSG:900913:27 55898588 56691412 98566189 99429706 EPSG:900913:28 111797176 113382825 197132379 198859412 EPSG:900913:29 223594352 226765651 394264758 397718824 EPSG:900913:30 447188704 453531303 788529516 795437649 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 6 6 11 11 EPSG:3857:5 13 13 23 23 EPSG:3857:6 26 27 47 47 EPSG:3857:7 53 54 94 94 EPSG:3857:8 106 108 188 189 EPSG:3857:9 213 216 376 379 EPSG:3857:10 426 432 752 758 EPSG:3857:11 852 865 1504 1517 EPSG:3857:12 1705 1730 3008 3034 EPSG:3857:13 3411 3460 6016 6068 EPSG:3857:14 6823 6920 12032 12137 EPSG:3857:15 13647 13840 24064 24274 EPSG:3857:16 27294 27681 48128 48549 EPSG:3857:17 54588 55362 96256 97099 EPSG:3857:18 109176 110725 192512 194198 EPSG:3857:19 218353 221450 385024 388397 EPSG:3857:20 436707 442901 770048 776794 EPSG:3857:21 873415 885803 1540096 1553589 EPSG:3857:22 1746830 1771606 3080193 3107178 EPSG:3857:23 3493661 3543213 6160386 6214356 EPSG:3857:24 6987323 7086426 12320773 12428713 EPSG:3857:25 13974647 14172853 24641547 24857426 EPSG:3857:26 27949294 28345706 49283094 49714853 EPSG:3857:27 55898588 56691412 98566189 99429706 EPSG:3857:28 111797176 113382825 197132379 198859412 EPSG:3857:29 223594352 226765651 394264758 397718824 EPSG:3857:30 447188704 453531303 788529516 795437649 Combination Tropical cyclone / Forest at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcw_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Flood/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_flo_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from Hadley Centre for Climate Prediction, Met Office, UK, HadCM3 Model "Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19)" -180.0 -60.0 180.0 90.0 LWP:sresa2_ukmo_hadcm3_5km_2041-2060_debiasedmean_tas_av12_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 POP_FACEBOOK_Sangha_2019_92m_UTM_opt 13.123883469958475 0.03537250842287123 16.999368548454783 2.722913660432471 AccessMod:POP_FACEBOOK_Sangha_2019_92m_UTM_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 15 15 17 17 EPSG:3857:6 31 31 34 35 EPSG:3857:7 63 63 68 70 EPSG:3857:8 126 127 137 140 EPSG:3857:9 252 255 274 280 EPSG:3857:10 504 511 549 560 EPSG:3857:11 1008 1023 1098 1120 EPSG:3857:12 2017 2047 2197 2241 EPSG:3857:13 4034 4095 4394 4482 EPSG:3857:14 8068 8190 8789 8965 EPSG:3857:15 16136 16380 17578 17931 EPSG:3857:16 32272 32761 35157 35862 EPSG:3857:17 64544 65523 70314 71725 EPSG:3857:18 129088 131046 140628 143450 EPSG:3857:19 258176 262092 281257 286901 EPSG:3857:20 516353 524184 562514 573802 EPSG:3857:21 1032707 1048369 1125028 1147604 EPSG:3857:22 2065415 2096739 2250056 2295208 EPSG:3857:23 4130831 4193479 4500112 4590417 EPSG:3857:24 8261663 8386959 9000225 9180835 EPSG:3857:25 16523326 16773919 18000450 18361671 EPSG:3857:26 33046652 33547838 36000901 36723343 EPSG:3857:27 66093305 67095676 72001802 73446687 EPSG:3857:28 132186611 134191352 144003604 146893375 EPSG:3857:29 264373223 268382704 288007209 293786751 EPSG:3857:30 528746446 536765409 576014419 587573503 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 7 7 17 17 EPSG:4326:5 15 15 34 35 EPSG:4326:6 31 31 68 70 EPSG:4326:7 62 63 137 140 EPSG:4326:8 124 127 274 280 EPSG:4326:9 248 255 549 560 EPSG:4326:10 496 511 1098 1120 EPSG:4326:11 993 1023 2197 2241 EPSG:4326:12 1986 2047 4394 4482 EPSG:4326:13 3972 4094 8789 8965 EPSG:4326:14 7944 8188 17578 17931 EPSG:4326:15 15888 16377 35157 35862 EPSG:4326:16 31776 32755 70314 71725 EPSG:4326:17 63553 65510 140628 143450 EPSG:4326:18 127106 131020 281257 286901 EPSG:4326:19 254212 262040 562514 573802 EPSG:4326:20 508425 524081 1125028 1147604 EPSG:4326:21 1016851 1048163 2250056 2295208 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 15 15 17 17 EPSG:3857:6 31 31 34 35 EPSG:3857:7 63 63 68 70 EPSG:3857:8 126 127 137 140 EPSG:3857:9 252 255 274 280 EPSG:3857:10 504 511 549 560 EPSG:3857:11 1008 1023 1098 1120 EPSG:3857:12 2017 2047 2197 2241 EPSG:3857:13 4034 4095 4394 4482 EPSG:3857:14 8068 8190 8789 8965 EPSG:3857:15 16136 16380 17578 17931 EPSG:3857:16 32272 32761 35157 35862 EPSG:3857:17 64544 65523 70314 71725 EPSG:3857:18 129088 131046 140628 143450 EPSG:3857:19 258176 262092 281257 286901 EPSG:3857:20 516353 524184 562514 573802 EPSG:3857:21 1032707 1048369 1125028 1147604 EPSG:3857:22 2065415 2096739 2250056 2295208 EPSG:3857:23 4130831 4193479 4500112 4590417 EPSG:3857:24 8261663 8386959 9000225 9180835 EPSG:3857:25 16523326 16773919 18000450 18361671 EPSG:3857:26 33046652 33547838 36000901 36723343 EPSG:3857:27 66093305 67095676 72001802 73446687 EPSG:3857:28 132186611 134191352 144003604 146893375 EPSG:3857:29 264373223 268382704 288007209 293786751 EPSG:3857:30 528746446 536765409 576014419 587573503 Combination Tsunami/Forest at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 ecuador_ecosistemas_clean_fragmentation -81.09264033289094 -5.015146735772655 -75.1950953254417 1.4627334137699841 MAPX_nd:ecuador_ecosistemas_clean_fragmentation image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 16 8 9 EPSG:3857:6 31 32 17 18 EPSG:3857:7 63 65 35 37 EPSG:3857:8 126 131 70 74 EPSG:3857:9 253 263 140 149 EPSG:3857:10 507 526 281 298 EPSG:3857:11 1015 1052 562 596 EPSG:3857:12 2031 2105 1125 1192 EPSG:3857:13 4062 4210 2250 2384 EPSG:3857:14 8125 8420 4501 4769 EPSG:3857:15 16250 16841 9002 9539 EPSG:3857:16 32501 33682 18005 19079 EPSG:3857:17 65003 67364 36011 38158 EPSG:3857:18 130006 134728 72022 76316 EPSG:3857:19 260013 269457 144044 152633 EPSG:3857:20 520027 538914 288088 305266 EPSG:3857:21 1040054 1077828 576177 610532 EPSG:3857:22 2080108 2155657 1152354 1221065 EPSG:3857:23 4160216 4311314 2304708 2442131 EPSG:3857:24 8320432 8622629 4609417 4884262 EPSG:3857:25 16640864 17245259 9218834 9768525 EPSG:3857:26 33281729 34490519 18437668 19537050 EPSG:3857:27 66563458 68981038 36875336 39074100 EPSG:3857:28 133126916 137962076 73750672 78148201 EPSG:3857:29 266253832 275924153 147501345 156296402 EPSG:3857:30 532507665 551848307 295002691 312592804 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 1 1 1 EPSG:4326:2 1 2 2 2 EPSG:4326:3 3 4 4 4 EPSG:4326:4 7 8 8 9 EPSG:4326:5 15 16 17 18 EPSG:4326:6 31 33 35 37 EPSG:4326:7 62 67 70 74 EPSG:4326:8 125 135 140 149 EPSG:4326:9 251 270 281 298 EPSG:4326:10 503 540 562 596 EPSG:4326:11 1007 1081 1125 1192 EPSG:4326:12 2014 2162 2250 2384 EPSG:4326:13 4029 4324 4501 4769 EPSG:4326:14 8058 8648 9002 9539 EPSG:4326:15 16117 17296 18005 19079 EPSG:4326:16 32235 34593 36011 38158 EPSG:4326:17 64470 69187 72022 76316 EPSG:4326:18 128941 138375 144044 152633 EPSG:4326:19 257883 276751 288088 305266 EPSG:4326:20 515766 553503 576177 610532 EPSG:4326:21 1031533 1107006 1152354 1221065 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 0 EPSG:900913:2 1 2 1 1 EPSG:900913:3 3 4 2 2 EPSG:900913:4 7 8 4 4 EPSG:900913:5 15 16 8 9 EPSG:900913:6 31 32 17 18 EPSG:900913:7 63 65 35 37 EPSG:900913:8 126 131 70 74 EPSG:900913:9 253 263 140 149 EPSG:900913:10 507 526 281 298 EPSG:900913:11 1015 1052 562 596 EPSG:900913:12 2031 2105 1125 1192 EPSG:900913:13 4062 4210 2250 2384 EPSG:900913:14 8125 8420 4501 4769 EPSG:900913:15 16250 16841 9002 9539 EPSG:900913:16 32501 33682 18005 19079 EPSG:900913:17 65003 67364 36011 38158 EPSG:900913:18 130006 134728 72022 76316 EPSG:900913:19 260013 269457 144044 152633 EPSG:900913:20 520027 538914 288088 305266 EPSG:900913:21 1040054 1077828 576177 610532 EPSG:900913:22 2080108 2155657 1152354 1221065 EPSG:900913:23 4160216 4311314 2304708 2442131 EPSG:900913:24 8320432 8622629 4609417 4884262 EPSG:900913:25 16640864 17245259 9218834 9768525 EPSG:900913:26 33281729 34490519 18437668 19537050 EPSG:900913:27 66563458 68981038 36875336 39074100 EPSG:900913:28 133126916 137962076 73750672 78148201 EPSG:900913:29 266253832 275924153 147501345 156296402 EPSG:900913:30 532507665 551848307 295002691 312592804 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 16 8 9 EPSG:3857:6 31 32 17 18 EPSG:3857:7 63 65 35 37 EPSG:3857:8 126 131 70 74 EPSG:3857:9 253 263 140 149 EPSG:3857:10 507 526 281 298 EPSG:3857:11 1015 1052 562 596 EPSG:3857:12 2031 2105 1125 1192 EPSG:3857:13 4062 4210 2250 2384 EPSG:3857:14 8125 8420 4501 4769 EPSG:3857:15 16250 16841 9002 9539 EPSG:3857:16 32501 33682 18005 19079 EPSG:3857:17 65003 67364 36011 38158 EPSG:3857:18 130006 134728 72022 76316 EPSG:3857:19 260013 269457 144044 152633 EPSG:3857:20 520027 538914 288088 305266 EPSG:3857:21 1040054 1077828 576177 610532 EPSG:3857:22 2080108 2155657 1152354 1221065 EPSG:3857:23 4160216 4311314 2304708 2442131 EPSG:3857:24 8320432 8622629 4609417 4884262 EPSG:3857:25 16640864 17245259 9218834 9768525 EPSG:3857:26 33281729 34490519 18437668 19537050 EPSG:3857:27 66563458 68981038 36875336 39074100 EPSG:3857:28 133126916 137962076 73750672 78148201 EPSG:3857:29 266253832 275924153 147501345 156296402 EPSG:3857:30 532507665 551848307 295002691 312592804 Forest Connectivity (2013) (NASA) Forest connectivity identifies key areas between Intact Forest Landscapes (IFLs) in 2013. IFLs are large areas (greater than or equal to 500 square kilometres) of forest and other natural vegetation that show no remotely detected signs of human disturbance. Data Sources: Hansen, M.C., et al. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342, 850–853. DOI: <a href="https://doi.org/10.1126/science.1244693" target="_blank">10.1126/science.1244693</a> Potapov, P., et al., 2017. The last frontiers of wilderness: Tracking loss of intact forest landscapes from 2000 to 2013. Science Advances 3, e1600821. <a href="https://doi.org/10.1126/sciadv.1600821" target="_blank">10.1126/sciadv.1600821</a> -95.26972112443687 -26.368039400717038 167.81411628372408 25.126944105146272 MapX_UNDP_nd:c2013 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 3 15 EPSG:3857:5 13 18 7 30 EPSG:3857:6 27 36 15 61 EPSG:3857:7 54 73 30 123 EPSG:3857:8 109 147 60 247 EPSG:3857:9 219 294 120 494 EPSG:3857:10 438 589 241 989 EPSG:3857:11 876 1179 482 1978 EPSG:3857:12 1752 2359 964 3957 EPSG:3857:13 3504 4718 1928 7914 EPSG:3857:14 7009 9436 3856 15829 EPSG:3857:15 14019 18873 7712 31658 EPSG:3857:16 28039 37747 15424 63317 EPSG:3857:17 56079 75494 30849 126635 EPSG:3857:18 112158 150988 61698 253270 EPSG:3857:19 224317 301977 123397 506541 EPSG:3857:20 448635 603954 246794 1013082 EPSG:3857:21 897270 1207909 493589 2026164 EPSG:3857:22 1794540 2415818 987179 4052328 EPSG:3857:23 3589080 4831636 1974358 8104656 EPSG:3857:24 7178160 9663272 3948717 16209312 EPSG:3857:25 14356320 19326544 7897434 32418625 EPSG:3857:26 28712640 38653089 15794868 64837250 EPSG:3857:27 57425281 77306178 31589737 129674501 EPSG:3857:28 114850562 154612357 63179475 259349002 EPSG:3857:29 229701124 309224714 126358950 518698005 EPSG:3857:30 459402248 618449429 252717900 1037396010 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 1 2 1 7 EPSG:4326:3 2 5 3 15 EPSG:4326:4 5 10 7 30 EPSG:4326:5 11 20 15 61 EPSG:4326:6 23 41 30 123 EPSG:4326:7 46 82 60 247 EPSG:4326:8 92 165 120 494 EPSG:4326:9 184 331 241 989 EPSG:4326:10 369 662 482 1978 EPSG:4326:11 738 1324 964 3957 EPSG:4326:12 1476 2648 1928 7914 EPSG:4326:13 2952 5296 3856 15829 EPSG:4326:14 5904 10592 7712 31658 EPSG:4326:15 11809 21184 15424 63317 EPSG:4326:16 23619 42368 30849 126635 EPSG:4326:17 47239 84736 61698 253270 EPSG:4326:18 94478 169473 123397 506541 EPSG:4326:19 188956 338946 246794 1013082 EPSG:4326:20 377912 677892 493589 2026164 EPSG:4326:21 755825 1355785 987179 4052328 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 3 15 EPSG:3857:5 13 18 7 30 EPSG:3857:6 27 36 15 61 EPSG:3857:7 54 73 30 123 EPSG:3857:8 109 147 60 247 EPSG:3857:9 219 294 120 494 EPSG:3857:10 438 589 241 989 EPSG:3857:11 876 1179 482 1978 EPSG:3857:12 1752 2359 964 3957 EPSG:3857:13 3504 4718 1928 7914 EPSG:3857:14 7009 9436 3856 15829 EPSG:3857:15 14019 18873 7712 31658 EPSG:3857:16 28039 37747 15424 63317 EPSG:3857:17 56079 75494 30849 126635 EPSG:3857:18 112158 150988 61698 253270 EPSG:3857:19 224317 301977 123397 506541 EPSG:3857:20 448635 603954 246794 1013082 EPSG:3857:21 897270 1207909 493589 2026164 EPSG:3857:22 1794540 2415818 987179 4052328 EPSG:3857:23 3589080 4831636 1974358 8104656 EPSG:3857:24 7178160 9663272 3948717 16209312 EPSG:3857:25 14356320 19326544 7897434 32418625 EPSG:3857:26 28712640 38653089 15794868 64837250 EPSG:3857:27 57425281 77306178 31589737 129674501 EPSG:3857:28 114850562 154612357 63179475 259349002 EPSG:3857:29 229701124 309224714 126358950 518698005 EPSG:3857:30 459402248 618449429 252717900 1037396010 International Boundaries Polygons Level 0 - UNmap UNmap is a global multi-scale geospatial dataset that is designed to serve as a base geodatabase for map production and web mapping to meet the needs of the United Nations Secretariat in supporting the work of the Security Council and field operations. It consists of basic geospatial information at different scales. -180.0 -90.0 180.0 84.4950561523438 grid_data_core_pro:ungiwg_bnd_ply_01m image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 7 255 0 511 EPSG:4326:9 15 511 0 1023 EPSG:4326:10 31 1023 0 2047 EPSG:4326:11 62 2047 0 4095 EPSG:4326:12 125 4095 0 8191 EPSG:4326:13 250 8191 0 16383 EPSG:4326:14 501 16383 0 32767 EPSG:4326:15 1002 32767 0 65535 EPSG:4326:16 2004 65535 0 131071 EPSG:4326:17 4008 131071 0 262143 EPSG:4326:18 8017 262143 0 524287 EPSG:4326:19 16034 524287 0 1048575 EPSG:4326:20 32068 1048575 0 2097151 EPSG:4326:21 64137 2097151 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 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78758045 80353494 EPSG:3857:28 93432598 95620708 157516090 160706988 EPSG:3857:29 186865196 191241417 315032180 321413977 EPSG:3857:30 373730392 382482835 630064360 642827955 Evapotranspiration Winter 2019 - 2020 (USGS) The original data is from the USGS FEWS Data Downloads (https://earlywarning.usgs.gov/fews/datadownloads/Global/PET). The present raster in the average monthly evapotranspiration for winter 2019-2020. It in the average of the various evapotranspiration files available in winter 2019-2020 (December 2019, January 2020 and February 2020). On vegetated landscapes, Evapotranspiration (ET) can be simplified as the combination of evaporation from soil and transpiration from vegetation. Actual ET (ETa) is produced using the Operational Simplified Surface Energy Balance (SSEBop) model (Senay et al., 2013) for 2003 to present using data stream from the Aqua satellite. The SSEBop setup is based on the original Simplified Surface Energy Balance (SSEB) approach (Senay et al., 2007, 2011) with unique and improved parameterizations for operational applications. It combines ET fractions generated from remotely sensed MODIS thermal imagery, summarized every 10 days (dekadal), with reference ET, generated from weather data fields using the Penman-Monteith Equation. The unique feature of the SSEBop parameterization is that it uses a pre-defined, seasonally dynamic surface psychrometer constant parameter that helps define the hot/dry and cold/wet reference limits, unique to each pixel. Furthermore, the cold/wet limit is determined using the daily maximum air temperature (Ta) using the c factor parameter which relates Ta to land surface temperature at well-vegetated/well-watered surfaces. The original SSEB model was formulated based on an adaptation of the hot and cold pixel principles of SEBAL (Bastiaanssen et al., 1998) and METRIC (Allen et al., 2007) models. NoData pixels are indicated as NoDATA in ArcGIS. However, other software (e.g., ERDAS imagine) show nodata as -32768.00. ETa data and anomaly products (current vs. 2003 &#8211; 2015 median), produced at 1 km resolution, are available at: https://earlywarning.usgs.gov/fews. -180.0 -60.00000000570601 180.0 80.002258848399 wesr_mountains:m201912-202001-02_hiver_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1838 11626 0 16383 EPSG:3857:15 3677 23252 0 32767 EPSG:3857:16 7354 46504 0 65535 EPSG:3857:17 14709 93008 0 131071 EPSG:3857:18 29418 186017 0 262143 EPSG:3857:19 58837 372034 0 524287 EPSG:3857:20 117674 744069 0 1048575 EPSG:3857:21 235349 1488139 0 2097151 EPSG:3857:22 470698 2976279 0 4194304 EPSG:3857:23 941396 5952559 0 8388608 EPSG:3857:24 1882793 11905118 0 16777215 EPSG:3857:25 3765587 23810236 0 33554431 EPSG:3857:26 7531175 47620473 0 67108863 EPSG:3857:27 15062350 95240947 0 134217727 EPSG:3857:28 30124701 190481895 0 268435456 EPSG:3857:29 60249403 380963791 0 536870911 EPSG:3857:30 120498807 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 3 53 0 127 EPSG:4326:7 7 106 0 255 EPSG:4326:8 14 213 0 511 EPSG:4326:9 28 426 0 1023 EPSG:4326:10 56 853 0 2047 EPSG:4326:11 113 1706 0 4095 EPSG:4326:12 227 3413 0 8191 EPSG:4326:13 455 6826 0 16383 EPSG:4326:14 910 13653 0 32767 EPSG:4326:15 1820 27306 0 65535 EPSG:4326:16 3640 54613 0 131071 EPSG:4326:17 7280 109226 0 262143 EPSG:4326:18 14560 218453 0 524287 EPSG:4326:19 29120 436906 0 1048575 EPSG:4326:20 58241 873813 0 2097151 EPSG:4326:21 116482 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1838 11626 0 16383 EPSG:3857:15 3677 23252 0 32767 EPSG:3857:16 7354 46504 0 65535 EPSG:3857:17 14709 93008 0 131071 EPSG:3857:18 29418 186017 0 262143 EPSG:3857:19 58837 372034 0 524287 EPSG:3857:20 117674 744069 0 1048575 EPSG:3857:21 235349 1488139 0 2097152 EPSG:3857:22 470698 2976279 0 4194304 EPSG:3857:23 941396 5952559 0 8388607 EPSG:3857:24 1882793 11905118 0 16777215 EPSG:3857:25 3765587 23810236 0 33554431 EPSG:3857:26 7531175 47620473 0 67108863 EPSG:3857:27 15062350 95240947 0 134217728 EPSG:3857:28 30124701 190481895 0 268435455 EPSG:3857:29 60249403 380963791 0 536870911 EPSG:3857:30 120498807 761927583 0 1073741824 Yearly emissions of CO2 (excluding short cycle organic Carbon) - 2000 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -88.79999999998984 179.99999999997954 90.0 wesr_climat:v60_CO2_excl_short-cycle_org_C_2000_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 254 0 511 EPSG:4326:9 0 508 0 1023 EPSG:4326:10 0 1017 0 2047 EPSG:4326:11 0 2034 0 4095 EPSG:4326:12 0 4068 0 8191 EPSG:4326:13 0 8137 0 16383 EPSG:4326:14 0 16274 0 32767 EPSG:4326:15 0 32549 0 65535 EPSG:4326:16 0 65099 0 131071 EPSG:4326:17 0 130198 0 262143 EPSG:4326:18 0 260396 0 524287 EPSG:4326:19 0 520792 0 1048575 EPSG:4326:20 0 1041585 0 2097151 EPSG:4326:21 0 2083170 0 4194303 EPSG:900913 EPSG:3857_512 site_0336_19860908_visual_bilinear 21.804453393351142 2.163950346428799 22.972377367092143 3.360478793316272 hotspots:site_0336_19860908_visual_bilinear image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 15 15 35 36 EPSG:4326:6 30 31 71 72 EPSG:4326:7 61 62 143 144 EPSG:4326:8 123 124 287 288 EPSG:4326:9 246 249 574 577 EPSG:4326:10 492 499 1148 1154 EPSG:4326:11 985 999 2296 2309 EPSG:4326:12 1971 1998 4592 4618 EPSG:4326:13 3943 3997 9184 9237 EPSG:4326:14 7886 7995 18368 18474 EPSG:4326:15 15772 15990 36737 36949 EPSG:4326:16 31544 31980 73474 73899 EPSG:4326:17 63088 63960 146949 147799 EPSG:4326:18 126177 127920 293899 295599 EPSG:4326:19 252355 255841 587798 591199 EPSG:4326:20 504711 511682 1175596 1182399 EPSG:4326:21 1009423 1023364 2351192 2364799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 Combination Tsunami/Forest at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_for6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Winter precipitations change (%) for the period 2080 - 2099 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_djf_ENDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 GEOCARBON Global Forest Aboveground Biomass (Mg/ha) This file provides the global biomass map produced with the EU FP7 GEOCARBON project (www.geocarbon.net) and presented by Avitabile et al. (2014) at the Global Vegetation Monitoring and Modeling, 3-7 February 2014, Avignon (France). The map is obtained by combining and harmonizing the pan-tropical biomass map by Avitabile et al. (2016) with the boreal forest biomass map by Santoro et al. (2015). The map covers only forest areas, where forest are defined as areas with dominance of tree cover in the GLC2000 map (Bartholomé and Belward, 2005). For a proper use and description of this dataset, please refer to the mentioned articles. Source: Avitabile, V., Herold, M., Lewis, S.L., Phillips, O.L., Aguilar-Amuchastegui, N., Asner, G. P., Brienen, R.J.W., DeVries, B., Cazzolla Gatti, R., Feldpausch, T.R., Girardin, C., de Jong, B., Kearsley, E., Klop, E., Lin, X., Lindsell, J., Lopez-Gonzalez, G., Lucas, R., Malhi, Y., Morel, A.,  Mitchard, E., Pandey, D., Piao, S., Ryan, C., Sales, M., Santoro, M., Vaglio Laurin, G., Valentini, R., Verbeeck, H., Wijaya, A., Willcock, S., 2014. Comparative analysis and fusion for improved global biomass mapping.  Global Vegetation Monitoring and Modeling, 3 – 7 February 2014, Avignon (France) (https://colloque.inra.fr/gv2m) Based on data from: Avitabile, V., Herold, M., Heuvelink, G. B. M., Lewis, S. L., Phillips, O. L., Asner, G. P., Armston, J., Ashton, P. S., Banin, L., Bayol, N., Berry, N. J., Boeckx, P., de Jong, B. H. J., DeVries, B., Girardin, C. A. J., Kearsley, E., Lindsell, J. A., Lopez-Gonzalez, G., Lucas, R., Malhi, Y., Morel, A., Mitchard, E. T. A., Nagy, L., Qie, L., Quinones, M. J., Ryan, C. M., Ferry, S. J. W., Sunderland, T., Laurin, G. V., Gatti, R. C., Valentini, R., Verbeeck, H., Wijaya, A. and Willcock, S. (2016), An integrated pan-tropical biomass map using multiple reference datasets. Glob Change Biol, 22: 1406–1420. doi:10.1111/gcb.13139 Santoro, M., Beaudoin, A., Beer, C., Cartus, O., Fransson, J.E.S., Hall, R.J., Pathe, C., Schmullius, C., Schepaschenko, D., Shvidenko, A., Thurner, M. and Wegmüller, U. (2015). Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR. Remote Sensing of Environment, Vol. 168, pag. 316-334 Source: Avitabile V, Herold M, Heuvelink G, Lewis SL, Phillips OL, Asner GP et al. (2016). An integrated pan-tropical biomass maps using multiple reference datasets. Global Change Biology, 22: 1406–1420. doi:10.1111/gcb.13139. Data Source: https://www.wur.nl/en/Expertise-Services/Chair-groups/Environmental-Sciences/Laboratory-of-Geo-information-Science-and-Remote-Sensing/Research/Integrated-land-monitoring/Forest_Biomass/Forest-Biomass-downloads.htm -180.0 -56.02000000000001 180.0 84.0 MapX_UNDP:GEOCARBON_Global_Forest_AGB_10072015 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 44 0 63 EPSG:3857:7 3 88 0 127 EPSG:3857:8 7 176 0 255 EPSG:3857:9 15 352 0 511 EPSG:3857:10 31 705 0 1023 EPSG:3857:11 62 1410 0 2047 EPSG:3857:12 125 2820 0 4095 EPSG:3857:13 251 5641 0 8191 EPSG:3857:14 502 11283 0 16383 EPSG:3857:15 1005 22567 0 32767 EPSG:3857:16 2011 45135 0 65535 EPSG:3857:17 4023 90270 0 131071 EPSG:3857:18 8047 180540 0 262143 EPSG:3857:19 16095 361080 0 524287 EPSG:3857:20 32191 722160 0 1048575 EPSG:3857:21 64382 1444321 0 2097151 EPSG:3857:22 128764 2888642 0 4194304 EPSG:3857:23 257528 5777285 0 8388608 EPSG:3857:24 515056 11554570 0 16777215 EPSG:3857:25 1030113 23109140 0 33554431 EPSG:3857:26 2060227 46218280 0 67108863 EPSG:3857:27 4120454 92436561 0 134217727 EPSG:3857:28 8240909 184873122 0 268435456 EPSG:3857:29 16481819 369746245 0 536870911 EPSG:3857:30 32963639 739492490 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 4 103 0 255 EPSG:4326:8 8 207 0 511 EPSG:4326:9 17 415 0 1023 EPSG:4326:10 34 830 0 2047 EPSG:4326:11 68 1661 0 4095 EPSG:4326:12 136 3322 0 8191 EPSG:4326:13 273 6645 0 16383 EPSG:4326:14 546 13291 0 32767 EPSG:4326:15 1092 26582 0 65535 EPSG:4326:16 2184 53164 0 131071 EPSG:4326:17 4369 106328 0 262143 EPSG:4326:18 8738 212657 0 524287 EPSG:4326:19 17476 425314 0 1048575 EPSG:4326:20 34952 850628 0 2097151 EPSG:4326:21 69905 1701256 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 22 0 31 EPSG:900913:6 1 44 0 63 EPSG:900913:7 3 88 0 127 EPSG:900913:8 7 176 0 255 EPSG:900913:9 15 352 0 511 EPSG:900913:10 31 705 0 1023 EPSG:900913:11 62 1410 0 2047 EPSG:900913:12 125 2820 0 4095 EPSG:900913:13 251 5641 0 8191 EPSG:900913:14 502 11283 0 16383 EPSG:900913:15 1005 22567 0 32767 EPSG:900913:16 2011 45135 0 65535 EPSG:900913:17 4023 90270 0 131071 EPSG:900913:18 8047 180540 0 262143 EPSG:900913:19 16095 361080 0 524287 EPSG:900913:20 32191 722160 0 1048575 EPSG:900913:21 64382 1444321 0 2097151 EPSG:900913:22 128764 2888642 0 4194303 EPSG:900913:23 257528 5777285 0 8388607 EPSG:900913:24 515056 11554570 0 16777215 EPSG:900913:25 1030113 23109140 0 33554431 EPSG:900913:26 2060227 46218280 0 67108863 EPSG:900913:27 4120454 92436561 0 134217727 EPSG:900913:28 8240909 184873122 0 268435455 EPSG:900913:29 16481819 369746245 0 536870911 EPSG:900913:30 32963639 739492490 0 1073741823 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 44 0 63 EPSG:3857:7 3 88 0 127 EPSG:3857:8 7 176 0 255 EPSG:3857:9 15 352 0 511 EPSG:3857:10 31 705 0 1023 EPSG:3857:11 62 1410 0 2047 EPSG:3857:12 125 2820 0 4095 EPSG:3857:13 251 5641 0 8191 EPSG:3857:14 502 11283 0 16383 EPSG:3857:15 1005 22567 0 32767 EPSG:3857:16 2011 45135 0 65535 EPSG:3857:17 4023 90270 0 131071 EPSG:3857:18 8047 180540 0 262143 EPSG:3857:19 16095 361080 0 524287 EPSG:3857:20 32191 722160 0 1048575 EPSG:3857:21 64382 1444321 0 2097152 EPSG:3857:22 128764 2888642 0 4194304 EPSG:3857:23 257528 5777285 0 8388607 EPSG:3857:24 515056 11554570 0 16777215 EPSG:3857:25 1030113 23109140 0 33554431 EPSG:3857:26 2060227 46218280 0 67108863 EPSG:3857:27 4120454 92436561 0 134217728 EPSG:3857:28 8240909 184873122 0 268435455 EPSG:3857:29 16481819 369746245 0 536870911 EPSG:3857:30 32963639 739492490 0 1073741824 GHS population grid (2020) The GHS-POP depicts the distribution of residential population, expressed as the number of people per cell. Residential population estimates between 1975 and 2020 in 5 years intervals and projections to 2025 and 2030 derived from CIESIN GPWv4.11 were disaggregated from census or administrative units to grid cells, informed by the distribution, density, and classification of built-up as mapped in the Global Human Settlement Layer (GHSL) global layer per corresponding epoch. This dataset is an update of the product released in 2022. Major improvements are the following: use of built-up volume maps (GHS-BUILT-V R2022A); use of more recent and detailed population estimates derived from GPWv4.11 integrating both UN World Population Prospects 2022 country population data and World Urbanisation Prospects 2018 data on Cities; revision of GPWv4.11 population growthrates by convergence to upper administrative level growthrates; systematic improvement of census coastlines; systematic revision of census units declared as unpopulated; integration of non-residential built-up volume information (GHS-BUILT-V_NRES R2023A); spatial resolution of 100m Mollweide (and 3 arcseconds in WGS84); projections to 2030. The complete information about the GHSL main products can be found in the GHSL Data Package 2023 report. Publication: Schiavina, Marcello; Freire, Sergio; Alessandra Carioli; MacManus, Kytt (2023): GHS-POP R2023A - GHS population grid multitemporal (1975-2030). European Commission, Joint Research Centre (JRC) [Dataset] doi: 10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE PID: http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe Concept & Methodology: Freire S., MacManus K., Pesaresi M., Doxsey-Whitfield E., Mills J. (2016) Development of new open and free multi-temporal global population grids at 250 m resolution. Geospatial Data in a Changing World; Association of Geographic Information Laboratories in Europe (AGILE), AGILE 2016 -180.0 -89.09291610520242 180.0 89.09208317767579 MAPX:GHS_POP_E2020_GLOBE_R2023A_4326_3ss_V1_0_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 1 254 0 511 EPSG:4326:9 2 509 0 1023 EPSG:4326:10 5 1018 0 2047 EPSG:4326:11 10 2037 0 4095 EPSG:4326:12 20 4075 0 8191 EPSG:4326:13 41 8150 0 16383 EPSG:4326:14 82 16301 0 32767 EPSG:4326:15 165 32602 0 65535 EPSG:4326:16 330 65205 0 131071 EPSG:4326:17 661 130411 0 262143 EPSG:4326:18 1322 260822 0 524287 EPSG:4326:19 2644 521645 0 1048575 EPSG:4326:20 5288 1043291 0 2097151 EPSG:4326:21 10577 2086583 0 4194303 EPSG:900913 EPSG:3857_512 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from Meteorological Research Institute, Japan, CGCM2.3.2a Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_mri_cgcm2_3_2a_5km_2041-2060_debiasedmean_tas_12mav_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Potential Clean Water Provision <span style="font-size:1em"> This dataset shows the total potential supply of clean water available to users in m³. Water quantity in each pixel is calculated as the water balance (rainfall minus actual evapotranspiration) cumulated downstream. See Mulligan et al. (2013) for a description of the global water balance dataset. Potential water provisioning services for each cell are first calculated as the volume of clean water available from upstream. The volume of water is calculated as the downstream cumulated water balance based on (rainfall+fog+snowmelt)-actual evapotranspiration. <br> <br> <u>References:</u> <ul> <li> Mulligan, M. (2013) WaterWorld: a self-parameterising, physically based model for application in data-poor but problem-rich environments globally. Hydrology research 44, 5; 748-769. </li> </ul> </span> -179.99999999990345 -56.016220913563274 179.97221821435372 83.99999999995521 MapX_UNDP:potential_clean_water_prov_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 44 0 63 EPSG:3857:7 3 88 0 127 EPSG:3857:8 7 176 0 255 EPSG:3857:9 15 352 0 511 EPSG:3857:10 31 705 0 1023 EPSG:3857:11 62 1410 0 2047 EPSG:3857:12 125 2820 0 4095 EPSG:3857:13 251 5641 0 8191 EPSG:3857:14 502 11283 0 16382 EPSG:3857:15 1005 22566 0 32765 EPSG:3857:16 2011 45133 0 65530 EPSG:3857:17 4023 90267 0 131061 EPSG:3857:18 8047 180535 0 262123 EPSG:3857:19 16095 361070 0 524247 EPSG:3857:20 32191 722140 0 1048495 EPSG:3857:21 64382 1444281 0 2096990 EPSG:3857:22 128764 2888563 0 4193980 EPSG:3857:23 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1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 44 0 63 EPSG:3857:7 3 88 0 127 EPSG:3857:8 7 176 0 255 EPSG:3857:9 15 352 0 511 EPSG:3857:10 31 705 0 1023 EPSG:3857:11 62 1410 0 2047 EPSG:3857:12 125 2820 0 4095 EPSG:3857:13 251 5641 0 8191 EPSG:3857:14 502 11283 0 16382 EPSG:3857:15 1005 22566 0 32765 EPSG:3857:16 2011 45133 0 65530 EPSG:3857:17 4023 90267 0 131061 EPSG:3857:18 8047 180535 0 262123 EPSG:3857:19 16095 361070 0 524247 EPSG:3857:20 32191 722140 0 1048495 EPSG:3857:21 64382 1444281 0 2096990 EPSG:3857:22 128764 2888563 0 4193980 EPSG:3857:23 257528 5777127 0 8387960 EPSG:3857:24 515056 11554255 0 16775921 EPSG:3857:25 1030113 23108510 0 33551842 EPSG:3857:26 2060227 46217020 0 67103685 EPSG:3857:27 4120454 92434040 0 134207370 EPSG:3857:28 8240909 184868081 0 268414740 EPSG:3857:29 16481819 369736162 0 536829480 EPSG:3857:30 32963639 739472324 0 1073658961 Dogondoutchi_Duration_78_T100 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Duration_78_T100 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 6 6 16 16 EPSG:4326:5 13 13 32 33 EPSG:4326:6 26 27 64 66 EPSG:4326:7 52 55 129 132 EPSG:4326:8 105 111 259 264 EPSG:4326:9 211 222 518 529 EPSG:4326:10 423 444 1037 1058 EPSG:4326:11 846 888 2075 2117 EPSG:4326:12 1693 1776 4151 4234 EPSG:4326:13 3387 3552 8302 8468 EPSG:4326:14 6774 7105 16605 16936 EPSG:4326:15 13549 14211 33210 33872 EPSG:4326:16 27099 28423 66421 67745 EPSG:4326:17 54199 56847 132842 135490 EPSG:4326:18 108399 113695 265685 270981 EPSG:4326:19 216798 227390 531371 541962 EPSG:4326:20 433596 454780 1062742 1083925 EPSG:4326:21 867193 909560 2125484 2167851 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 Closed forest total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:forestcfkm2a image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Self-calibrating Palmer Drought Severity Index (scPDSI) 2021 (CRU) This layer shows the average values for 2021 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_21_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 site_0336_19860908_math 21.804453393351142 2.163950346428799 22.972377367092143 3.360478793316272 hotspots:site_0336_19860908_math image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 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global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_sea6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tsunami/Sea grasses at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_sea9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone surge/ Forest at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone surge/ Sea grasses at global level - 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16243 199611 0 524287 EPSG:4326:19 32486 399223 0 1048575 EPSG:4326:20 64972 798447 0 2097151 EPSG:4326:21 129945 1596895 0 4194303 EPSG:900913 Population density in Dakar Senegal (2030) This layer shows the estimated population distribution for the Dakar region in 2030, based on the Global Human Settlement Layer (GHSL, open access). The dataset is provided as a raster at 100 m spatial resolution. Each pixel contains the estimated number of inhabitants living within a 100 m × 100 m cell. This gridded representation allows the analysis of population patterns and supports the derivation of population density values at different spatial scales. This layer serves as an input for the project, supporting the identification of areas where higher population concentrations may increase the susceptibility of illegal dumping sites. -17.574657994490252 14.62972698943294 -17.17229869382342 14.86844154301869 dakar_waste:popu_2030_Dakar image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 463 EPSG:3857:11 938 939 924 926 EPSG:3857:12 1876 1879 1848 1852 EPSG:3857:13 3753 3759 3696 3705 EPSG:3857:14 7507 7518 7392 7410 EPSG:3857:15 15015 15037 14784 14820 EPSG:3857:16 30030 30075 29568 29641 EPSG:3857:17 60060 60150 59137 59283 EPSG:3857:18 120121 120301 118274 118567 EPSG:3857:19 240243 240602 236549 237135 EPSG:3857:20 480486 481205 473098 474270 EPSG:3857:21 960972 962410 946196 948540 EPSG:3857:22 1921944 1924820 1892392 1897080 EPSG:3857:23 3843888 3849640 3784784 3794160 EPSG:3857:24 7687777 7699281 7569569 7588320 EPSG:3857:25 15375555 15398563 15139139 15176641 EPSG:3857:26 30751111 30797126 30278278 30353283 EPSG:3857:27 61502222 61594253 60556556 60706567 EPSG:3857:28 123004444 123188507 121113113 121413134 EPSG:3857:29 246008888 246377015 242226226 242826268 EPSG:3857:30 492017776 492754030 484452452 485652536 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 463 EPSG:4326:10 427 428 924 926 EPSG:4326:11 854 857 1848 1852 EPSG:4326:12 1709 1715 3696 3705 EPSG:4326:13 3419 3430 7392 7410 EPSG:4326:14 6838 6860 14784 14820 EPSG:4326:15 13677 13720 29568 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1032 924 1450 EPSG:3857:12 1473 2065 1848 2901 EPSG:3857:13 2946 4130 3697 5802 EPSG:3857:14 5893 8260 7395 11605 EPSG:3857:15 11787 16520 14791 23210 EPSG:3857:16 23574 33041 29582 46421 EPSG:3857:17 47149 66082 59164 92842 EPSG:3857:18 94299 132164 118328 185685 EPSG:3857:19 188599 264328 236657 371370 EPSG:3857:20 377199 528657 473315 742741 EPSG:3857:21 754398 1057315 946631 1485482 EPSG:3857:22 1508796 2114630 1893262 2970965 EPSG:3857:23 3017592 4229260 3786524 5941930 EPSG:3857:24 6035184 8458521 7573048 11883861 EPSG:3857:25 12070369 16917042 15146097 23767722 EPSG:3857:26 24140738 33834084 30292195 47535445 EPSG:3857:27 48281477 67668168 60584391 95070890 EPSG:3857:28 96562954 135336336 121168782 190141781 EPSG:3857:29 193125908 270672673 242337564 380283562 EPSG:3857:30 386251817 541345347 484675128 760567125 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 7 11 EPSG:4326:4 3 8 14 22 EPSG:4326:5 7 16 28 45 EPSG:4326:6 15 32 57 90 EPSG:4326:7 31 65 115 181 EPSG:4326:8 63 130 231 362 EPSG:4326:9 127 260 462 725 EPSG:4326:10 255 520 924 1450 EPSG:4326:11 511 1041 1848 2901 EPSG:4326:12 1023 2082 3697 5802 EPSG:4326:13 2047 4164 7395 11605 EPSG:4326:14 4095 8328 14791 23210 EPSG:4326:15 8191 16657 29582 46421 EPSG:4326:16 16383 33314 59164 92842 EPSG:4326:17 32767 66628 118328 185685 EPSG:4326:18 65535 133256 236657 371370 EPSG:4326:19 131071 266513 473315 742741 EPSG:4326:20 262143 533026 946631 1485482 EPSG:4326:21 524287 1066052 1893262 2970965 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 231 362 EPSG:3857:10 368 516 462 725 EPSG:3857:11 736 1032 924 1450 EPSG:3857:12 1473 2065 1848 2901 EPSG:3857:13 2946 4130 3697 5802 EPSG:3857:14 5893 8260 7395 11605 EPSG:3857:15 11787 16520 14791 23210 EPSG:3857:16 23574 33041 29582 46421 EPSG:3857:17 47149 66082 59164 92842 EPSG:3857:18 94299 132164 118328 185685 EPSG:3857:19 188599 264328 236657 371370 EPSG:3857:20 377199 528657 473315 742741 EPSG:3857:21 754398 1057315 946631 1485482 EPSG:3857:22 1508796 2114630 1893262 2970965 EPSG:3857:23 3017592 4229260 3786524 5941930 EPSG:3857:24 6035184 8458521 7573048 11883861 EPSG:3857:25 12070369 16917042 15146097 23767722 EPSG:3857:26 24140738 33834084 30292195 47535445 EPSG:3857:27 48281477 67668168 60584391 95070890 EPSG:3857:28 96562954 135336336 121168782 190141781 EPSG:3857:29 193125908 270672673 242337564 380283562 EPSG:3857:30 386251817 541345347 484675128 760567125 Ocean Pollution (Shipping Lanes, Ports) 2008 - KNB This data layer combines estimates of pollution coming from commercial shipping and from ports. As such, it is a combination of the shipping and port volume data layers, with the port volume data plumed to estimate pollution from commercial ports (with exponential decline in intensity from the port). Ocean-based pollution is assumed to derive from commercial and recreational ship activity. No data on global recreational ship activity currently exist, and therefore we modelled this driver to oceans using a combination of the commercial shipping traffic data and port data. The shipping data provide an estimate of the occurrence of ships at a particular location, and therefore an estimate of the amount of pollution they produce (via fuel leaks, oil discharge, waste disposal, etc.) that is unique from their contribution to ship strikes, etc. described above. We recognize that ocean currents can disperse this pollution into untraveled regions, but small-scale oceanography is known for only a few select locations around the world, and pollutants are likely to be most concentrated in high traffic areas. The dispersal of port-derived pollution was modelled as a diffusive plume with a maximum distance of 100 km. These plumes were not clipped to shallow regions as was done for Invasive Species. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS." -179.9999997890976 -89.99765318080647 179.99802237886038 85.2846797894314 unea_pollution:08_ocean_pollution_halpern_KNB_WGS84 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262142 EPSG:3857:19 0 524287 0 524285 EPSG:3857:20 0 1048575 0 1048570 EPSG:3857:21 0 2097151 0 2097140 EPSG:3857:22 -1 4194303 0 4194280 EPSG:3857:23 -1 8388607 0 8388561 EPSG:3857:24 0 16777215 0 16777123 EPSG:3857:25 0 33554431 0 33554247 EPSG:3857:26 0 67108863 0 67108495 EPSG:3857:27 0 134217727 0 134216990 EPSG:3857:28 -1 268435455 0 268433981 EPSG:3857:29 0 536870911 0 536867962 EPSG:3857:30 0 1073741823 0 1073735925 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 6 255 0 511 EPSG:4326:9 13 511 0 1023 EPSG:4326:10 26 1023 0 2047 EPSG:4326:11 53 2047 0 4095 EPSG:4326:12 107 4095 0 8191 EPSG:4326:13 214 8191 0 16383 EPSG:4326:14 429 16383 0 32767 EPSG:4326:15 858 32767 0 65535 EPSG:4326:16 1716 65535 0 131071 EPSG:4326:17 3433 131070 0 262142 EPSG:4326:18 6867 262140 0 524285 EPSG:4326:19 13734 524281 0 1048570 EPSG:4326:20 27468 1048562 0 2097140 EPSG:4326:21 54937 2097124 0 4194280 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 0 31 0 31 EPSG:900913:6 0 63 0 63 EPSG:900913:7 0 127 0 127 EPSG:900913:8 0 255 0 255 EPSG:900913:9 0 511 0 511 EPSG:900913:10 0 1023 0 1023 EPSG:900913:11 0 2047 0 2047 EPSG:900913:12 0 4095 0 4095 EPSG:900913:13 0 8191 0 8191 EPSG:900913:14 0 16383 0 16383 EPSG:900913:15 0 32767 0 32767 EPSG:900913:16 0 65535 0 65535 EPSG:900913:17 0 131071 0 131071 EPSG:900913:18 0 262143 0 262142 EPSG:900913:19 0 524287 0 524285 EPSG:900913:20 0 1048575 0 1048570 EPSG:900913:21 0 2097151 0 2097140 EPSG:900913:22 0 4194303 0 4194280 EPSG:900913:23 0 8388607 0 8388561 EPSG:900913:24 0 16777215 0 16777123 EPSG:900913:25 0 33554431 0 33554247 EPSG:900913:26 0 67108863 0 67108495 EPSG:900913:27 0 134217727 0 134216990 EPSG:900913:28 0 268435455 0 268433981 EPSG:900913:29 0 536870911 0 536867962 EPSG:900913:30 0 1073741823 0 1073735925 Forest Connectivity (2000) (NASA) Forest connectivity identifies key areas between Intact Forest Landscapes (IFLs) in 2000. IFLs are large areas (greater than or equal to 500 square kilometres) of forest and other natural vegetation that show no remotely detected signs of human disturbance. Data Sources: Hansen, M.C., et al. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342, 850–853. DOI: <a href="https://doi.org/10.1126/science.1244693" target="_blank">10.1126/science.1244693</a> Potapov, P., et al., 2017. The last frontiers of wilderness: Tracking loss of intact forest landscapes from 2000 to 2013. Science Advances 3, e1600821. <a href="https://doi.org/10.1126/sciadv.1600821" target="_blank">10.1126/sciadv.1600821</a> -95.26972112443687 -26.368039400717038 167.81411628372408 25.126944105146272 MapX_UNDP_nd:c2000 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 3 15 EPSG:3857:5 13 18 7 30 EPSG:3857:6 27 36 15 61 EPSG:3857:7 54 73 30 123 EPSG:3857:8 109 147 60 247 EPSG:3857:9 219 294 120 494 EPSG:3857:10 438 589 241 989 EPSG:3857:11 876 1179 482 1978 EPSG:3857:12 1752 2359 964 3957 EPSG:3857:13 3504 4718 1928 7914 EPSG:3857:14 7009 9436 3856 15829 EPSG:3857:15 14019 18873 7712 31658 EPSG:3857:16 28039 37747 15424 63317 EPSG:3857:17 56079 75494 30849 126635 EPSG:3857:18 112158 150988 61698 253270 EPSG:3857:19 224317 301977 123397 506541 EPSG:3857:20 448635 603954 246794 1013082 EPSG:3857:21 897270 1207909 493589 2026164 EPSG:3857:22 1794540 2415818 987179 4052328 EPSG:3857:23 3589080 4831636 1974358 8104656 EPSG:3857:24 7178160 9663272 3948717 16209312 EPSG:3857:25 14356320 19326544 7897434 32418625 EPSG:3857:26 28712640 38653089 15794868 64837250 EPSG:3857:27 57425281 77306178 31589737 129674501 EPSG:3857:28 114850562 154612357 63179475 259349002 EPSG:3857:29 229701124 309224714 126358950 518698005 EPSG:3857:30 459402248 618449429 252717900 1037396010 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 1 2 1 7 EPSG:4326:3 2 5 3 15 EPSG:4326:4 5 10 7 30 EPSG:4326:5 11 20 15 61 EPSG:4326:6 23 41 30 123 EPSG:4326:7 46 82 60 247 EPSG:4326:8 92 165 120 494 EPSG:4326:9 184 331 241 989 EPSG:4326:10 369 662 482 1978 EPSG:4326:11 738 1324 964 3957 EPSG:4326:12 1476 2648 1928 7914 EPSG:4326:13 2952 5296 3856 15829 EPSG:4326:14 5904 10592 7712 31658 EPSG:4326:15 11809 21184 15424 63317 EPSG:4326:16 23619 42368 30849 126635 EPSG:4326:17 47239 84736 61698 253270 EPSG:4326:18 94478 169473 123397 506541 EPSG:4326:19 188956 338946 246794 1013082 EPSG:4326:20 377912 677892 493589 2026164 EPSG:4326:21 755825 1355785 987179 4052328 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 3 15 EPSG:3857:5 13 18 7 30 EPSG:3857:6 27 36 15 61 EPSG:3857:7 54 73 30 123 EPSG:3857:8 109 147 60 247 EPSG:3857:9 219 294 120 494 EPSG:3857:10 438 589 241 989 EPSG:3857:11 876 1179 482 1978 EPSG:3857:12 1752 2359 964 3957 EPSG:3857:13 3504 4718 1928 7914 EPSG:3857:14 7009 9436 3856 15829 EPSG:3857:15 14019 18873 7712 31658 EPSG:3857:16 28039 37747 15424 63317 EPSG:3857:17 56079 75494 30849 126635 EPSG:3857:18 112158 150988 61698 253270 EPSG:3857:19 224317 301977 123397 506541 EPSG:3857:20 448635 603954 246794 1013082 EPSG:3857:21 897270 1207909 493589 2026164 EPSG:3857:22 1794540 2415818 987179 4052328 EPSG:3857:23 3589080 4831636 1974358 8104656 EPSG:3857:24 7178160 9663272 3948717 16209312 EPSG:3857:25 14356320 19326544 7897434 32418625 EPSG:3857:26 28712640 38653089 15794868 64837250 EPSG:3857:27 57425281 77306178 31589737 129674501 EPSG:3857:28 114850562 154612357 63179475 259349002 EPSG:3857:29 229701124 309224714 126358950 518698005 EPSG:3857:30 459402248 618449429 252717900 1037396010 Tropical Cyclone Wind 1000 Years Return Period (km/h) The tropical cyclonic strong wind and storm surge hazard model uses information from 2594 historical tropical cyclones besides data on topography, terrain roughness, and bathymetry. The historical tropical cyclones used in the cyclone wind and storm surge hazard model for the GAR Atlas cover the five different oceanic basins: Northeast Pacific, Northwest Pacific, South Pacific, North Indian, South Indian and North Atlantic. In all cases, the data associated to each track were obtained from the IBTrACS database (Knapp et al., 2010). Topography data from the Shuttle Radar Topography Mission (SRTM) of NASA, which provides terrain elevation grids at a 90 meters resolution, delivered by quadrants over the world was used and, additionally, to account for surface roughness, polygons of urban areas worldwide were obtained from the Socioeconomic Data and Applications Centre, SEDAC (CIESIN et al., 2011). A digital bathymetry model, with a spatial resolution of 30 arc-seconds, from the GEBCO_08 (General Bathymetric Chart of the Oceans) Grid Database of the British Oceanographic Data Centre (2009) was used. More information about the cyclone wind and storm surge hazard model can be found in Cardona et al., 2015. Hazard analysis was performed using the software CAPRA Team Tropical Cyclones Hazard Modeler (Bernal, 2014). -180.0 -55.13566066745048 179.9077507461337 59.904585330559826 wesr_risk:cy_hazard_1000_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 0 15 EPSG:4326:4 2 12 0 31 EPSG:4326:5 5 25 0 63 EPSG:4326:6 10 51 0 127 EPSG:4326:7 21 103 0 255 EPSG:4326:8 42 206 0 511 EPSG:4326:9 85 412 0 1023 EPSG:4326:10 171 825 0 2047 EPSG:4326:11 342 1651 0 4094 EPSG:4326:12 684 3302 0 8189 EPSG:4326:13 1369 6605 0 16379 EPSG:4326:14 2739 13210 0 32759 EPSG:4326:15 5478 26421 0 65519 EPSG:4326:16 10957 52842 0 131038 EPSG:4326:17 21914 105684 0 262076 EPSG:4326:18 43829 211369 0 524153 EPSG:4326:19 87659 422738 0 1048307 EPSG:4326:20 175318 845476 0 2096614 EPSG:4326:21 350636 1690953 0 4193229 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 10 0 15 EPSG:3857:5 9 21 0 31 EPSG:3857:6 18 43 0 63 EPSG:3857:7 37 87 0 127 EPSG:3857:8 74 175 0 255 EPSG:3857:9 148 350 0 511 EPSG:3857:10 297 700 0 1023 EPSG:3857:11 595 1401 0 2047 EPSG:3857:12 1191 2803 0 4094 EPSG:3857:13 2383 5606 0 8189 EPSG:3857:14 4766 11212 0 16379 EPSG:3857:15 9533 22425 0 32759 EPSG:3857:16 19066 44850 0 65519 EPSG:3857:17 38132 89700 0 131038 EPSG:3857:18 76265 179400 0 262076 EPSG:3857:19 152530 358801 0 524153 EPSG:3857:20 305061 717603 0 1048307 EPSG:3857:21 610122 1435207 0 2096614 EPSG:3857:22 1220244 2870414 0 4193229 EPSG:3857:23 2440488 5740829 0 8386458 EPSG:3857:24 4880977 11481659 0 16772916 EPSG:3857:25 9761955 22963319 0 33545833 EPSG:3857:26 19523911 45926638 0 67091667 EPSG:3857:27 39047823 91853276 0 134183334 EPSG:3857:28 78095647 183706553 0 268366669 EPSG:3857:29 156191295 367413106 0 536733339 EPSG:3857:30 312382591 734826213 0 1073466679 Combination Tsunami/Mangroves at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_man6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 ecuador_ecosistemas_clean_ecosistema -81.09264033289094 -5.015146735772655 -75.1950953254417 1.4627334137699841 MAPX_nd:ecuador_ecosistemas_clean_ecosistema image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 16 8 9 EPSG:3857:6 31 32 17 18 EPSG:3857:7 63 65 35 37 EPSG:3857:8 126 131 70 74 EPSG:3857:9 253 263 140 149 EPSG:3857:10 507 526 281 298 EPSG:3857:11 1015 1052 562 596 EPSG:3857:12 2031 2105 1125 1192 EPSG:3857:13 4062 4210 2250 2384 EPSG:3857:14 8125 8420 4501 4769 EPSG:3857:15 16250 16841 9002 9539 EPSG:3857:16 32501 33682 18005 19079 EPSG:3857:17 65003 67364 36011 38158 EPSG:3857:18 130006 134728 72022 76316 EPSG:3857:19 260013 269457 144044 152633 EPSG:3857:20 520027 538914 288088 305266 EPSG:3857:21 1040054 1077828 576177 610532 EPSG:3857:22 2080108 2155657 1152354 1221065 EPSG:3857:23 4160216 4311314 2304708 2442131 EPSG:3857:24 8320432 8622629 4609417 4884262 EPSG:3857:25 16640864 17245259 9218834 9768525 EPSG:3857:26 33281729 34490519 18437668 19537050 EPSG:3857:27 66563458 68981038 36875336 39074100 EPSG:3857:28 133126916 137962076 73750672 78148201 EPSG:3857:29 266253832 275924153 147501345 156296402 EPSG:3857:30 532507665 551848307 295002691 312592804 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 1 1 1 EPSG:4326:2 1 2 2 2 EPSG:4326:3 3 4 4 4 EPSG:4326:4 7 8 8 9 EPSG:4326:5 15 16 17 18 EPSG:4326:6 31 33 35 37 EPSG:4326:7 62 67 70 74 EPSG:4326:8 125 135 140 149 EPSG:4326:9 251 270 281 298 EPSG:4326:10 503 540 562 596 EPSG:4326:11 1007 1081 1125 1192 EPSG:4326:12 2014 2162 2250 2384 EPSG:4326:13 4029 4324 4501 4769 EPSG:4326:14 8058 8648 9002 9539 EPSG:4326:15 16117 17296 18005 19079 EPSG:4326:16 32235 34593 36011 38158 EPSG:4326:17 64470 69187 72022 76316 EPSG:4326:18 128941 138375 144044 152633 EPSG:4326:19 257883 276751 288088 305266 EPSG:4326:20 515766 553503 576177 610532 EPSG:4326:21 1031533 1107006 1152354 1221065 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 0 EPSG:900913:2 1 2 1 1 EPSG:900913:3 3 4 2 2 EPSG:900913:4 7 8 4 4 EPSG:900913:5 15 16 8 9 EPSG:900913:6 31 32 17 18 EPSG:900913:7 63 65 35 37 EPSG:900913:8 126 131 70 74 EPSG:900913:9 253 263 140 149 EPSG:900913:10 507 526 281 298 EPSG:900913:11 1015 1052 562 596 EPSG:900913:12 2031 2105 1125 1192 EPSG:900913:13 4062 4210 2250 2384 EPSG:900913:14 8125 8420 4501 4769 EPSG:900913:15 16250 16841 9002 9539 EPSG:900913:16 32501 33682 18005 19079 EPSG:900913:17 65003 67364 36011 38158 EPSG:900913:18 130006 134728 72022 76316 EPSG:900913:19 260013 269457 144044 152633 EPSG:900913:20 520027 538914 288088 305266 EPSG:900913:21 1040054 1077828 576177 610532 EPSG:900913:22 2080108 2155657 1152354 1221065 EPSG:900913:23 4160216 4311314 2304708 2442131 EPSG:900913:24 8320432 8622629 4609417 4884262 EPSG:900913:25 16640864 17245259 9218834 9768525 EPSG:900913:26 33281729 34490519 18437668 19537050 EPSG:900913:27 66563458 68981038 36875336 39074100 EPSG:900913:28 133126916 137962076 73750672 78148201 EPSG:900913:29 266253832 275924153 147501345 156296402 EPSG:900913:30 532507665 551848307 295002691 312592804 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 16 8 9 EPSG:3857:6 31 32 17 18 EPSG:3857:7 63 65 35 37 EPSG:3857:8 126 131 70 74 EPSG:3857:9 253 263 140 149 EPSG:3857:10 507 526 281 298 EPSG:3857:11 1015 1052 562 596 EPSG:3857:12 2031 2105 1125 1192 EPSG:3857:13 4062 4210 2250 2384 EPSG:3857:14 8125 8420 4501 4769 EPSG:3857:15 16250 16841 9002 9539 EPSG:3857:16 32501 33682 18005 19079 EPSG:3857:17 65003 67364 36011 38158 EPSG:3857:18 130006 134728 72022 76316 EPSG:3857:19 260013 269457 144044 152633 EPSG:3857:20 520027 538914 288088 305266 EPSG:3857:21 1040054 1077828 576177 610532 EPSG:3857:22 2080108 2155657 1152354 1221065 EPSG:3857:23 4160216 4311314 2304708 2442131 EPSG:3857:24 8320432 8622629 4609417 4884262 EPSG:3857:25 16640864 17245259 9218834 9768525 EPSG:3857:26 33281729 34490519 18437668 19537050 EPSG:3857:27 66563458 68981038 36875336 39074100 EPSG:3857:28 133126916 137962076 73750672 78148201 EPSG:3857:29 266253832 275924153 147501345 156296402 EPSG:3857:30 532507665 551848307 295002691 312592804 Winter temperature change (°C) for the period 2040 - 2059 under the RCP 2.6 scenario Projected change of temperature for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:tas_djf_MIDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Crop Suitability 1981-2010 This dataset show general agricultural suitability at a spatial resolution of 30 arc-second (~1km), considering rainfed conditions and irrigation on currently irrigated areas. The agricultural suitability represents for each pixel the maximum suitability value of considered 16 plants, including: We show a subset of the data that covers three time periods (1981-2010, 2011-2040, 2071-2100), as well as changes in agricultural suitability over the same periods.<br><br>For futher details see: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107522">Zabel F., Putzenlechner B., Mauser W. (2014): Global agricultural land resources – a high resolution suitability evaluation and its perspectives until 2100 under climate change conditions</a><br/><br>Data can also be downloaded from <a href="http://geoportal-glues.ufz.de/stories/globalsuitability.html">here</a>.<br/> -180.0 -60.0 180.0 90.0 MapX_UNDP:overall_cropsuit_i_1981-2010 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Peak Ground Acceleration PGA 2475 Years (cm/s2) For the GAR Atlas, a fully probabilistic seismic hazard analysis at global level was developed by CIMNE and INGENIAR Ltda. This hazard model is a continuation and improvement of the one developed in the framework of GAR13 where a set of tectonic provinces were identified and characterized by means of a set of parameters that describe the future seismic activity on each of them based on historical records together with relationships to obtain hazard intensities as a function of magnitude and distance. The hazard analysis was performed using the program CRISIS2014, a state-of-the-art tool for these kinds of tasks and widely known and acknowledged by experts in the field across the world. The chosen hazard intensity measure for this case was spectral acceleration and to guarantee a good connection between the hazard and the exposure characteristics, results for several ordinates beteween 0.0 and 2.3 seconds were computed. More details about the probabilistic seismic hazard analysis can be found in Cardona et al. (2015). -180.0 -90.0 180.0 90.0 wesr_risk:pga_2475_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Tree Canopy Change 1982 - 2016 This analysis of 35 years’ worth of satellite data (at approximately 25 square kilometer resolution at the equator) provides a comprehensive record of global land-change dynamics during the period 1982–2016. Contrary to the prevailing view that forest area has declined globally — tree cover has increased by 2.24 million km2 (+7.1% relative to the 1982 level), largely the result of a net loss in the tropics being outweighed by a net gain in the extratropics. Global bare ground cover has decreased by 1.16 million km2 (−3.1%), most notably in agricultural regions in Asia. Of all land changes, 60% are associated with direct human activities and 40% with indirect drivers such as climate change. Land-use change exhibits regional dominance, including tropical deforestation and agricultural expansion, temperate reforestation or afforestation, cropland intensification and urbanization. Consistently across all climate domains, montane systems have gained tree cover and many arid and semi-arid ecosystems have lost vegetation cover.<br><br>For full details see: <a href="https://doi.org/10.1038/s41586-018-0411-9">Song, X.-P., Hansen, M.C., Stehman, S.V., Potapov, P.V., Tyukavina, A., Vermote, E.F., Townshend, J.R., 2018. Global land change from 1982 to 2016. Nature 1</a><br/>. -180.0 -90.0 180.0 90.0 MapX_UNDP:Tree_canopy_change_1982-2016 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Satellite Mogadisho Urban Growth 2004 Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2004-09-24. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov. 45.195394649846214 1.955229029551538 45.47923060483454 2.141476613353127 MAPX:Mogadisho_Landsat7_20040924-531 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 10 10 EPSG:3857:5 15 15 20 20 EPSG:3857:6 31 31 40 40 EPSG:3857:7 63 63 80 80 EPSG:3857:8 126 126 160 160 EPSG:3857:9 252 253 320 320 EPSG:3857:10 505 506 640 641 EPSG:3857:11 1011 1012 1281 1282 EPSG:3857:12 2023 2025 2562 2565 EPSG:3857:13 4047 4051 5124 5130 EPSG:3857:14 8094 8102 10248 10261 EPSG:3857:15 16189 16205 20497 20523 EPSG:3857:16 32378 32411 40995 41047 EPSG:3857:17 64756 64823 81991 82094 EPSG:3857:18 129512 129647 163982 164188 EPSG:3857:19 259024 259295 327964 328377 EPSG:3857:20 518049 518591 655929 656755 EPSG:3857:21 1036098 1037183 1311858 1313511 EPSG:3857:22 2072196 2074367 2623716 2627023 EPSG:3857:23 4144392 4148735 5247433 5254046 EPSG:3857:24 8288784 8297470 10494866 10508093 EPSG:3857:25 16577569 16594940 20989732 21016187 EPSG:3857:26 33155138 33189880 41979464 42032375 EPSG:3857:27 66310277 66379760 83958928 84064750 EPSG:3857:28 132620555 132759520 167917856 168129500 EPSG:3857:29 265241110 265519041 335835713 336259000 EPSG:3857:30 530482221 531038082 671671427 672518000 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 10 10 EPSG:4326:4 7 7 20 20 EPSG:4326:5 15 15 40 40 EPSG:4326:6 31 31 80 80 EPSG:4326:7 62 62 160 160 EPSG:4326:8 124 125 320 320 EPSG:4326:9 249 250 640 641 EPSG:4326:10 499 500 1281 1282 EPSG:4326:11 999 1001 2562 2565 EPSG:4326:12 1999 2003 5124 5130 EPSG:4326:13 3998 4007 10248 10261 EPSG:4326:14 7997 8014 20497 20523 EPSG:4326:15 15994 16028 40995 41047 EPSG:4326:16 31988 32056 81991 82094 EPSG:4326:17 63976 64112 163982 164188 EPSG:4326:18 127953 128224 327964 328377 EPSG:4326:19 255906 256448 655929 656755 EPSG:4326:20 511812 512897 1311858 1313511 EPSG:4326:21 1023625 1025795 2623716 2627023 EPSG:900913 International Boundaries Polygons Level 0 - GAUL -180.0 -90.0 180.0 84.4950561523438 grid_data_core_pro:g2015_2014_0 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 7 255 0 511 EPSG:4326:9 15 511 0 1023 EPSG:4326:10 31 1023 0 2047 EPSG:4326:11 62 2047 0 4095 EPSG:4326:12 125 4095 0 8191 EPSG:4326:13 250 8191 0 16383 EPSG:4326:14 501 16383 0 32767 EPSG:4326:15 1002 32767 0 65535 EPSG:4326:16 2004 65535 0 131071 EPSG:4326:17 4008 131071 0 262143 EPSG:4326:18 8017 262143 0 524287 EPSG:4326:19 16034 524287 0 1048575 EPSG:4326:20 32068 1048575 0 2097151 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EPSG:900913:29 9111477 536870911 0 536870911 EPSG:900913:30 18222955 1073741823 0 1073741823 International Boundaries Polygons Level 1 - GAUL -180.0 -60.199836730957 180.0 84.3429794311523 grid_data_core_pro:g2015_2014_1 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 8 213 0 511 EPSG:4326:9 16 427 0 1023 EPSG:4326:10 32 854 0 2047 EPSG:4326:11 64 1708 0 4095 EPSG:4326:12 128 3417 0 8191 EPSG:4326:13 257 6835 0 16383 EPSG:4326:14 514 13671 0 32767 EPSG:4326:15 1029 27343 0 65535 EPSG:4326:16 2059 54686 0 131071 EPSG:4326:17 4119 109372 0 262143 EPSG:4326:18 8238 218744 0 524287 EPSG:4326:19 16477 437488 0 1048575 EPSG:4326:20 32954 874977 0 2097151 EPSG:4326:21 65909 1749954 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 22 0 31 EPSG:900913:6 1 45 0 63 EPSG:900913:7 2 90 0 127 EPSG:900913:8 5 181 0 255 EPSG:900913:9 10 363 0 511 EPSG:900913:10 21 727 0 1023 EPSG:900913:11 43 1455 0 2047 EPSG:900913:12 87 2911 0 4095 EPSG:900913:13 174 5822 0 8191 EPSG:900913:14 349 11644 0 16383 EPSG:900913:15 698 23288 0 32767 EPSG:900913:16 1396 46577 0 65535 EPSG:900913:17 2793 93154 0 131071 EPSG:900913:18 5587 186309 0 262143 EPSG:900913:19 11175 372618 0 524287 EPSG:900913:20 22350 745237 0 1048575 EPSG:900913:21 44701 1490475 0 2097151 EPSG:900913:22 89403 2980950 0 4194303 EPSG:900913:23 178806 5961900 0 8388607 EPSG:900913:24 357613 11923801 0 16777215 EPSG:900913:25 715226 23847602 0 33554431 EPSG:900913:26 1430453 47695204 0 67108863 EPSG:900913:27 2860906 95390409 0 134217727 EPSG:900913:28 5721812 190780818 0 268435455 EPSG:900913:29 11443624 381561637 0 536870911 EPSG:900913:30 22887249 763123274 0 1073741823 International Boundaries Polygons Level 2 - GAUL -180.0 -60.1909866333008 180.0 82.5640869140625 grid_data_core_pro:g2015_2014_2 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 5 106 0 255 EPSG:4326:8 10 213 0 511 EPSG:4326:9 21 427 0 1023 EPSG:4326:10 42 854 0 2047 EPSG:4326:11 84 1708 0 4095 EPSG:4326:12 169 3417 0 8191 EPSG:4326:13 338 6835 0 16383 EPSG:4326:14 676 13670 0 32767 EPSG:4326:15 1353 27341 0 65535 EPSG:4326:16 2707 54682 0 131071 EPSG:4326:17 5414 109365 0 262143 EPSG:4326:18 10829 218731 0 524287 EPSG:4326:19 21658 437462 0 1048575 EPSG:4326:20 43317 874925 0 2097151 EPSG:4326:21 86634 1749851 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 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tza_natural_hazards_exposure 29.44107835330835 -11.771764043500044 40.45015746710648 -0.9815888211757782 mapx_chemobs:tza_natural_hazards_exposure image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 17 18 19 EPSG:3857:6 32 34 37 39 EPSG:3857:7 64 68 74 78 EPSG:3857:8 128 136 148 156 EPSG:3857:9 257 272 297 313 EPSG:3857:10 514 545 595 627 EPSG:3857:11 1029 1091 1191 1254 EPSG:3857:12 2059 2182 2382 2508 EPSG:3857:13 4118 4365 4765 5016 EPSG:3857:14 8236 8731 9531 10032 EPSG:3857:15 16473 17463 19063 20065 EPSG:3857:16 32946 34926 38127 40131 EPSG:3857:17 65893 69852 76255 80263 EPSG:3857:18 131786 139704 152510 160526 EPSG:3857:19 263573 279409 305020 321053 EPSG:3857:20 527147 558819 610041 642107 EPSG:3857:21 1054294 1117639 1220082 1284215 EPSG:3857:22 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20547443 EPSG:3857:26 33737422 35764451 39042646 41094887 EPSG:3857:27 67474844 71528902 78085293 82189775 EPSG:3857:28 134949689 143057805 156170587 164379551 EPSG:3857:29 269899378 286115610 312341174 328759103 EPSG:3857:30 539798757 572231221 624682348 657518206 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from NASA Goddard Institute for Space Studies, ModelE20/Russell Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_giss_model_e_r_5km_2041-2060_debiasedmean_tas_av_12m_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 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text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 17 18 19 EPSG:3857:6 32 34 37 39 EPSG:3857:7 64 68 74 78 EPSG:3857:8 128 136 148 156 EPSG:3857:9 257 272 297 313 EPSG:3857:10 514 545 595 627 EPSG:3857:11 1029 1091 1191 1254 EPSG:3857:12 2059 2182 2382 2508 EPSG:3857:13 4118 4365 4765 5016 EPSG:3857:14 8236 8731 9531 10032 EPSG:3857:15 16473 17463 19063 20065 EPSG:3857:16 32946 34926 38127 40131 EPSG:3857:17 65893 69852 76255 80263 EPSG:3857:18 131786 139705 152510 160526 EPSG:3857:19 263573 279410 305020 321053 EPSG:3857:20 527147 558820 610041 642107 EPSG:3857:21 1054294 1117640 1220082 1284215 EPSG:3857:22 2108588 2235281 2440165 2568430 EPSG:3857:23 4217176 4470563 4880330 5136860 EPSG:3857:24 8434353 8941127 9760661 10273721 EPSG:3857:25 16868707 17882255 19521323 20547443 EPSG:3857:26 33737414 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35764511 39042646 41094887 EPSG:3857:27 67474829 71529023 78085293 82189774 EPSG:3857:28 134949659 143058047 156170587 164379548 EPSG:3857:29 269899318 286116094 312341175 328759096 EPSG:3857:30 539798637 572232189 624682351 657518192 Combination Tsunami/Sea grasses at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_sea9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 madagascar_remote_site_screening_res50 43.191379547000075 -25.608932661999972 50.48387954700007 -11.94543266199997 mapx_chemobs:madagascar_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 5 EPSG:3857:4 8 9 9 10 EPSG:3857:5 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572760504 615930580 665694219 687444947 Mean temperatures 2014 - Central African Republic Mean observed temperatures in 2014 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2014_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Average year precipitations (1991-2020) Average year precipitations in mm across the period 1991-2020. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_91_20_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Average year precipitations (2021-2022) Average year precipitations in mm across the period 2021-2022. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_21_22_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 wesr_climate_perma1_5 -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_perma1_5 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 hfp2010_meris_wgs Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11 -179.99997804642848 -65.24741434935741 180.0 89.8976232152096 MapX_UNDP_nd:hfp2010_meris_wgs image/png image/vnd.jpeg-png image/jpeg image/png8 EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12146 0 16383 EPSG:3857:15 0 24293 0 32767 EPSG:3857:16 0 48587 0 65535 EPSG:3857:17 0 97175 0 131071 EPSG:3857:18 0 194351 0 262143 EPSG:3857:19 0 388703 0 524287 EPSG:3857:20 0 777407 0 1048575 EPSG:3857:21 0 1554814 0 2097151 EPSG:3857:22 -1 3109629 0 4194304 EPSG:3857:23 -1 6219258 0 8388608 EPSG:3857:24 0 12438517 1 16777215 EPSG:3857:25 0 24877035 2 33554431 EPSG:3857:26 0 49754070 4 67108863 EPSG:3857:27 0 99508140 8 134217727 EPSG:3857:28 -1 199016280 16 268435456 EPSG:3857:29 0 398032561 32 536870911 EPSG:3857:30 0 796065123 65 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 55 0 127 EPSG:4326:7 0 110 0 255 EPSG:4326:8 0 220 0 511 EPSG:4326:9 0 441 0 1023 EPSG:4326:10 0 883 0 2047 EPSG:4326:11 1 1766 0 4095 EPSG:4326:12 2 3532 0 8191 EPSG:4326:13 4 7065 0 16383 EPSG:4326:14 9 14130 0 32767 EPSG:4326:15 18 28261 0 65535 EPSG:4326:16 37 56523 0 131071 EPSG:4326:17 74 113047 0 262143 EPSG:4326:18 149 226095 0 524287 EPSG:4326:19 298 452190 0 1048575 EPSG:4326:20 596 904381 0 2097151 EPSG:4326:21 1192 1808763 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 23 0 31 EPSG:900913:6 0 47 0 63 EPSG:900913:7 0 94 0 127 EPSG:900913:8 0 189 0 255 EPSG:900913:9 0 379 0 511 EPSG:900913:10 0 759 0 1023 EPSG:900913:11 0 1518 0 2047 EPSG:900913:12 0 3036 0 4095 EPSG:900913:13 0 6073 0 8191 EPSG:900913:14 0 12146 0 16383 EPSG:900913:15 0 24293 0 32767 EPSG:900913:16 0 48587 0 65535 EPSG:900913:17 0 97175 0 131071 EPSG:900913:18 0 194351 0 262143 EPSG:900913:19 0 388703 0 524287 EPSG:900913:20 0 777407 0 1048575 EPSG:900913:21 0 1554814 0 2097151 EPSG:900913:22 0 3109629 0 4194303 EPSG:900913:23 0 6219258 0 8388607 EPSG:900913:24 0 12438517 1 16777215 EPSG:900913:25 0 24877035 2 33554431 EPSG:900913:26 0 49754070 4 67108863 EPSG:900913:27 0 99508140 8 134217727 EPSG:900913:28 0 199016280 16 268435455 EPSG:900913:29 0 398032561 32 536870911 EPSG:900913:30 0 796065123 65 1073741823 Combination Landslide/Forest at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_lds_for6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 frac_cats_2016_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_2016_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 v432_CO2_excl_C_1970_opt_deflate -180.0 -77.95 179.95 88.15000000000002 wesr_climat:v432_CO2_excl_C_1970_opt_deflate image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 0 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 -1 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 0 115142440 0 134199086 EPSG:3857:28 -1 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 0 921139526 0 1073592693 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 -1 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 0 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 -1 115142440 0 134199086 EPSG:3857:28 0 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 -1 921139526 0 1073592693 Combination Tropical cyclone surge/ Forest at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_for6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Coastal Vulnerability Index The Coastal Vulnerability Index shows the susceptibility of coastal areas to extreme climate impacts and their capacity to recover, survive, and adapt depending on their geo-morphological, ecological, and socioeconomic characteristics. Combination of climate related / environmental variables: - Elevation; - Coastal slope; - Land roughness; - Distance from the shoreline; - Ecosystem health and gender-related variables: - Education; - Labour market; - Health status and quality of life; - Socio-economic status. Area: Morocco Child Project: SCCF Source: GEF-MedProgramme -6.243055555556 34.6680215 -3.8041666647160004 35.922465945448 medprogramme:MOR_cvi_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 6 6 7 7 EPSG:3857:5 12 12 15 15 EPSG:3857:6 25 25 30 31 EPSG:3857:7 50 50 61 62 EPSG:3857:8 100 101 123 125 EPSG:3857:9 201 203 247 250 EPSG:3857:10 402 406 494 501 EPSG:3857:11 804 813 988 1002 EPSG:3857:12 1609 1627 1976 2004 EPSG:3857:13 3219 3254 3953 4009 EPSG:3857:14 6438 6508 7907 8018 EPSG:3857:15 12876 13016 15815 16037 EPSG:3857:16 25752 26032 31631 32075 EPSG:3857:17 51504 52064 63262 64150 EPSG:3857:18 103009 104129 126525 128301 EPSG:3857:19 206019 208258 253051 256603 EPSG:3857:20 412039 416516 506103 513207 EPSG:3857:21 824079 833033 1012207 1026415 EPSG:3857:22 1648159 1666066 2024415 2052830 EPSG:3857:23 3296318 3332133 4048830 4105660 EPSG:3857:24 6592637 6664267 8097660 8211320 EPSG:3857:25 13185274 13328535 16195321 16422641 EPSG:3857:26 26370549 26657071 32390642 32845283 EPSG:3857:27 52741099 53314142 64781284 65690567 EPSG:3857:28 105482198 106628284 129562568 131381135 EPSG:3857:29 210964396 213256568 259125136 262762271 EPSG:3857:30 421928792 426513136 518250273 525524542 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 2 2 7 7 EPSG:4326:4 4 4 15 15 EPSG:4326:5 9 9 30 31 EPSG:4326:6 19 19 61 62 EPSG:4326:7 38 39 123 125 EPSG:4326:8 76 78 247 250 EPSG:4326:9 153 157 494 501 EPSG:4326:10 307 314 988 1002 EPSG:4326:11 615 629 1976 2004 EPSG:4326:12 1230 1259 3953 4009 EPSG:4326:13 2461 2518 7907 8018 EPSG:4326:14 4922 5036 15815 16037 EPSG:4326:15 9844 10072 31631 32075 EPSG:4326:16 19689 20145 63262 64150 EPSG:4326:17 39378 40291 126525 128301 EPSG:4326:18 78756 80583 253051 256603 EPSG:4326:19 157512 161166 506103 513207 EPSG:4326:20 315024 322332 1012207 1026415 EPSG:4326:21 630048 644664 2024415 2052830 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 6 6 7 7 EPSG:3857:5 12 12 15 15 EPSG:3857:6 25 25 30 31 EPSG:3857:7 50 50 61 62 EPSG:3857:8 100 101 123 125 EPSG:3857:9 201 203 247 250 EPSG:3857:10 402 406 494 501 EPSG:3857:11 804 813 988 1002 EPSG:3857:12 1609 1627 1976 2004 EPSG:3857:13 3219 3254 3953 4009 EPSG:3857:14 6438 6508 7907 8018 EPSG:3857:15 12876 13016 15815 16037 EPSG:3857:16 25752 26032 31631 32075 EPSG:3857:17 51504 52064 63262 64150 EPSG:3857:18 103009 104129 126525 128301 EPSG:3857:19 206019 208258 253051 256603 EPSG:3857:20 412039 416516 506103 513207 EPSG:3857:21 824079 833033 1012207 1026415 EPSG:3857:22 1648159 1666066 2024415 2052830 EPSG:3857:23 3296318 3332133 4048830 4105660 EPSG:3857:24 6592637 6664267 8097660 8211320 EPSG:3857:25 13185274 13328535 16195321 16422641 EPSG:3857:26 26370549 26657071 32390642 32845283 EPSG:3857:27 52741099 53314142 64781284 65690567 EPSG:3857:28 105482198 106628284 129562568 131381135 EPSG:3857:29 210964396 213256568 259125136 262762271 EPSG:3857:30 421928792 426513136 518250273 525524542 wesr_climate_perma1 -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_perma1 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 wesr_climate_perma2 -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_perma2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 wesr_climate_perma3 -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_perma3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 wesr_climate_perma4 -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_perma4 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 wesr_climate_perma5 -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_perma5 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 wesr_climate_perma6 -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_perma6 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Year precipitations 2005 - Central African Republic Total precipitations observed in 2005 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2005_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Automn precipitations change (%) for the period 2020 - 2039 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_son_NEARREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Flood Hazard 1000 Years - SSP5 RCP8.5 The hydrological model used is the Continuum model (Silvestro et al. 2013 and 2015). It is a continuous, distributed and physically based hydrological model able to reproduce the spatial-temporal evolution of soil moisture, energy fluxes, surface soil temperature, evapotranspiration and discharge. Climate dataset used for the simulation of basin response are the W5E5 Global Meteorological dataset for present climate, and the ISIMIP3b Global Meteorological reanalysis dataset for the futur climate. In order to generate flood hazard maps, resulting discharge estimates are input to an hydraulic model based on the Manning equation that compute channel uniform flow depth. This simplified approach fits to determine flood maps on large areas. -180.0 -90.0 180.0 90.0 testing:GLOBAL_RCP85_h1000glob image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Winter precipitations change (%) for the period 2020 - 2039 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario. Data provided by MedECC AtlasProjected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_djf_NEARREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Kerala Flood 25 Years RP - RCP85 Kerala State flood hazard map - RCP 8.5 scenario. Maximum expected flood event water height in a 25 years return period, expressed in cm. 74.85958333333333 8.25375 77.49208333333334 12.842916666666673 ECO-DRR:Kerala_Flood_25_Yrs_RCP85 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185583 187500 EPSG:4326:18 112368 119051 371166 375000 EPSG:4326:19 224736 238103 742332 750000 EPSG:4326:20 449472 476206 1484664 1500000 EPSG:4326:21 898945 952412 2969329 3000000 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 Kerala Flood 50 Years RP - RCP85 Kerala State flood hazard map - RCP 8.5 scenario. Maximum expected flood event water height in a 50 years return period, expressed in cm. 74.85958333333333 8.25375 77.49208333333334 12.842916666666673 ECO-DRR:Kerala_Flood_50_Yrs_RCP85 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185583 187500 EPSG:4326:18 112368 119051 371166 375000 EPSG:4326:19 224736 238103 742332 750000 EPSG:4326:20 449472 476206 1484664 1500000 EPSG:4326:21 898945 952412 2969329 3000000 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185583 187500 EPSG:3857:19 243281 250081 371166 375000 EPSG:3857:20 486563 500163 742332 750000 EPSG:3857:21 973126 1000327 1484664 1500000 EPSG:3857:22 1946252 2000654 2969329 3000000 EPSG:3857:23 3892504 4001309 5938658 6000000 EPSG:3857:24 7785008 8002618 11877317 12000000 EPSG:3857:25 15570017 16005236 23754634 24000001 EPSG:3857:26 31140035 32010472 47509269 48000003 EPSG:3857:27 62280070 64020944 95018539 96000006 EPSG:3857:28 124560140 128041888 190037079 192000013 EPSG:3857:29 249120281 256083777 380074158 384000026 EPSG:3857:30 498240563 512167555 760148316 768000053 POP_LEKOUMOU_2019_finale_Worlpop_opt 12.796059046335326 -4.052797249963222 14.35138242981778 -2.088002670078685 AccessMod:POP_LEKOUMOU_2019_finale_Worlpop_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 8 8 EPSG:3857:5 16 16 17 17 EPSG:3857:6 32 32 34 34 EPSG:3857:7 64 65 68 69 EPSG:3857:8 129 130 137 138 EPSG:3857:9 258 261 274 276 EPSG:3857:10 517 523 548 552 EPSG:3857:11 1035 1047 1096 1105 EPSG:3857:12 2071 2094 2193 2211 EPSG:3857:13 4143 4188 4387 4422 EPSG:3857:14 8287 8376 8774 8845 EPSG:3857:15 16574 16753 17548 17690 EPSG:3857:16 33148 33506 35097 35380 EPSG:3857:17 66296 67012 70194 70761 EPSG:3857:18 132592 134025 140389 141522 EPSG:3857:19 265185 268051 280779 283044 EPSG:3857:20 530371 536102 561559 566089 EPSG:3857:21 1060742 1072204 1123118 1132178 EPSG:3857:22 2121484 2144409 2246236 2264357 EPSG:3857:23 4242968 4288819 4492473 4528715 EPSG:3857:24 8485937 8577639 8984947 9057430 EPSG:3857:25 16971875 17155279 17969895 18114861 EPSG:3857:26 33943750 34310558 35939790 36229723 EPSG:3857:27 67887500 68621117 71879580 72459447 EPSG:3857:28 135775000 137242235 143759161 144918894 EPSG:3857:29 271550000 274484471 287518322 289837788 EPSG:3857:30 543100001 548968943 575036644 579675577 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 8 8 EPSG:4326:4 8 8 17 17 EPSG:4326:5 16 16 34 34 EPSG:4326:6 32 33 68 69 EPSG:4326:7 65 66 137 138 EPSG:4326:8 130 133 274 276 EPSG:4326:9 261 267 548 552 EPSG:4326:10 523 535 1096 1105 EPSG:4326:11 1047 1070 2193 2211 EPSG:4326:12 2095 2140 4387 4422 EPSG:4326:13 4191 4280 8774 8845 EPSG:4326:14 8382 8560 17548 17690 EPSG:4326:15 16764 17121 35097 35380 EPSG:4326:16 33528 34243 70194 70761 EPSG:4326:17 67056 68487 140389 141522 EPSG:4326:18 134112 136974 280779 283044 EPSG:4326:19 268225 273948 561559 566089 EPSG:4326:20 536451 547897 1123118 1132178 EPSG:4326:21 1072902 1095794 2246236 2264357 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 8 8 EPSG:3857:5 16 16 17 17 EPSG:3857:6 32 32 34 34 EPSG:3857:7 64 65 68 69 EPSG:3857:8 129 130 137 138 EPSG:3857:9 258 261 274 276 EPSG:3857:10 517 523 548 552 EPSG:3857:11 1035 1047 1096 1105 EPSG:3857:12 2071 2094 2193 2211 EPSG:3857:13 4143 4188 4387 4422 EPSG:3857:14 8287 8376 8774 8845 EPSG:3857:15 16574 16753 17548 17690 EPSG:3857:16 33148 33506 35097 35380 EPSG:3857:17 66296 67012 70194 70761 EPSG:3857:18 132592 134025 140389 141522 EPSG:3857:19 265185 268051 280779 283044 EPSG:3857:20 530371 536102 561559 566089 EPSG:3857:21 1060742 1072204 1123118 1132178 EPSG:3857:22 2121484 2144409 2246236 2264357 EPSG:3857:23 4242968 4288819 4492473 4528715 EPSG:3857:24 8485937 8577639 8984947 9057430 EPSG:3857:25 16971875 17155279 17969895 18114861 EPSG:3857:26 33943750 34310558 35939790 36229723 EPSG:3857:27 67887500 68621117 71879580 72459447 EPSG:3857:28 135775000 137242235 143759161 144918894 EPSG:3857:29 271550000 274484471 287518322 289837788 EPSG:3857:30 543100001 548968943 575036644 579675577 Temperature change trend (2011-2020) Trend of year temperatures change in '°C per year' across the period 2011-2020. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_11_20_lm image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Precipitation anomalies (mm) 2045-2065 (RCP4.5) Yearly precipitation anomalies (mm) for the period 2045-2065 based on the climate scenario RCP4.5 (reference 1986-2005). -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:pr_45_46_65 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 6 11 EPSG:4326:4 3 8 13 22 EPSG:4326:5 7 17 27 45 EPSG:4326:6 15 34 54 90 EPSG:4326:7 31 68 109 181 EPSG:4326:8 63 137 218 363 EPSG:4326:9 127 275 436 726 EPSG:4326:10 255 550 872 1453 EPSG:4326:11 510 1101 1745 2906 EPSG:4326:12 1021 2203 3490 5813 EPSG:4326:13 2043 4406 6980 11626 EPSG:4326:14 4086 8812 13960 23252 EPSG:4326:15 8173 17625 27921 46505 EPSG:4326:16 16347 35251 55843 93010 EPSG:4326:17 32695 70502 111687 186020 EPSG:4326:18 65390 141004 223375 372040 EPSG:4326:19 130780 282008 446751 744081 EPSG:4326:20 261561 564017 893503 1488162 EPSG:4326:21 523122 1128034 1787006 2976324 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 Albedo Winter 2019 - 2020 (Copernicus) Unit: ratio of the solar radiation reflected by a surface to the total incoming solar radiation, usually measured between 0 (all incident radiation absorbed) and 1 (all incident radiation refleted). Surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. The present layer represents the black-sky albedo (directional albedo), which is considered as an Essential Climate Variable by the Global Climate Observing System (GCOS). Surface albedo is a sensitive indicator of environmental vulnerability making it a key element required by climate, biogeochemical, hydrological, and weather forecast models. It has a spatial resolution of 1km and is available from the Copernicus Global Land Service (https://land.copernicus.eu/global/products/sa) as netCDF files (technical documentation available at https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_PUM_SA1km-V1_I1.40.pdf. The present raster is the broadband directional albedo over full spectrum [0.3-4µm]. It is the average of the various albedo files available in winter 2019-2020 (3 December 2019, 13 December 2019, 24 December 2020, 3 January 2020, 13 January 2020, 24 January 2020, 3 February 2020, 13 February 2020 et 22 February 2020), then transformed into a geotiff in order to display and example of albedo reflectance in winter. -180.0 -59.995535714253904 179.9955357142039 80.00446428571429 wesr_mountains:c_gls_ALDH_2019-20_hiver_raster_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 3 53 0 127 EPSG:4326:7 7 106 0 255 EPSG:4326:8 14 213 0 511 EPSG:4326:9 28 426 0 1023 EPSG:4326:10 56 853 0 2047 EPSG:4326:11 113 1706 0 4095 EPSG:4326:12 227 3413 0 8191 EPSG:4326:13 454 6826 0 16383 EPSG:4326:14 909 13652 0 32767 EPSG:4326:15 1819 27305 0 65535 EPSG:4326:16 3639 54611 0 131070 EPSG:4326:17 7278 109223 0 262140 EPSG:4326:18 14557 218446 0 524281 EPSG:4326:19 29114 436893 0 1048562 EPSG:4326:20 58228 873787 0 2097125 EPSG:4326:21 116456 1747574 0 4194251 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 46502 0 65535 EPSG:3857:17 14704 93005 0 131070 EPSG:3857:18 29409 186010 0 262140 EPSG:3857:19 58818 372021 0 524281 EPSG:3857:20 117637 744043 0 1048562 EPSG:3857:21 235275 1488087 0 2097125 EPSG:3857:22 470550 2976175 0 4194251 EPSG:3857:23 941100 5952351 0 8388503 EPSG:3857:24 1882201 11904702 0 16777007 EPSG:3857:25 3764403 23809404 0 33554015 EPSG:3857:26 7528807 47618809 0 67108031 EPSG:3857:27 15057614 95237619 0 134216063 EPSG:3857:28 30115228 190475238 0 268432127 EPSG:3857:29 60230457 380950477 0 536864254 EPSG:3857:30 120460914 761900955 0 1073728508 Self-calibrating Palmer Drought Severity Index (scPDSI) 2010-2018 (CRU) This layer shows the average values over the 2010 to 2018 decade of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901 to 2018. Original data were subset and processed using QGIS at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> The dataset has been updated each year using newer versions of CRU TS input data, currently to the end of 2018 using a preliminary version of CRU TS 4.03 (0.5° resolution). <br> Please read <a href="https://crudata.uea.ac.uk/cru/data/drought/scpdsi.global2018.readme.txt"target=_blank>this document</a> for more information. <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 UN_Sahel:scPDSI.cru_ts403_2010-2018 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Temperature anomalies (°C) 2045-2065 (RCP4.5) Temperature anomalies (°C) for the period 2045-2065 based on the climate scenario RCP4.5 (reference 1986-2005). -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:tas_45_46_65 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 6 11 EPSG:4326:4 3 8 13 22 EPSG:4326:5 7 17 27 45 EPSG:4326:6 15 34 54 90 EPSG:4326:7 31 68 109 181 EPSG:4326:8 63 137 218 363 EPSG:4326:9 127 275 436 726 EPSG:4326:10 255 550 872 1453 EPSG:4326:11 510 1101 1745 2906 EPSG:4326:12 1021 2203 3490 5813 EPSG:4326:13 2043 4406 6980 11626 EPSG:4326:14 4086 8812 13960 23252 EPSG:4326:15 8173 17625 27921 46505 EPSG:4326:16 16347 35251 55843 93010 EPSG:4326:17 32695 70502 111687 186020 EPSG:4326:18 65390 141004 223375 372040 EPSG:4326:19 130780 282008 446751 744081 EPSG:4326:20 261561 564017 893503 1488162 EPSG:4326:21 523122 1128034 1787006 2976324 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 Shaded Relief - manual -180.0 -90.0 180.0 90.0 grid_data_core:MSR_50M image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:900913 Combination Tropical cyclone surge/Forest at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 CGMFC-21, MFW, Global Mangrove Levels by Pixel (~30m), 2014 - Hamilton, Stuart, 2015 -179.950685815232 -38.762158638242894 179.98793546876746 32.350120473757 MapX_UNDP:CGMFC-21_mangroves_forest_cover_a2014 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 0 7 EPSG:3857:4 6 9 0 15 EPSG:3857:5 12 19 0 31 EPSG:3857:6 25 39 0 63 EPSG:3857:7 51 78 0 127 EPSG:3857:8 103 157 0 255 EPSG:3857:9 207 315 0 511 EPSG:3857:10 414 631 0 1023 EPSG:3857:11 829 1263 0 2047 EPSG:3857:12 1658 2527 0 4095 EPSG:3857:13 3317 5054 1 8191 EPSG:3857:14 6634 10108 2 16383 EPSG:3857:15 13269 20216 4 32766 EPSG:3857:16 26538 40433 8 65533 EPSG:3857:17 53076 80867 17 131067 EPSG:3857:18 106153 161735 35 262135 EPSG:3857:19 212307 323471 71 524270 EPSG:3857:20 424614 646942 143 1048540 EPSG:3857:21 849229 1293884 287 2097081 EPSG:3857:22 1698459 2587768 574 4194163 EPSG:3857:23 3396919 5175537 1149 8388326 EPSG:3857:24 6793838 10351074 2298 16776653 EPSG:3857:25 13587676 20702149 4596 33553307 EPSG:3857:26 27175353 41404298 9192 67106615 EPSG:3857:27 54350707 82808596 18385 134213230 EPSG:3857:28 108701415 165617193 36771 268426460 EPSG:3857:29 217402830 331234387 73542 536852920 EPSG:3857:30 434805661 662468775 147085 1073705840 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 1 2 0 7 EPSG:4326:3 2 5 0 15 EPSG:4326:4 5 11 0 31 EPSG:4326:5 10 22 0 63 EPSG:4326:6 20 45 0 127 EPSG:4326:7 40 91 0 255 EPSG:4326:8 81 183 0 511 EPSG:4326:9 163 366 0 1023 EPSG:4326:10 327 732 0 2047 EPSG:4326:11 655 1465 0 4095 EPSG:4326:12 1311 2930 1 8191 EPSG:4326:13 2623 5860 2 16383 EPSG:4326:14 5247 11720 4 32766 EPSG:4326:15 10494 23440 8 65533 EPSG:4326:16 20989 46880 17 131067 EPSG:4326:17 41979 93761 35 262135 EPSG:4326:18 83958 187523 71 524270 EPSG:4326:19 167917 375046 143 1048540 EPSG:4326:20 335834 750093 287 2097081 EPSG:4326:21 671669 1500187 574 4194163 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 1 2 0 3 EPSG:900913:3 3 4 0 7 EPSG:900913:4 6 9 0 15 EPSG:900913:5 12 19 0 31 EPSG:900913:6 25 39 0 63 EPSG:900913:7 51 78 0 127 EPSG:900913:8 103 157 0 255 EPSG:900913:9 207 315 0 511 EPSG:900913:10 414 631 0 1023 EPSG:900913:11 829 1263 0 2047 EPSG:900913:12 1658 2527 0 4095 EPSG:900913:13 3317 5054 1 8191 EPSG:900913:14 6634 10108 2 16383 EPSG:900913:15 13269 20216 4 32766 EPSG:900913:16 26538 40433 8 65533 EPSG:900913:17 53076 80867 17 131067 EPSG:900913:18 106153 161735 35 262135 EPSG:900913:19 212307 323471 71 524270 EPSG:900913:20 424614 646942 143 1048540 EPSG:900913:21 849229 1293884 287 2097081 EPSG:900913:22 1698459 2587768 574 4194163 EPSG:900913:23 3396919 5175537 1149 8388326 EPSG:900913:24 6793838 10351074 2298 16776653 EPSG:900913:25 13587676 20702149 4596 33553307 EPSG:900913:26 27175353 41404298 9192 67106615 EPSG:900913:27 54350707 82808596 18385 134213230 EPSG:900913:28 108701415 165617193 36771 268426460 EPSG:900913:29 217402830 331234387 73542 536852920 EPSG:900913:30 434805661 662468775 147085 1073705840 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 0 7 EPSG:3857:4 6 9 0 15 EPSG:3857:5 12 19 0 31 EPSG:3857:6 25 39 0 63 EPSG:3857:7 51 78 0 127 EPSG:3857:8 103 157 0 255 EPSG:3857:9 207 315 0 511 EPSG:3857:10 414 631 0 1023 EPSG:3857:11 829 1263 0 2047 EPSG:3857:12 1658 2527 0 4095 EPSG:3857:13 3317 5054 1 8191 EPSG:3857:14 6634 10108 2 16383 EPSG:3857:15 13269 20216 4 32766 EPSG:3857:16 26538 40433 8 65533 EPSG:3857:17 53076 80867 17 131067 EPSG:3857:18 106153 161735 35 262135 EPSG:3857:19 212307 323471 71 524270 EPSG:3857:20 424614 646942 143 1048540 EPSG:3857:21 849229 1293884 287 2097081 EPSG:3857:22 1698459 2587768 574 4194163 EPSG:3857:23 3396919 5175537 1149 8388326 EPSG:3857:24 6793838 10351074 2298 16776653 EPSG:3857:25 13587676 20702149 4596 33553307 EPSG:3857:26 27175353 41404298 9192 67106615 EPSG:3857:27 54350707 82808596 18385 134213230 EPSG:3857:28 108701415 165617193 36771 268426460 EPSG:3857:29 217402830 331234387 73542 536852920 EPSG:3857:30 434805661 662468775 147085 1073705840 Average year temperature anomalies (2011-2020) against 1901-1920 Average year temperature anomalies in °Celsius across the period 2011-2020 calculated over the average temperatures per year in the period 1901-1920 (as close as possible to the pre-industrial era). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_11_20_anom_1901_1920 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Flood/Forest at global level - others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_flo_for9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 20190618Classes Classification of a Sentinel-2 image with post-processing using field knowledge. This research was funded by the Copernicus RawMatCop programme, through funding from EIT RawMaterials and the European Commission DG Internal Market, Industry, Entrepreneurship and SMEs (DG GROW). https://eitrawmaterials.eu/eit-rm-academy/rawmatcop/, in the scope of project CopX: "Geospatial mining transparency through Copernicus and MapX" -74.8619381795564 7.565137269898085 -74.77524438684844 7.625960417972978 UNILIEGE:20190618Classes image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125502 125547 76559 76622 EPSG:3857:19 251004 251094 153118 153244 EPSG:3857:20 502009 502188 306236 306489 EPSG:3857:21 1004019 1004377 612473 612978 EPSG:3857:22 2008039 2008754 1224947 1225957 EPSG:3857:23 4016079 4017509 2449894 2451914 EPSG:3857:24 8032158 8035018 4899788 4903829 EPSG:3857:25 16064317 16070036 9799577 9807658 EPSG:3857:26 32128634 32140072 19599155 19615316 EPSG:3857:27 64257268 64280145 39198310 39230632 EPSG:3857:28 128514536 128560290 78396621 78461264 EPSG:3857:29 257029072 257120581 156793242 156922529 EPSG:3857:30 514058144 514241162 313586484 313845058 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 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502009 502188 306236 306489 EPSG:3857:21 1004019 1004377 612473 612978 EPSG:3857:22 2008039 2008754 1224947 1225957 EPSG:3857:23 4016079 4017509 2449894 2451914 EPSG:3857:24 8032158 8035018 4899788 4903829 EPSG:3857:25 16064317 16070036 9799577 9807658 EPSG:3857:26 32128634 32140072 19599155 19615316 EPSG:3857:27 64257268 64280145 39198310 39230632 EPSG:3857:28 128514536 128560290 78396621 78461264 EPSG:3857:29 257029072 257120581 156793242 156922529 EPSG:3857:30 514058144 514241162 313586484 313845058 site_0336_20010128_raw 21.804453393351142 2.163950346428799 22.972377367092143 3.360478793316272 hotspots:site_0336_20010128_raw image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 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3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 15 15 35 36 EPSG:4326:6 30 31 71 72 EPSG:4326:7 61 62 143 144 EPSG:4326:8 123 124 287 288 EPSG:4326:9 246 249 574 577 EPSG:4326:10 492 499 1148 1154 EPSG:4326:11 985 999 2296 2309 EPSG:4326:12 1971 1998 4592 4618 EPSG:4326:13 3943 3997 9184 9237 EPSG:4326:14 7886 7995 18368 18474 EPSG:4326:15 15772 15990 36737 36949 EPSG:4326:16 31544 31980 73474 73899 EPSG:4326:17 63088 63960 146949 147799 EPSG:4326:18 126177 127920 293899 295599 EPSG:4326:19 252355 255841 587798 591199 EPSG:4326:20 504711 511682 1175596 1182399 EPSG:4326:21 1009423 1023364 2351192 2364799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from Meteorological Institute of the University of Bonn, ECHO-G Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_miub_echo_g_5km_2041-2060_debiasedmean_tas_av12mon_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Extreme Heat recurrence map between 1995 and 2024 The study of extreme heat in the Kédougou region, based on a three-decadal analysis (1995–2004, 2005–2014, 2015–2024), highlights an alarming change in surface temperatures, corroborated by the observations of Sy et al. (2021) in northern Senegal. The combined mapping of the three periods, synthesizing the occurrences of exceedances of the critical threshold of 42°C (corresponding to the 90th percentile of local maxima), makes it possible to visualize the areas most exposed over the long term. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:heat image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491251 EPSG:4326:20 445870 452589 971450 982502 EPSG:4326:21 891741 905179 1942901 1965005 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 Global Grid of Probabilities of Urban Expansion to 2030 The Global Grid of Probabilities of Urban Expansion to 2030 presents spatially explicit probabilistic forecasts of global urban land cover change from 2000 to 2030 at a 2.5 arc-minute resolution. For each grid cell that is non-urban in 2000, a Monte-Carlo model assigned a probability of becoming urban by the year 2030. The authors first extracted urban extent circa 2000 from the NASA MODIS Land Cover Type Product Version 5, which provides a conservative estimate of global urban land cover. The authors then used population densities from the Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) to create the population density driver map. They estimated the amount of new urban land in each United Nations region by 2030 in a Monte-Carlo fashion based on present empirical distribution of regional urban population densities and probability density functions of projected regional population and GDP values for 2030. To facilitate integration with other data products, CIESIN reprojected the data from Goode's Homolosine to Geographic WGS84 projection. We recommend using the Goode Homolosine equal area projection for data analysis. NOTES CONCERNING THE DATA Although regions were not excluded in the creation of these data some small urban areas, such as Tromso and Norilsk, are missing. This is a result of resampling the input land-cover data from 463 meters to 5 kilometers as described in the documentation. ACCESSING THE DATA The data may be downloaded via the World Wide Web at http://sedac.ciesin.columbia.edu/data/set/lulc-global-grid-prob-urban-expansion-2030. The data are available in a compressed zipfile of GeoTIFF format. The downloaded files need to be uncompressed in a single folder using either WinZip (Windows file compression utility) or a similar application before it can be accessed by your GIS software package. DATA FORMAT Two files containing probability of urban expansion grids in GeoTIFF format are available in the download. The WGS84 archive is in geographic coordinates of decimal degrees based on the World Geodetic System spheroid of 1984. The Goode Homolosine archive is in projected coordinates based on the pseudocylindrical, equal-area, composite map, Goode Homolosine projection. File naming convention: urban-expansion-2000-to-2030-wgs84 WGS 1984, with 0.048125633 decimal degree resolution urban-expansion-2000-to-2030-goode Goode Homolosine, with 5 kilometer resolution -179.99997803468415 -55.922762245435266 180.0 83.97845284575614 MapX_UNDP:global_grid_prob_expansion_2030_unused image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 4 88 0 127 EPSG:3857:8 8 176 0 255 EPSG:3857:9 16 352 0 511 EPSG:3857:10 32 704 0 1023 EPSG:3857:11 64 1409 0 2047 EPSG:3857:12 128 2818 0 4095 EPSG:3857:13 256 5637 0 8191 EPSG:3857:14 512 11275 0 16383 EPSG:3857:15 1024 22551 0 32767 EPSG:3857:16 2049 45103 0 65535 EPSG:3857:17 4098 90206 0 131071 EPSG:3857:18 8197 180413 0 262143 EPSG:3857:19 16395 360827 0 524287 EPSG:3857:20 32790 721654 0 1048575 EPSG:3857:21 65580 1443309 0 2097151 EPSG:3857:22 131161 2886618 0 4194304 EPSG:3857:23 262323 5773236 0 8388608 EPSG:3857:24 524646 11546472 1 16777215 EPSG:3857:25 1049292 23092944 2 33554431 EPSG:3857:26 2098585 46185889 4 67108863 EPSG:3857:27 4197171 92371778 8 134217727 EPSG:3857:28 8394342 184743557 16 268435456 EPSG:3857:29 16788684 369487114 32 536870911 EPSG:3857:30 33577368 738974228 65 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 4 103 0 255 EPSG:4326:8 8 207 0 511 EPSG:4326:9 17 415 0 1023 EPSG:4326:10 34 830 0 2047 EPSG:4326:11 68 1660 0 4095 EPSG:4326:12 137 3320 0 8191 EPSG:4326:13 274 6641 0 16383 EPSG:4326:14 548 13282 0 32767 EPSG:4326:15 1096 26564 0 65535 EPSG:4326:16 2192 53128 0 131071 EPSG:4326:17 4384 106257 0 262143 EPSG:4326:18 8769 212515 0 524287 EPSG:4326:19 17539 425030 0 1048575 EPSG:4326:20 35078 850061 0 2097151 EPSG:4326:21 70156 1700123 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 1 22 0 31 EPSG:900913:6 2 44 0 63 EPSG:900913:7 4 88 0 127 EPSG:900913:8 8 176 0 255 EPSG:900913:9 16 352 0 511 EPSG:900913:10 32 704 0 1023 EPSG:900913:11 64 1409 0 2047 EPSG:900913:12 128 2818 0 4095 EPSG:900913:13 256 5637 0 8191 EPSG:900913:14 512 11275 0 16383 EPSG:900913:15 1024 22551 0 32767 EPSG:900913:16 2049 45103 0 65535 EPSG:900913:17 4098 90206 0 131071 EPSG:900913:18 8197 180413 0 262143 EPSG:900913:19 16395 360827 0 524287 EPSG:900913:20 32790 721654 0 1048575 EPSG:900913:21 65580 1443309 0 2097151 EPSG:900913:22 131161 2886618 0 4194303 EPSG:900913:23 262323 5773236 0 8388607 EPSG:900913:24 524646 11546472 1 16777215 EPSG:900913:25 1049292 23092944 2 33554431 EPSG:900913:26 2098585 46185889 4 67108863 EPSG:900913:27 4197171 92371778 8 134217727 EPSG:900913:28 8394342 184743557 16 268435455 EPSG:900913:29 16788684 369487114 32 536870911 EPSG:900913:30 33577368 738974228 65 1073741823 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 4 88 0 127 EPSG:3857:8 8 176 0 255 EPSG:3857:9 16 352 0 511 EPSG:3857:10 32 704 0 1023 EPSG:3857:11 64 1409 0 2047 EPSG:3857:12 128 2818 0 4095 EPSG:3857:13 256 5637 0 8191 EPSG:3857:14 512 11275 0 16383 EPSG:3857:15 1024 22551 0 32767 EPSG:3857:16 2049 45103 0 65535 EPSG:3857:17 4098 90206 0 131071 EPSG:3857:18 8197 180413 0 262143 EPSG:3857:19 16395 360827 0 524287 EPSG:3857:20 32790 721654 0 1048575 EPSG:3857:21 65580 1443309 0 2097152 EPSG:3857:22 131161 2886618 0 4194304 EPSG:3857:23 262323 5773236 0 8388607 EPSG:3857:24 524646 11546472 1 16777215 EPSG:3857:25 1049292 23092944 2 33554431 EPSG:3857:26 2098585 46185889 4 67108863 EPSG:3857:27 4197171 92371778 8 134217728 EPSG:3857:28 8394342 184743557 16 268435455 EPSG:3857:29 16788684 369487114 32 536870911 EPSG:3857:30 33577368 738974228 65 1073741824 Spring precipitations change (%) for the period 2020 - 2039 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_mam_NEARREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Yearly emissions of CO2 (excluding short cycle organic Carbon) - 1980 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -88.79999999998984 179.99999999997954 90.0 wesr_climat:v60_CO2_excl_short-cycle_org_C_1980_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 63 0 127 EPSG:4326:7 0 127 0 255 EPSG:4326:8 0 254 0 511 EPSG:4326:9 0 508 0 1023 EPSG:4326:10 0 1017 0 2047 EPSG:4326:11 0 2034 0 4095 EPSG:4326:12 0 4068 0 8191 EPSG:4326:13 0 8137 0 16383 EPSG:4326:14 0 16274 0 32767 EPSG:4326:15 0 32549 0 65535 EPSG:4326:16 0 65099 0 131071 EPSG:4326:17 0 130198 0 262143 EPSG:4326:18 0 260396 0 524287 EPSG:4326:19 0 520792 0 1048575 EPSG:4326:20 0 1041585 0 2097151 EPSG:4326:21 0 2083170 0 4194303 EPSG:900913 EPSG:3857_512 Title example 2 Abstract example 2 -180.0 -90.0 180.0 90.0 testing:name_rewritten_2 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Title example_3 Abstract example -179.99999999966695 -56.05000002425277 179.25000000033162 77.49166664241338 testing:name_rewritten_3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 11 0 15 EPSG:3857:5 4 22 0 31 EPSG:3857:6 9 44 0 63 EPSG:3857:7 18 88 0 127 EPSG:3857:8 37 176 0 255 EPSG:3857:9 75 352 0 510 EPSG:3857:10 151 705 0 1021 EPSG:3857:11 303 1410 0 2043 EPSG:3857:12 606 2821 0 4087 EPSG:3857:13 1213 5643 0 8174 EPSG:3857:14 2426 11286 0 16349 EPSG:3857:15 4853 22572 0 32699 EPSG:3857:16 9706 45144 0 65399 EPSG:3857:17 19412 90289 0 130798 EPSG:3857:18 38825 180579 0 261597 EPSG:3857:19 77651 361158 0 523195 EPSG:3857:20 155303 722317 0 1046391 EPSG:3857:21 310607 1444634 0 2092782 EPSG:3857:22 621214 2889268 0 4185565 EPSG:3857:23 1242428 5778536 0 8371131 EPSG:3857:24 2484856 11557072 0 16742263 EPSG:3857:25 4969713 23114145 0 33484526 EPSG:3857:26 9939427 46228290 0 66969053 EPSG:3857:27 19878854 92456581 0 133938107 EPSG:3857:28 39757708 184913162 0 267876215 EPSG:3857:29 79515417 369826324 0 535752430 EPSG:3857:30 159030835 739652649 0 1071504861 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 0 31 EPSG:4326:5 2 25 0 63 EPSG:4326:6 4 51 0 127 EPSG:4326:7 8 103 0 255 EPSG:4326:8 17 207 0 510 EPSG:4326:9 35 415 0 1021 EPSG:4326:10 71 830 0 2043 EPSG:4326:11 142 1661 0 4087 EPSG:4326:12 284 3323 0 8174 EPSG:4326:13 569 6646 0 16349 EPSG:4326:14 1138 13293 0 32699 EPSG:4326:15 2277 26587 0 65399 EPSG:4326:16 4554 53175 0 130798 EPSG:4326:17 9108 106350 0 261597 EPSG:4326:18 18216 212700 0 523195 EPSG:4326:19 36433 425401 0 1046391 EPSG:4326:20 72866 850802 0 2092782 EPSG:4326:21 145732 1701605 0 4185565 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 11 0 15 EPSG:3857:5 4 22 0 31 EPSG:3857:6 9 44 0 63 EPSG:3857:7 18 88 0 127 EPSG:3857:8 37 176 0 255 EPSG:3857:9 75 352 0 510 EPSG:3857:10 151 705 0 1021 EPSG:3857:11 303 1410 0 2043 EPSG:3857:12 606 2821 0 4087 EPSG:3857:13 1213 5643 0 8174 EPSG:3857:14 2426 11286 0 16349 EPSG:3857:15 4853 22572 0 32699 EPSG:3857:16 9706 45144 0 65399 EPSG:3857:17 19412 90289 0 130798 EPSG:3857:18 38825 180579 0 261597 EPSG:3857:19 77651 361158 0 523195 EPSG:3857:20 155303 722317 0 1046391 EPSG:3857:21 310607 1444634 0 2092782 EPSG:3857:22 621214 2889268 0 4185565 EPSG:3857:23 1242428 5778536 0 8371131 EPSG:3857:24 2484856 11557072 0 16742263 EPSG:3857:25 4969713 23114145 0 33484526 EPSG:3857:26 9939427 46228290 0 66969053 EPSG:3857:27 19878854 92456581 0 133938107 EPSG:3857:28 39757708 184913162 0 267876215 EPSG:3857:29 79515417 369826324 0 535752430 EPSG:3857:30 159030835 739652649 0 1071504861 Average year precipitations (1991-2000) Average year precipitations in mm across the period 1991-2000. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/pre/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_pre_91_00_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mean temperatures 2013 - Central African Republic Mean observed temperatures in 2013 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2013_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 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EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Corine LandCover - Warsaw -81.23107933735224 -29.1293425632973 93.48635817033636 72.12305826803104 unep_storymap:Corine_LCov_Warsaw image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json 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1261501 1268705 1920648 1927821 EPSG:3857:22 2523003 2537411 3841297 3855642 EPSG:3857:23 5046006 5074823 7682595 7711285 EPSG:3857:24 10092012 10149647 15365191 15422570 EPSG:3857:25 20184025 20299295 30730383 30845141 EPSG:3857:26 40368050 40598590 61460767 61690283 EPSG:3857:27 80736101 81197180 122921534 123380566 EPSG:3857:28 161472202 162394360 245843069 246761133 EPSG:3857:29 322944404 324788720 491686139 493522267 EPSG:3857:30 645888809 649577440 983372279 987044534 Novel Climate Risk This is the novel climate risk dataset - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates. <br> This dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007).The metrics represent dissimilarity measurements of the squared Euclidean distance between seasonal (June–August and December–February) temperature and precipitation variables in the 20th century climate and mid-21st century climate. (1) disappearing climate risk - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climates (2) novel climate risk - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates. <br> John W. Williams, Karyn Tabor. (2018). Novel and Disappearing Climates 2050 SRES A2 (Version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1559299 John W. Williams, Karyn Tabor. (2018). Novel and Disappearing Climates 2050 SRES A2 (Version 1) [Data set]. 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517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 Drought-affected areas in Kedougou between 2015 and 2024 The TCI, VCI and VHI indices are used to identify areas affected by drought. They are characterized as vegetation indices because they describe the state of vegetation in a specific area. The VCI is widely used to detect changes in vegetation from poor to favorable conditions. TCI detects vegetative stress induced by high temperatures and high humidity. VHI, on the other hand, is the combination of TCI (temperature) and VCI (vegetation condition) that describes vegetation health. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:vhi_2015_2024 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491251 EPSG:4326:20 445870 452589 971450 982502 EPSG:4326:21 891741 905179 1942901 1965005 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 Illegal Dumping Susceptibility in Keur Massar Senegal in 2025 (unweighted) This map shows the non-weighted illegal dumping susceptibility across the three communes of Keur Massar (Malika, Keur Massar, and Yeumbeul Nord) in Dakar, Senegal. The map was produced in 2025 as part of a research project using multi-criteria analysis at UNEP/GRID Geneva. The map represents the mean of several positively correlated criteria with illegal dumping: proximity to water edges, vegetation areas, bare soil areas, population density (2025), land surface temperature, market areas, and areas around PRNs, as well as a social perception criterion derived from a survey of students living in the three communes. Waste collection routes, which are negatively correlated with illegal dumping, are also included. All criteria were rasterized when necessary and normalized before averaging to produce the final map. The Focal Statistics tool was applied with a radius of 7 pixels to smooth the results and reduce local noise. The susceptibility levels are visualized using a color scale: dark green (very low, ≤ 0.19), light green (low, ≤ 0.24), beige (medium, ≤ 0.27), orange (high, ≤ 0.31), and red (very high, ≤ 0.42). This output provides an integrated overview of spatial susceptibility patterns for illegal dumping, supporting targeted interventions and planning. -17.36716999545483 14.763385550148119 -17.286595649628648 14.822825777160343 dakar_waste:carte_non_ponderee image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7509 7512 7401 7405 EPSG:3857:15 15019 15025 14803 14810 EPSG:3857:16 30038 30050 29606 29621 EPSG:3857:17 60077 60100 59212 59242 EPSG:3857:18 120155 120200 118425 118484 EPSG:3857:19 240311 240401 236851 236968 EPSG:3857:20 480623 480802 473702 473937 EPSG:3857:21 961247 961605 947404 947874 EPSG:3857:22 1922494 1923210 1894809 1895748 EPSG:3857:23 3844988 3846421 3789619 3791497 EPSG:3857:24 7689977 7692842 7579239 7582994 EPSG:3857:25 15379954 15385684 15158478 15165988 EPSG:3857:26 30759908 30771368 30316956 30331977 EPSG:3857:27 61519816 61542736 60633913 60663954 EPSG:3857:28 123039632 123085473 121267827 121327908 EPSG:3857:29 246079264 246170947 242535654 242655816 EPSG:3857:30 492158529 492341894 485071309 485311632 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 462 EPSG:4326:10 427 428 925 925 EPSG:4326:11 855 856 1850 1851 EPSG:4326:12 1710 1712 3700 3702 EPSG:4326:13 3421 3424 7401 7405 EPSG:4326:14 6842 6848 14803 14810 EPSG:4326:15 13685 13696 29606 29621 EPSG:4326:16 27371 27392 59212 59242 EPSG:4326:17 54742 54785 118425 118484 EPSG:4326:18 109484 109571 236851 236968 EPSG:4326:19 218969 219142 473702 473937 EPSG:4326:20 437938 438285 947404 947874 EPSG:4326:21 875877 876570 1894809 1895748 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7509 7512 7401 7405 EPSG:3857:15 15019 15025 14803 14810 EPSG:3857:16 30038 30050 29606 29621 EPSG:3857:17 60077 60100 59212 59242 EPSG:3857:18 120155 120200 118425 118484 EPSG:3857:19 240311 240401 236851 236968 EPSG:3857:20 480623 480802 473702 473937 EPSG:3857:21 961247 961605 947404 947874 EPSG:3857:22 1922494 1923210 1894809 1895748 EPSG:3857:23 3844988 3846421 3789619 3791497 EPSG:3857:24 7689977 7692842 7579239 7582994 EPSG:3857:25 15379954 15385684 15158478 15165988 EPSG:3857:26 30759908 30771368 30316956 30331977 EPSG:3857:27 61519816 61542736 60633913 60663954 EPSG:3857:28 123039632 123085473 121267827 121327908 EPSG:3857:29 246079264 246170947 242535654 242655816 EPSG:3857:30 492158529 492341894 485071309 485311632 Combination Tropical cyclone surge/Forest at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_for9_1112_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 MovMasa_COSTA_SIERRA Layer provided by Ministry of Environment of Peru. Areas prone to landslides. Methods and info related to the susceptibility analysis. https://geoservidor.minam.gob.pe/wp-content/uploads/2017/06/Texto-MAPA-DE-SUSCEPTIBILIDAD.pdf -81.64209767609421 -18.407041570165664 -68.74570664904627 -3.3742169907173394 wesr_cca:MovMasa_COSTA_SIERRA image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 0 0 EPSG:3857:2 2 2 1 1 EPSG:3857:3 4 4 2 2 EPSG:3857:4 8 8 4 4 EPSG:3857:5 16 17 8 9 EPSG:3857:6 32 35 17 19 EPSG:3857:7 65 70 34 39 EPSG:3857:8 130 141 69 79 EPSG:3857:9 260 282 139 158 EPSG:3857:10 521 565 279 316 EPSG:3857:11 1043 1130 559 632 EPSG:3857:12 2086 2261 1119 1265 EPSG:3857:13 4172 4522 2238 2531 EPSG:3857:14 8345 9044 4476 5063 EPSG:3857:15 16691 18089 8952 10126 EPSG:3857:16 33382 36178 17905 20253 EPSG:3857:17 66765 72356 35811 40506 EPSG:3857:18 133530 144712 71622 81012 EPSG:3857:19 267060 289424 143244 162025 EPSG:3857:20 534121 578849 286488 324051 EPSG:3857:21 1068243 1157698 572976 648103 EPSG:3857:22 2136487 2315396 1145952 1296206 EPSG:3857:23 4272974 4630793 2291905 2592412 EPSG:3857:24 8545948 9261587 4583810 5184825 EPSG:3857:25 17091897 18523174 9167620 10369651 EPSG:3857:26 34183795 37046348 18335241 20739303 EPSG:3857:27 68367591 74092696 36670483 41478606 EPSG:3857:28 136735182 148185392 73340967 82957213 EPSG:3857:29 273470364 296370784 146681935 165914427 EPSG:3857:30 546940728 592741568 293363870 331828855 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 1 1 1 1 EPSG:4326:2 2 2 2 2 EPSG:4326:3 4 4 4 4 EPSG:4326:4 8 9 8 9 EPSG:4326:5 16 19 17 19 EPSG:4326:6 33 38 34 39 EPSG:4326:7 66 77 69 79 EPSG:4326:8 132 154 139 158 EPSG:4326:9 265 308 279 316 EPSG:4326:10 531 616 559 632 EPSG:4326:11 1062 1233 1119 1265 EPSG:4326:12 2124 2466 2238 2531 EPSG:4326:13 4249 4933 4476 5063 EPSG:4326:14 8499 9867 8952 10126 EPSG:4326:15 16998 19734 17905 20253 EPSG:4326:16 33996 39469 35811 40506 EPSG:4326:17 67993 78939 71622 81012 EPSG:4326:18 135986 157879 143244 162025 EPSG:4326:19 271972 315758 286488 324051 EPSG:4326:20 543944 631516 572976 648103 EPSG:4326:21 1087888 1263033 1145952 1296206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 0 0 EPSG:3857:2 2 2 1 1 EPSG:3857:3 4 4 2 2 EPSG:3857:4 8 8 4 4 EPSG:3857:5 16 17 8 9 EPSG:3857:6 32 35 17 19 EPSG:3857:7 65 70 34 39 EPSG:3857:8 130 141 69 79 EPSG:3857:9 260 282 139 158 EPSG:3857:10 521 565 279 316 EPSG:3857:11 1043 1130 559 632 EPSG:3857:12 2086 2261 1119 1265 EPSG:3857:13 4172 4522 2238 2531 EPSG:3857:14 8345 9044 4476 5063 EPSG:3857:15 16691 18089 8952 10126 EPSG:3857:16 33382 36178 17905 20253 EPSG:3857:17 66765 72356 35811 40506 EPSG:3857:18 133530 144712 71622 81012 EPSG:3857:19 267060 289424 143244 162025 EPSG:3857:20 534121 578849 286488 324051 EPSG:3857:21 1068243 1157698 572976 648103 EPSG:3857:22 2136487 2315396 1145952 1296206 EPSG:3857:23 4272974 4630793 2291905 2592412 EPSG:3857:24 8545948 9261587 4583810 5184825 EPSG:3857:25 17091897 18523174 9167620 10369651 EPSG:3857:26 34183795 37046348 18335241 20739303 EPSG:3857:27 68367591 74092696 36670483 41478606 EPSG:3857:28 136735182 148185392 73340967 82957213 EPSG:3857:29 273470364 296370784 146681935 165914427 EPSG:3857:30 546940728 592741568 293363870 331828855 Population density map 2018 based on GSHL and the World Population Prospect 2019 Population density map for 2018 at 30arcsec resolution. <br><br> The layer uses the Global Human Settlement Layer (GHSL) - JRC and the national population count for 2018 reported on the World Population Prospects 2019. <br><br> The original GHSL layer was recalculated at 30arcsec resolution (~1km) through an aggregation process (sum) in Google Earth Engine. Pixel counts were then recalculated for 2018 based on the country population data reported for 2018 by the World Population Prospects 2019. <br><br> Source of data: <br> GHSL: GHS_POP_E2015_GLOBE_R2019A_4326_30SS_V1_0 (downloaded from <a href="https://ghsl.jrc.ec.europa.eu/download.php?ds=pop at 30arcsec resolution"target=_blank>JRC</a>)<br> Dataset:<br> Schiavina, Marcello; Freire, Sergio; MacManus, Kytt (2019): GHS population grid multitemporal (1975, 1990, 2000, 2015) R2019A. European Commission, Joint Research Centre (JRC) DOI: <a href="http://data.europa.eu/89h/0c6b9751-a71f-4062-830b-43c9f432370f"target=_blank>10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218</a> <br> Concept & Methodology: Freire, Sergio; MacManus, Kytt; Pesaresi, Martino; Doxsey-Whitfield, Erin; Mills, Jane (2016): Development of new open and free multi-temporal global population grids at 250 m resolution. Geospatial Data in a Changing World; Association of Geographic Information Laboratories in Europe (AGILE). AGILE 2016. <br><br><a href="https://population.un.org/wpp/"target=_blank>World Population Prospects 2019 (UN)</a> <br><br> -179.999999999928 -59.99999999424 179.999999999928 84.00833333903574 grid_data_core_pro:GHSL_pop_count_2018_wnodata_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 45 0 63 EPSG:3857:7 3 90 0 127 EPSG:3857:8 7 181 0 255 EPSG:3857:9 15 363 0 511 EPSG:3857:10 31 726 0 1023 EPSG:3857:11 62 1453 0 2047 EPSG:3857:12 124 2906 0 4095 EPSG:3857:13 249 5813 0 8191 EPSG:3857:14 499 11626 0 16383 EPSG:3857:15 998 23252 0 32767 EPSG:3857:16 1997 46504 0 65535 EPSG:3857:17 3994 93008 0 131071 EPSG:3857:18 7989 186017 0 262143 EPSG:3857:19 15979 372034 0 524287 EPSG:3857:20 31958 744069 0 1048575 EPSG:3857:21 63917 1488139 0 2097151 EPSG:3857:22 127834 2976279 0 4194304 EPSG:3857:23 255669 5952559 0 8388608 EPSG:3857:24 511338 11905118 0 16777215 EPSG:3857:25 1022677 23810236 0 33554431 EPSG:3857:26 2045355 47620473 0 67108863 EPSG:3857:27 4090711 95240947 0 134217727 EPSG:3857:28 8181422 190481895 0 268435456 EPSG:3857:29 16362845 380963791 0 536870911 EPSG:3857:30 32725690 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 8 213 0 511 EPSG:4326:9 17 426 0 1023 EPSG:4326:10 34 853 0 2047 EPSG:4326:11 68 1706 0 4095 EPSG:4326:12 136 3413 0 8191 EPSG:4326:13 272 6826 0 16383 EPSG:4326:14 545 13653 0 32767 EPSG:4326:15 1090 27306 0 65535 EPSG:4326:16 2181 54613 0 131071 EPSG:4326:17 4362 109226 0 262143 EPSG:4326:18 8725 218453 0 524287 EPSG:4326:19 17451 436906 0 1048575 EPSG:4326:20 34903 873813 0 2097151 EPSG:4326:21 69807 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 45 0 63 EPSG:3857:7 3 90 0 127 EPSG:3857:8 7 181 0 255 EPSG:3857:9 15 363 0 511 EPSG:3857:10 31 726 0 1023 EPSG:3857:11 62 1453 0 2047 EPSG:3857:12 124 2906 0 4095 EPSG:3857:13 249 5813 0 8191 EPSG:3857:14 499 11626 0 16383 EPSG:3857:15 998 23252 0 32767 EPSG:3857:16 1997 46504 0 65535 EPSG:3857:17 3994 93008 0 131071 EPSG:3857:18 7989 186017 0 262143 EPSG:3857:19 15979 372034 0 524287 EPSG:3857:20 31958 744069 0 1048575 EPSG:3857:21 63917 1488139 0 2097152 EPSG:3857:22 127834 2976279 0 4194304 EPSG:3857:23 255669 5952559 0 8388607 EPSG:3857:24 511338 11905118 0 16777215 EPSG:3857:25 1022677 23810236 0 33554431 EPSG:3857:26 2045355 47620473 0 67108863 EPSG:3857:27 4090711 95240947 0 134217728 EPSG:3857:28 8181422 190481895 0 268435455 EPSG:3857:29 16362845 380963791 0 536870911 EPSG:3857:30 32725690 761927583 0 1073741824 Spatial distribution of flood risk Analysis of flood risk results reveals a complex and variable spatial distribution of the most exposed areas in the Kédougou region. By combining data from satellite imagery, notably the (MNDWI) and topographic information extracted from the SRTM model, the study highlights the sectors where hydrological hazard is combined with increased vulnerability due to urbanization and land use. -13.239494659264894 12.307771971227796 -11.34243244226129 13.461029132980437 risk_southeast_senegal:flood_risk image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15255 15178 15351 EPSG:3857:16 30294 30510 30357 30703 EPSG:3857:17 60589 61020 60715 61406 EPSG:3857:18 121178 122040 121431 122812 EPSG:3857:19 242357 244080 242862 245625 EPSG:3857:20 484714 488160 485725 491250 EPSG:3857:21 969428 976320 971450 982501 EPSG:3857:22 1938856 1952640 1942900 1965003 EPSG:3857:23 3877713 3905280 3885801 3930006 EPSG:3857:24 7755426 7810561 7771602 7860012 EPSG:3857:25 15510853 15621122 15543205 15720024 EPSG:3857:26 31021706 31242245 31086411 31440049 EPSG:3857:27 62043412 62484491 62172822 62880098 EPSG:3857:28 124086825 124968983 124345645 125760197 EPSG:3857:29 248173650 249937966 248691290 251520394 EPSG:3857:30 496347300 499875932 497382581 503040789 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226295 485725 491250 EPSG:4326:20 445871 452590 971450 982501 EPSG:4326:21 891743 905180 1942900 1965003 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15255 15178 15351 EPSG:3857:16 30294 30510 30357 30703 EPSG:3857:17 60589 61020 60715 61406 EPSG:3857:18 121178 122040 121431 122812 EPSG:3857:19 242357 244080 242862 245625 EPSG:3857:20 484714 488160 485725 491250 EPSG:3857:21 969428 976320 971450 982501 EPSG:3857:22 1938856 1952640 1942900 1965003 EPSG:3857:23 3877713 3905280 3885801 3930006 EPSG:3857:24 7755426 7810561 7771602 7860012 EPSG:3857:25 15510853 15621122 15543205 15720024 EPSG:3857:26 31021706 31242245 31086411 31440049 EPSG:3857:27 62043412 62484491 62172822 62880098 EPSG:3857:28 124086825 124968983 124345645 125760197 EPSG:3857:29 248173650 249937966 248691290 251520394 EPSG:3857:30 496347300 499875932 497382581 503040789 Drought-affected areas in Kedougou between 1995 and 2004 The TCI, VCI and VHI indices are used to identify areas affected by drought. They are characterized as vegetation indices because they describe the state of vegetation in a specific area. The VCI is widely used to detect changes in vegetation from poor to favorable conditions. TCI detects vegetative stress induced by high temperatures and high humidity. VHI, on the other hand, is the combination of TCI (temperature) and VCI (vegetation condition) that describes vegetation health. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:vhi_1995_2004 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 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124761 139808 EPSG:3857:19 203897 233858 249522 279616 EPSG:3857:20 407795 467716 499044 559232 EPSG:3857:21 815590 935432 998089 1118465 EPSG:3857:22 1631180 1870865 1996178 2236931 EPSG:3857:23 3262361 3741730 3992356 4473862 EPSG:3857:24 6524723 7483460 7984713 8947725 EPSG:3857:25 13049447 14966920 15969427 17895451 EPSG:3857:26 26098895 29933840 31938855 35790903 EPSG:3857:27 52197790 59867681 63877710 71581807 EPSG:3857:28 104395580 119735363 127755420 143163615 EPSG:3857:29 208791161 239470726 255510841 286327231 EPSG:3857:30 417582323 478941452 511021683 572654463 Satellite Mogadisho Urban Growth 2018 Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2018-01-02. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov. 45.195394649846214 1.955229029551538 45.47923060483454 2.141476613353127 MAPX:Mogadisho_Landsat7_20180102-531 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 10 10 EPSG:3857:5 15 15 20 20 EPSG:3857:6 31 31 40 40 EPSG:3857:7 63 63 80 80 EPSG:3857:8 126 126 160 160 EPSG:3857:9 252 253 320 320 EPSG:3857:10 505 506 640 641 EPSG:3857:11 1011 1012 1281 1282 EPSG:3857:12 2023 2025 2562 2565 EPSG:3857:13 4047 4051 5124 5130 EPSG:3857:14 8094 8102 10248 10261 EPSG:3857:15 16189 16205 20497 20523 EPSG:3857:16 32378 32411 40995 41047 EPSG:3857:17 64756 64823 81991 82094 EPSG:3857:18 129512 129647 163982 164188 EPSG:3857:19 259024 259295 327964 328377 EPSG:3857:20 518049 518591 655929 656755 EPSG:3857:21 1036098 1037183 1311858 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1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 Satellite Mogadisho Urban Growth 2003 Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2003-12-27. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov. 45.195394649846214 1.955229029551538 45.47923060483454 2.141476613353127 MAPX:Mogadisho_Landsat7_20031227-531 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 10 10 EPSG:3857:5 15 15 20 20 EPSG:3857:6 31 31 40 40 EPSG:3857:7 63 63 80 80 EPSG:3857:8 126 126 160 160 EPSG:3857:9 252 253 320 320 EPSG:3857:10 505 506 640 641 EPSG:3857:11 1011 1012 1281 1282 EPSG:3857:12 2023 2025 2562 2565 EPSG:3857:13 4047 4051 5124 5130 EPSG:3857:14 8094 8102 10248 10261 EPSG:3857:15 16189 16205 20497 20523 EPSG:3857:16 32378 32411 40995 41047 EPSG:3857:17 64756 64823 81991 82094 EPSG:3857:18 129512 129647 163982 164188 EPSG:3857:19 259024 259295 327964 328377 EPSG:3857:20 518049 518591 655929 656755 EPSG:3857:21 1036098 1037183 1311858 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327964 328377 EPSG:4326:19 255906 256448 655929 656755 EPSG:4326:20 511812 512897 1311858 1313511 EPSG:4326:21 1023625 1025795 2623716 2627023 EPSG:900913 Flood hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:fl_phex image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 africaSCI3 4.291563438357412 -7.915216499533859 35.4060669442033 6.84482706260207 MapX_UNDP:africaSCI3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 16 16 19 EPSG:3857:6 30 33 32 38 EPSG:3857:7 61 66 65 76 EPSG:3857:8 123 133 131 153 EPSG:3857:9 246 267 262 306 EPSG:3857:10 492 534 524 612 EPSG:3857:11 984 1069 1048 1225 EPSG:3857:12 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EPSG:3857:17 63037 68427 67098 78426 EPSG:3857:18 126075 136854 134197 156853 EPSG:3857:19 252151 273708 268394 313707 EPSG:3857:20 504303 547416 536788 627415 EPSG:3857:21 1008606 1094832 1073576 1254831 EPSG:3857:22 2017213 2189665 2147152 2509662 EPSG:3857:23 4034427 4379331 4294304 5019325 EPSG:3857:24 8068854 8758662 8588609 10038650 EPSG:3857:25 16137708 17517325 17177218 20077300 EPSG:3857:26 32275417 35034651 34354437 40154601 EPSG:3857:27 64550835 70069302 68708874 80309202 EPSG:3857:28 129101671 140138604 137417749 160618405 EPSG:3857:29 258203342 280277208 274835499 321236810 EPSG:3857:30 516406685 560554416 549670998 642473620 Human impact on forests <span style="font-size:0.95em"><span style="font-size:1.1em"><b>Description</b></span> A global map containing information on forest management, using the following categories: 1) forest without any signs of human impact, 2) forest with signs of human impact, including clear cuts, logging, and built-up roads; 3) replanted forest and forest - rotation period longer than 20 years; 4) woody plantations - rotation period of maximum 15 years; 5) oil palm plantations; and 6) agroforestry, including fruit tree plantations, tree shelter-belts, and individual trees on pastures. This information has been produced based on more than 100,000 observations collected through a citizen science campaign using the <a href="https://www.geo-wiki.org" target="_blank">Geo-Wiki Platform</a>. Machine learning techniques were applied in combination with Proba-V 100m images to generate the final map.<br><br>NatureMap is currently soliciting feedback on the validity of this map at the national and sub-national levels. Please submit any comments via the <a href="https://explorer.naturemap.earth/" target="_blank">Nature Map Explorer</a>.</span> -179.9999885408441 -60.00069958862515 179.99982972004844 80.00049603174595 MapX_UNDP:forest_management_layer_v3_2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1839 11626 0 16383 EPSG:3857:15 3678 23252 0 32767 EPSG:3857:16 7356 46504 0 65535 EPSG:3857:17 14713 93009 0 131071 EPSG:3857:18 29426 186018 0 262143 EPSG:3857:19 58852 372036 0 524287 EPSG:3857:20 117704 744073 0 1048575 EPSG:3857:21 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742741 EPSG:3857:21 754398 1057315 943718 1485482 EPSG:3857:22 1508796 2114630 1887436 2970965 EPSG:3857:23 3017592 4229260 3774873 5941930 EPSG:3857:24 6035184 8458521 7549747 11883861 EPSG:3857:25 12070369 16917042 15099494 23767722 EPSG:3857:26 24140738 33834084 30198988 47535445 EPSG:3857:27 48281477 67668168 60397977 95070890 EPSG:3857:28 96562954 135336336 120795955 190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 7 11 EPSG:4326:4 3 8 14 22 EPSG:4326:5 7 16 28 45 EPSG:4326:6 15 32 57 90 EPSG:4326:7 31 65 115 181 EPSG:4326:8 63 130 230 362 EPSG:4326:9 127 260 460 725 EPSG:4326:10 255 520 921 1450 EPSG:4326:11 511 1041 1843 2901 EPSG:4326:12 1023 2082 3686 5802 EPSG:4326:13 2047 4164 7372 11605 EPSG:4326:14 4095 8328 14745 23210 EPSG:4326:15 8191 16657 29491 46421 EPSG:4326:16 16383 33314 58982 92842 EPSG:4326:17 32767 66628 117964 185685 EPSG:4326:18 65535 133256 235929 371370 EPSG:4326:19 131071 266513 471859 742741 EPSG:4326:20 262143 533026 943718 1485482 EPSG:4326:21 524287 1066052 1887436 2970965 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 230 362 EPSG:3857:10 368 516 460 725 EPSG:3857:11 736 1032 921 1450 EPSG:3857:12 1473 2065 1843 2901 EPSG:3857:13 2946 4130 3686 5802 EPSG:3857:14 5893 8260 7372 11605 EPSG:3857:15 11787 16520 14745 23210 EPSG:3857:16 23574 33041 29491 46421 EPSG:3857:17 47149 66082 58982 92842 EPSG:3857:18 94299 132164 117964 185685 EPSG:3857:19 188599 264328 235929 371370 EPSG:3857:20 377199 528657 471859 742741 EPSG:3857:21 754398 1057315 943718 1485482 EPSG:3857:22 1508796 2114630 1887436 2970965 EPSG:3857:23 3017592 4229260 3774873 5941930 EPSG:3857:24 6035184 8458521 7549747 11883861 EPSG:3857:25 12070369 16917042 15099494 23767722 EPSG:3857:26 24140738 33834084 30198988 47535445 EPSG:3857:27 48281477 67668168 60397977 95070890 EPSG:3857:28 96562954 135336336 120795955 190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 hfp2005_meris_wgs Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11 -179.99997804642848 -65.24741434935741 180.0 89.8976232152096 MapX_UNDP_nd:hfp2005_meris_wgs image/png image/vnd.jpeg-png image/jpeg image/png8 EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12146 0 16383 EPSG:3857:15 0 24293 0 32767 EPSG:3857:16 0 48587 0 65535 EPSG:3857:17 0 97175 0 131071 EPSG:3857:18 0 194351 0 262143 EPSG:3857:19 0 388703 0 524287 EPSG:3857:20 0 777407 0 1048575 EPSG:3857:21 0 1554814 0 2097151 EPSG:3857:22 -1 3109629 0 4194304 EPSG:3857:23 -1 6219258 0 8388608 EPSG:3857:24 0 12438517 1 16777215 EPSG:3857:25 0 24877035 2 33554431 EPSG:3857:26 0 49754070 4 67108863 EPSG:3857:27 0 99508140 8 134217727 EPSG:3857:28 -1 199016280 16 268435456 EPSG:3857:29 0 398032561 32 536870911 EPSG:3857:30 0 796065123 65 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 55 0 127 EPSG:4326:7 0 110 0 255 EPSG:4326:8 0 220 0 511 EPSG:4326:9 0 441 0 1023 EPSG:4326:10 0 883 0 2047 EPSG:4326:11 1 1766 0 4095 EPSG:4326:12 2 3532 0 8191 EPSG:4326:13 4 7065 0 16383 EPSG:4326:14 9 14130 0 32767 EPSG:4326:15 18 28261 0 65535 EPSG:4326:16 37 56523 0 131071 EPSG:4326:17 74 113047 0 262143 EPSG:4326:18 149 226095 0 524287 EPSG:4326:19 298 452190 0 1048575 EPSG:4326:20 596 904381 0 2097151 EPSG:4326:21 1192 1808763 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 23 0 31 EPSG:900913:6 0 47 0 63 EPSG:900913:7 0 94 0 127 EPSG:900913:8 0 189 0 255 EPSG:900913:9 0 379 0 511 EPSG:900913:10 0 759 0 1023 EPSG:900913:11 0 1518 0 2047 EPSG:900913:12 0 3036 0 4095 EPSG:900913:13 0 6073 0 8191 EPSG:900913:14 0 12146 0 16383 EPSG:900913:15 0 24293 0 32767 EPSG:900913:16 0 48587 0 65535 EPSG:900913:17 0 97175 0 131071 EPSG:900913:18 0 194351 0 262143 EPSG:900913:19 0 388703 0 524287 EPSG:900913:20 0 777407 0 1048575 EPSG:900913:21 0 1554814 0 2097151 EPSG:900913:22 0 3109629 0 4194303 EPSG:900913:23 0 6219258 0 8388607 EPSG:900913:24 0 12438517 1 16777215 EPSG:900913:25 0 24877035 2 33554431 EPSG:900913:26 0 49754070 4 67108863 EPSG:900913:27 0 99508140 8 134217727 EPSG:900913:28 0 199016280 16 268435455 EPSG:900913:29 0 398032561 32 536870911 EPSG:900913:30 0 796065123 65 1073741823 Combination Tsunami/Sea grasses at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_sea6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tsunami/Mangroves at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_man6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 validation_overlay -17.367169957539442 14.763385552886751 -17.28660005665432 14.822822501580214 dakar_waste:validation_overlay image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7509 7512 7401 7405 EPSG:3857:15 15019 15025 14803 14810 EPSG:3857:16 30038 30050 29606 29621 EPSG:3857:17 60077 60100 59212 59242 EPSG:3857:18 120155 120200 118425 118484 EPSG:3857:19 240311 240401 236851 236968 EPSG:3857:20 480623 480802 473702 473937 EPSG:3857:21 961247 961605 947404 947874 EPSG:3857:22 1922494 1923210 1894809 1895748 EPSG:3857:23 3844988 3846421 3789619 3791497 EPSG:3857:24 7689977 7692842 7579239 7582994 EPSG:3857:25 15379954 15385684 15158478 15165988 EPSG:3857:26 30759908 30771368 30316956 30331976 EPSG:3857:27 61519817 61542736 60633913 60663952 EPSG:3857:28 123039634 123085473 121267827 121327904 EPSG:3857:29 246079269 246170947 242535654 242655809 EPSG:3857:30 492158539 492341894 485071309 485311619 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 462 EPSG:4326:10 427 428 925 925 EPSG:4326:11 855 856 1850 1851 EPSG:4326:12 1710 1712 3700 3702 EPSG:4326:13 3421 3424 7401 7405 EPSG:4326:14 6842 6848 14803 14810 EPSG:4326:15 13685 13696 29606 29621 EPSG:4326:16 27371 27392 59212 59242 EPSG:4326:17 54742 54785 118425 118484 EPSG:4326:18 109484 109571 236851 236968 EPSG:4326:19 218969 219142 473702 473937 EPSG:4326:20 437938 438285 947404 947874 EPSG:4326:21 875877 876570 1894809 1895748 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7509 7512 7401 7405 EPSG:3857:15 15019 15025 14803 14810 EPSG:3857:16 30038 30050 29606 29621 EPSG:3857:17 60077 60100 59212 59242 EPSG:3857:18 120155 120200 118425 118484 EPSG:3857:19 240311 240401 236851 236968 EPSG:3857:20 480623 480802 473702 473937 EPSG:3857:21 961247 961605 947404 947874 EPSG:3857:22 1922494 1923210 1894809 1895748 EPSG:3857:23 3844988 3846421 3789619 3791497 EPSG:3857:24 7689977 7692842 7579239 7582994 EPSG:3857:25 15379954 15385684 15158478 15165988 EPSG:3857:26 30759908 30771368 30316956 30331976 EPSG:3857:27 61519817 61542736 60633913 60663952 EPSG:3857:28 123039634 123085473 121267827 121327904 EPSG:3857:29 246079269 246170947 242535654 242655809 EPSG:3857:30 492158539 492341894 485071309 485311619 total_extreme_events_Automn_output_opt -17.999999999999943 -1.4999999999999432 75.00000000000006 45.00000000000006 unccd:total_extreme_events_Automn_output_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 230 362 EPSG:3857:10 368 516 460 725 EPSG:3857:11 736 1032 921 1450 EPSG:3857:12 1473 2065 1843 2901 EPSG:3857:13 2946 4130 3686 5802 EPSG:3857:14 5893 8260 7372 11605 EPSG:3857:15 11787 16520 14745 23210 EPSG:3857:16 23574 33041 29491 46421 EPSG:3857:17 47149 66082 58982 92842 EPSG:3857:18 94299 132164 117964 185685 EPSG:3857:19 188599 264328 235929 371370 EPSG:3857:20 377199 528657 471859 742741 EPSG:3857:21 754398 1057315 943718 1485482 EPSG:3857:22 1508796 2114630 1887436 2970965 EPSG:3857:23 3017592 4229260 3774873 5941930 EPSG:3857:24 6035184 8458521 7549747 11883861 EPSG:3857:25 12070369 16917042 15099494 23767722 EPSG:3857:26 24140738 33834084 30198988 47535445 EPSG:3857:27 48281477 67668168 60397977 95070890 EPSG:3857:28 96562954 135336336 120795955 190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 7 11 EPSG:4326:4 3 8 14 22 EPSG:4326:5 7 16 28 45 EPSG:4326:6 15 32 57 90 EPSG:4326:7 31 65 115 181 EPSG:4326:8 63 130 230 362 EPSG:4326:9 127 260 460 725 EPSG:4326:10 255 520 921 1450 EPSG:4326:11 511 1041 1843 2901 EPSG:4326:12 1023 2082 3686 5802 EPSG:4326:13 2047 4164 7372 11605 EPSG:4326:14 4095 8328 14745 23210 EPSG:4326:15 8191 16657 29491 46421 EPSG:4326:16 16383 33314 58982 92842 EPSG:4326:17 32767 66628 117964 185685 EPSG:4326:18 65535 133256 235929 371370 EPSG:4326:19 131071 266513 471859 742741 EPSG:4326:20 262143 533026 943718 1485482 EPSG:4326:21 524287 1066052 1887436 2970965 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 230 362 EPSG:3857:10 368 516 460 725 EPSG:3857:11 736 1032 921 1450 EPSG:3857:12 1473 2065 1843 2901 EPSG:3857:13 2946 4130 3686 5802 EPSG:3857:14 5893 8260 7372 11605 EPSG:3857:15 11787 16520 14745 23210 EPSG:3857:16 23574 33041 29491 46421 EPSG:3857:17 47149 66082 58982 92842 EPSG:3857:18 94299 132164 117964 185685 EPSG:3857:19 188599 264328 235929 371370 EPSG:3857:20 377199 528657 471859 742741 EPSG:3857:21 754398 1057315 943718 1485482 EPSG:3857:22 1508796 2114630 1887436 2970965 EPSG:3857:23 3017592 4229260 3774873 5941930 EPSG:3857:24 6035184 8458521 7549747 11883861 EPSG:3857:25 12070369 16917042 15099494 23767722 EPSG:3857:26 24140738 33834084 30198988 47535445 EPSG:3857:27 48281477 67668168 60397977 95070890 EPSG:3857:28 96562954 135336336 120795955 190141781 EPSG:3857:29 193125908 270672673 241591910 380283562 EPSG:3857:30 386251817 541345347 483183820 760567125 Global Peatlands Distribution The Global Peatland Map, launched by the Global Peatlands Initiative and its partners, enhances our core knowledge of the location and extent of peatlands worldwide, and serves as the foundational map for the Global Peatlands Assessment, which consolidates the best available science to provide a comprehensive global overview of the State of the World’s Peatlands. The map’s uncertainty levels vary depending on the region. The data primarily originates from scientific publications on soil and peatland research, as well as from other ‘external’ sources such as national agencies and online repositories. For more information see Global Peatland Map This dataset was used for map production, statistics and analysis in the Global Peatland Assessment 2022. The dataset was compiled by the Greifswald Mire Centre with data of the Global Peatland Database. UNEP (2022). Global Peatlands Assessment – The State of the World’s Peatlands: Evidence for action toward the conservation, restoration, and sustainable management of peatlands. Main Report. Global Peatlands Initiative. United Nations Environment Programme, Nairobi. Greifswald Mire Centre (2022) Global Peatland Map 2.0. Underlying dataset of the UNEP Global Peatland Assessment - The State of the World’s Peatlands: Evidence for action toward the conservation, restoration, and sustainable management of peatlands, Global Peatlands Initiative, United Nations Environment Programme, Nairobi. -179.766242816 -74.342809401 179.733393112 78.32251340541809 peatlands:peatGPA22WGS_2cl_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 1 6 0 7 EPSG:3857:4 2 13 0 15 EPSG:3857:5 4 26 0 31 EPSG:3857:6 8 52 0 63 EPSG:3857:7 17 104 0 127 EPSG:3857:8 35 208 0 255 EPSG:3857:9 70 417 0 511 EPSG:3857:10 140 835 0 1023 EPSG:3857:11 280 1670 1 2046 EPSG:3857:12 561 3341 2 4092 EPSG:3857:13 1123 6682 5 8185 EPSG:3857:14 2246 13365 10 16371 EPSG:3857:15 4492 26731 21 32743 EPSG:3857:16 8984 53463 42 65487 EPSG:3857:17 17968 106927 85 130974 EPSG:3857:18 35936 213855 170 261949 EPSG:3857:19 71873 427711 340 523899 EPSG:3857:20 143747 855422 680 1047799 EPSG:3857:21 287495 1710844 1361 2095598 EPSG:3857:22 574990 3421688 2723 4191197 EPSG:3857:23 1149980 6843377 5446 8382395 EPSG:3857:24 2299960 13686755 10893 16764791 EPSG:3857:25 4599920 27373511 21787 33529582 EPSG:3857:26 9199840 54747023 43575 67059164 EPSG:3857:27 18399681 109494046 87150 134118329 EPSG:3857:28 36799362 218988093 174301 268236659 EPSG:3857:29 73598725 437976186 348603 536473319 EPSG:3857:30 147197450 875952373 697207 1072946638 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 1 14 0 31 EPSG:4326:5 2 29 0 63 EPSG:4326:6 4 58 0 127 EPSG:4326:7 8 116 0 255 EPSG:4326:8 16 233 0 511 EPSG:4326:9 33 467 0 1023 EPSG:4326:10 66 934 1 2046 EPSG:4326:11 132 1869 2 4092 EPSG:4326:12 265 3739 5 8185 EPSG:4326:13 531 7479 10 16371 EPSG:4326:14 1062 14958 21 32743 EPSG:4326:15 2125 29917 42 65487 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605388696 Burned area 2020 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2020 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2021 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2021 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Commercial Activity (Shipping Lanes) 2008 - KNB Vessel identity and location information was obtained using two approaches. (1) Over the past 20 years, 10-20% of the vessel fleet has voluntarily participated in collecting meteorological data for the open ocean, which includes location at the time of measurement, as part of the Volunteer Observing System (VOS). (2) In order to improve maritime safety, in 2002 the International Maritime Organization SOLAS agreement required all vessels over 300 gross tonnage (GT) and vessels carrying passengers to equip Automatic Identification System (AIS) transceivers, which use the Global Positioning System (GPS) to precisely locate vessels. A single year sample of the VOS data was used for analysis. These data ignores vessel type, and included observations from only 12% of the vessel fleet. The ships included are a spatially- and statistically-biased sample of the population, making the modelled results somewhat misleading. Data have limited observation frequency, leading to gaps that when directly interpolated with geodesic paths, create invalid routes which cross land masses. Routing model was used to create a visibility graph of the oceans, creating valid potential movement paths. These movement paths are based on the assumption that mariners will prefer great circle distances when possible. Raw stressor data from "Benjamin Halpern, Melanie Frazier, John Potapenko, Kenneth Casey, Kellee Koenig, et al. 2015. Cumulative human impacts: raw stressor data (2008 and 2013). Knowledge Network for Biocomplexity. doi:10.5063/F1S180FS." -179.99999978909742 -89.99765318080641 179.99802237886044 85.2846797894314 unea_pollution:08_shipping_halpern_KNB_WGS84 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 0 63 0 63 EPSG:3857:7 0 127 0 127 EPSG:3857:8 0 255 0 255 EPSG:3857:9 0 511 0 511 EPSG:3857:10 0 1023 0 1023 EPSG:3857:11 0 2047 0 2047 EPSG:3857:12 0 4095 0 4095 EPSG:3857:13 0 8191 0 8191 EPSG:3857:14 0 16383 0 16383 EPSG:3857:15 0 32767 0 32767 EPSG:3857:16 0 65535 0 65535 EPSG:3857:17 0 131071 0 131071 EPSG:3857:18 0 262143 0 262142 EPSG:3857:19 0 524287 0 524285 EPSG:3857:20 0 1048575 0 1048570 EPSG:3857:21 0 2097151 0 2097140 EPSG:3857:22 -1 4194303 0 4194280 EPSG:3857:23 -1 8388607 0 8388561 EPSG:3857:24 0 16777215 0 16777123 EPSG:3857:25 0 33554431 0 33554247 EPSG:3857:26 0 67108863 0 67108495 EPSG:3857:27 0 134217727 0 134216990 EPSG:3857:28 -1 268435455 0 268433981 EPSG:3857:29 0 536870911 0 536867962 EPSG:3857:30 0 1073741823 0 1073735925 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 6 255 0 511 EPSG:4326:9 13 511 0 1023 EPSG:4326:10 26 1023 0 2047 EPSG:4326:11 53 2047 0 4095 EPSG:4326:12 107 4095 0 8191 EPSG:4326:13 214 8191 0 16383 EPSG:4326:14 429 16383 0 32767 EPSG:4326:15 858 32767 0 65535 EPSG:4326:16 1716 65535 0 131071 EPSG:4326:17 3433 131070 0 262142 EPSG:4326:18 6867 262140 0 524285 EPSG:4326:19 13734 524281 0 1048570 EPSG:4326:20 27468 1048562 0 2097140 EPSG:4326:21 54937 2097124 0 4194280 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 0 31 0 31 EPSG:900913:6 0 63 0 63 EPSG:900913:7 0 127 0 127 EPSG:900913:8 0 255 0 255 EPSG:900913:9 0 511 0 511 EPSG:900913:10 0 1023 0 1023 EPSG:900913:11 0 2047 0 2047 EPSG:900913:12 0 4095 0 4095 EPSG:900913:13 0 8191 0 8191 EPSG:900913:14 0 16383 0 16383 EPSG:900913:15 0 32767 0 32767 EPSG:900913:16 0 65535 0 65535 EPSG:900913:17 0 131071 0 131071 EPSG:900913:18 0 262143 0 262142 EPSG:900913:19 0 524287 0 524285 EPSG:900913:20 0 1048575 0 1048570 EPSG:900913:21 0 2097151 0 2097140 EPSG:900913:22 0 4194303 0 4194280 EPSG:900913:23 0 8388607 0 8388561 EPSG:900913:24 0 16777215 0 16777123 EPSG:900913:25 0 33554431 0 33554247 EPSG:900913:26 0 67108863 0 67108495 EPSG:900913:27 0 134217727 0 134216990 EPSG:900913:28 0 268435455 0 268433981 EPSG:900913:29 0 536870911 0 536867962 EPSG:900913:30 0 1073741823 0 1073735925 Functional Diversity Map Layer provided by Ministry of Environment of Peru. Data are a suite of forest canopy functional trait maps from laser-guided imaging spectroscopy and used them to define distinct forest functional classes. 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EPSG:3857:24 8345223 9277855 4533848 5339857 EPSG:3857:25 16690446 18555710 9067696 10679714 EPSG:3857:26 33380893 37111420 18135392 21359429 EPSG:3857:27 66761786 74222841 36270785 42718859 EPSG:3857:28 133523572 148445682 72541570 85437718 EPSG:3857:29 267047144 296891365 145083141 170875436 EPSG:3857:30 534094288 593782731 290166282 341750872 Temperature anomalies (°C) 2081-2100 (RCP4.5) Temperature anomalies (°C) for the period 2081-2100 based on the climate scenario RCP4.5 (reference 1986-2005). -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:tas_45_81_00 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 6 11 EPSG:4326:4 3 8 13 22 EPSG:4326:5 7 17 27 45 EPSG:4326:6 15 34 54 90 EPSG:4326:7 31 68 109 181 EPSG:4326:8 63 137 218 363 EPSG:4326:9 127 275 436 726 EPSG:4326:10 255 550 872 1453 EPSG:4326:11 510 1101 1745 2906 EPSG:4326:12 1021 2203 3490 5813 EPSG:4326:13 2043 4406 6980 11626 EPSG:4326:14 4086 8812 13960 23252 EPSG:4326:15 8173 17625 27921 46505 EPSG:4326:16 16347 35251 55843 93010 EPSG:4326:17 32695 70502 111687 186020 EPSG:4326:18 65390 141004 223375 372040 EPSG:4326:19 130780 282008 446751 744081 EPSG:4326:20 261561 564017 893503 1488162 EPSG:4326:21 523122 1128034 1787006 2976324 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 136049 111687 186020 EPSG:3857:19 188393 272099 223375 372040 EPSG:3857:20 376786 544199 446751 744081 EPSG:3857:21 753573 1088399 893503 1488162 EPSG:3857:22 1507146 2176799 1787006 2976324 EPSG:3857:23 3014293 4353598 3574013 5952649 EPSG:3857:24 6028587 8707196 7148026 11905299 EPSG:3857:25 12057175 17414392 14296052 23810599 EPSG:3857:26 24114350 34828784 28592104 47621198 EPSG:3857:27 48228701 69657569 57184208 95242396 EPSG:3857:28 96457403 139315139 114368417 190484792 EPSG:3857:29 192914807 278630279 228736834 380969584 EPSG:3857:30 385829614 557260559 457473669 761939168 Kerala DEM 74.85875 8.25375 77.49291666666667 12.842916666666673 ECO-DRR:Kerala_MERIT_DEM image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185582 187500 EPSG:4326:18 112368 119051 371164 375001 EPSG:4326:19 224736 238103 742329 750002 EPSG:4326:20 449472 476206 1484659 1500004 EPSG:4326:21 898945 952412 2969319 3000009 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 20180623Classes Classification of a Sentinel-2 image with post-processing using field knowledge. This research was funded by the Copernicus RawMatCop programme, through funding from EIT RawMaterials and the European Commission DG Internal Market, Industry, Entrepreneurship and SMEs (DG GROW). https://eitrawmaterials.eu/eit-rm-academy/rawmatcop/, in the scope of project CopX: "Geospatial mining transparency through Copernicus and MapX" -74.86103149540197 7.565680150087606 -74.77551708391071 7.624603274629289 UNILIEGE:20180623Classes image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125503 125546 76559 76622 EPSG:3857:19 251006 251093 153119 153244 EPSG:3857:20 502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7497 7503 9569 9577 EPSG:4326:15 14995 15006 19139 19155 EPSG:4326:16 29991 30013 38279 38311 EPSG:4326:17 59983 60026 76559 76622 EPSG:4326:18 119967 120053 153119 153244 EPSG:4326:19 239935 240107 306239 306488 EPSG:4326:20 479871 480214 612478 612977 EPSG:4326:21 959742 960429 1224957 1225954 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15687 15693 9569 9577 EPSG:3857:16 31375 31386 19139 19155 EPSG:3857:17 62751 62773 38279 38311 EPSG:3857:18 125503 125546 76559 76622 EPSG:3857:19 251006 251093 153119 153244 EPSG:3857:20 502013 502187 306239 306488 EPSG:3857:21 1004027 1004374 612478 612977 EPSG:3857:22 2008055 2008748 1224957 1225954 EPSG:3857:23 4016111 4017496 2449915 2451908 EPSG:3857:24 8032222 8034992 4899831 4903816 EPSG:3857:25 16064444 16069985 9799662 9807632 EPSG:3857:26 32128889 32139970 19599324 19615265 EPSG:3857:27 64257778 64279941 39198648 39230530 EPSG:3857:28 128515557 128559882 78397297 78461061 EPSG:3857:29 257031114 257119764 156794594 156922122 EPSG:3857:30 514062228 514239528 313589188 313844245 Combination Tropical cyclone surge/ Coral reefs at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_cor9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 zimbabwe_remote_site_screening_res50 25.237080000000006 -22.417830000000002 33.05608000000001 -15.608830000000003 mapx_chemobs:zimbabwe_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 9 9 9 EPSG:3857:5 17 18 18 18 EPSG:3857:6 34 36 36 37 EPSG:3857:7 69 72 72 75 EPSG:3857:8 139 144 145 151 EPSG:3857:9 278 288 291 303 EPSG:3857:10 556 577 583 606 EPSG:3857:11 1113 1154 1167 1212 EPSG:3857:12 2227 2309 2335 2424 EPSG:3857:13 4455 4619 4670 4848 EPSG:3857:14 8911 9239 9340 9696 EPSG:3857:15 17822 18478 18681 19392 EPSG:3857:16 35645 36957 37362 38785 EPSG:3857:17 71290 73914 74724 77571 EPSG:3857:18 142581 147829 149449 155142 EPSG:3857:19 285162 295658 298898 310285 EPSG:3857:20 570325 591317 597796 620570 EPSG:3857:21 1140650 1182634 1195592 1241141 EPSG:3857:22 2281300 2365269 2391185 2482283 EPSG:3857:23 4562600 4730539 4782370 4964566 EPSG:3857:24 9125200 9461078 9564741 9929132 EPSG:3857:25 18250401 18922157 19129482 19858265 EPSG:3857:26 36500802 37844315 38258964 39716531 EPSG:3857:27 73001604 75688631 76517929 79433063 EPSG:3857:28 146003208 151377262 153035858 158866127 EPSG:3857:29 292006417 302754524 306071717 317732255 EPSG:3857:30 584012834 605509048 612143435 635464510 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 9 9 18 18 EPSG:4326:5 18 19 36 37 EPSG:4326:6 37 39 72 75 EPSG:4326:7 75 79 145 151 EPSG:4326:8 150 159 291 303 EPSG:4326:9 300 319 583 606 EPSG:4326:10 600 639 1167 1212 EPSG:4326:11 1201 1279 2335 2424 EPSG:4326:12 2403 2558 4670 4848 EPSG:4326:13 4806 5116 9340 9696 EPSG:4326:14 9612 10232 18681 19392 EPSG:4326:15 19225 20465 37362 38785 EPSG:4326:16 38451 40930 74724 77571 EPSG:4326:17 76902 81860 149449 155142 EPSG:4326:18 153804 163720 298898 310285 EPSG:4326:19 307608 327440 597796 620570 EPSG:4326:20 615216 654881 1195592 1241141 EPSG:4326:21 1230432 1309762 2391185 2482283 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 9 9 9 EPSG:3857:5 17 18 18 18 EPSG:3857:6 34 36 36 37 EPSG:3857:7 69 72 72 75 EPSG:3857:8 139 144 145 151 EPSG:3857:9 278 288 291 303 EPSG:3857:10 556 577 583 606 EPSG:3857:11 1113 1154 1167 1212 EPSG:3857:12 2227 2309 2335 2424 EPSG:3857:13 4455 4619 4670 4848 EPSG:3857:14 8911 9239 9340 9696 EPSG:3857:15 17822 18478 18681 19392 EPSG:3857:16 35645 36957 37362 38785 EPSG:3857:17 71290 73914 74724 77571 EPSG:3857:18 142581 147829 149449 155142 EPSG:3857:19 285162 295658 298898 310285 EPSG:3857:20 570325 591317 597796 620570 EPSG:3857:21 1140650 1182634 1195592 1241141 EPSG:3857:22 2281300 2365269 2391185 2482283 EPSG:3857:23 4562600 4730539 4782370 4964566 EPSG:3857:24 9125200 9461078 9564741 9929132 EPSG:3857:25 18250401 18922157 19129482 19858265 EPSG:3857:26 36500802 37844315 38258964 39716531 EPSG:3857:27 73001604 75688631 76517929 79433063 EPSG:3857:28 146003208 151377262 153035858 158866127 EPSG:3857:29 292006417 302754524 306071717 317732255 EPSG:3857:30 584012834 605509048 612143435 635464510 Tsunami hazard frequency -180.0 -90.0 180.0 90.0 ECO-DRR:ts_freqaf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Africa Forest Height (Montana State University) The forest structural condition index is derived from the University of Maryland canopy cover, canopy height, and time since forest loss data sets. The index spans from short, open-canopy, recently disturbed forests to tall, closed canopy forests that have not been disturbed with the last 14 years. Forest stature and canopy cover are products of both the biophysical potential of a local site and of disturbance history. The tallest, most dense forests are found in settings with favorable climate and soils but with low levels if natural or human disturbance. Such forests have been shown to support high levels of biodiversity, store high levels of carbon, and be more resilient to climate variability. Our maps of forest structural condition are the first to identify locations in the humid tropics of tall, dense forests resulting from high biophysical potential and low disturbance rates. Data are provided by the Montana State University for South America, Africa and Asia separately, and have been merged into a single dataset here. License information: CC-4.0 Attribution. -26.0005 -32.0005 61.0005 32.0005 MapX_UNDP:africa_forheight image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 3 4 3 5 EPSG:3857:4 6 9 6 10 EPSG:3857:5 12 19 13 21 EPSG:3857:6 25 38 27 42 EPSG:3857:7 51 76 54 85 EPSG:3857:8 103 152 109 171 EPSG:3857:9 207 304 219 342 EPSG:3857:10 415 608 438 685 EPSG:3857:11 831 1216 876 1371 EPSG:3857:12 1663 2432 1752 2742 EPSG:3857:13 3326 4865 3504 5484 EPSG:3857:14 6653 9730 7008 10968 EPSG:3857:15 13306 19461 14017 21936 EPSG:3857:16 26613 38922 28034 43872 EPSG:3857:17 53227 77844 56069 87745 EPSG:3857:18 106454 155689 112139 175491 EPSG:3857:19 212909 311378 224278 350982 EPSG:3857:20 425818 622757 448556 701964 EPSG:3857:21 851636 1245515 897112 1403929 EPSG:3857:22 1703272 2491031 1794224 2807859 EPSG:3857:23 3406544 4982063 3588448 5615718 EPSG:3857:24 6813088 9964127 7176896 11231437 EPSG:3857:25 13626176 19928255 14353793 22462874 EPSG:3857:26 27252353 39856510 28707587 44925749 EPSG:3857:27 54504706 79713021 57415175 89851498 EPSG:3857:28 109009413 159426042 114830350 179702997 EPSG:3857:29 218018827 318852084 229660700 359405995 EPSG:3857:30 436037654 637704169 459321400 718811990 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 1 2 3 5 EPSG:4326:3 2 5 6 10 EPSG:4326:4 5 10 13 21 EPSG:4326:5 10 21 27 42 EPSG:4326:6 20 43 54 85 EPSG:4326:7 41 86 109 171 EPSG:4326:8 82 173 219 342 EPSG:4326:9 164 347 438 685 EPSG:4326:10 329 694 876 1371 EPSG:4326:11 659 1388 1752 2742 EPSG:4326:12 1319 2776 3504 5484 EPSG:4326:13 2639 5552 7008 10968 EPSG:4326:14 5279 11104 14017 21936 EPSG:4326:15 10558 22209 28034 43872 EPSG:4326:16 21116 44419 56069 87745 EPSG:4326:17 42233 88838 112139 175491 EPSG:4326:18 84467 177676 224278 350982 EPSG:4326:19 168935 355352 448556 701964 EPSG:4326:20 337871 710704 897112 1403929 EPSG:4326:21 675743 1421408 1794224 2807859 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 1 2 1 2 EPSG:900913:3 3 4 3 5 EPSG:900913:4 6 9 6 10 EPSG:900913:5 12 19 13 21 EPSG:900913:6 25 38 27 42 EPSG:900913:7 51 76 54 85 EPSG:900913:8 103 152 109 171 EPSG:900913:9 207 304 219 342 EPSG:900913:10 415 608 438 685 EPSG:900913:11 831 1216 876 1371 EPSG:900913:12 1663 2432 1752 2742 EPSG:900913:13 3326 4865 3504 5484 EPSG:900913:14 6653 9730 7008 10968 EPSG:900913:15 13306 19461 14017 21936 EPSG:900913:16 26613 38922 28034 43872 EPSG:900913:17 53227 77844 56069 87745 EPSG:900913:18 106454 155689 112139 175491 EPSG:900913:19 212909 311378 224278 350982 EPSG:900913:20 425818 622757 448556 701964 EPSG:900913:21 851636 1245515 897112 1403929 EPSG:900913:22 1703272 2491031 1794224 2807859 EPSG:900913:23 3406544 4982063 3588448 5615718 EPSG:900913:24 6813088 9964127 7176896 11231437 EPSG:900913:25 13626176 19928255 14353793 22462874 EPSG:900913:26 27252353 39856510 28707587 44925749 EPSG:900913:27 54504706 79713021 57415175 89851498 EPSG:900913:28 109009413 159426042 114830350 179702997 EPSG:900913:29 218018827 318852084 229660700 359405995 EPSG:900913:30 436037654 637704169 459321400 718811990 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 3 4 3 5 EPSG:3857:4 6 9 6 10 EPSG:3857:5 12 19 13 21 EPSG:3857:6 25 38 27 42 EPSG:3857:7 51 76 54 85 EPSG:3857:8 103 152 109 171 EPSG:3857:9 207 304 219 342 EPSG:3857:10 415 608 438 685 EPSG:3857:11 831 1216 876 1371 EPSG:3857:12 1663 2432 1752 2742 EPSG:3857:13 3326 4865 3504 5484 EPSG:3857:14 6653 9730 7008 10968 EPSG:3857:15 13306 19461 14017 21936 EPSG:3857:16 26613 38922 28034 43872 EPSG:3857:17 53227 77844 56069 87745 EPSG:3857:18 106454 155689 112139 175491 EPSG:3857:19 212909 311378 224278 350982 EPSG:3857:20 425818 622757 448556 701964 EPSG:3857:21 851636 1245515 897112 1403929 EPSG:3857:22 1703272 2491031 1794224 2807859 EPSG:3857:23 3406544 4982063 3588448 5615718 EPSG:3857:24 6813088 9964127 7176896 11231437 EPSG:3857:25 13626176 19928255 14353793 22462874 EPSG:3857:26 27252353 39856510 28707587 44925749 EPSG:3857:27 54504706 79713021 57415175 89851498 EPSG:3857:28 109009413 159426042 114830350 179702997 EPSG:3857:29 218018827 318852084 229660700 359405995 EPSG:3857:30 436037654 637704169 459321400 718811990 Active Fires Frequency (2025) Raster of Active Fires frequency per square kilometer, based on MODIS Collection 6 Active Fire Product MCD14ML. Only location points described as "presumed vegetation fire" in the attributes are included in the frequency calculation. <br> This layer was produced by UNEP/GRID-Geneva. -180.0 -90.0 180.0 90.0 wesr_risk:fires_density_lastyear image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Spectral Acceleration 1.0 Sec 1500 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_10_s_1500_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Summer precipitations change (%) for the period 2040 - 2059 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_jja_MIDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 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EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Burned area 2019 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2019 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2017 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2017 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 pop_perc_2015_1975 -179.99999680823143 -55.98302144283261 179.99218561802442 83.63964763391371 wesr_climat:pop_perc_2015_1975 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 176 0 255 EPSG:3857:9 20 352 0 511 EPSG:3857:10 40 705 0 1023 EPSG:3857:11 81 1410 0 2047 EPSG:3857:12 163 2820 0 4095 EPSG:3857:13 327 5640 0 8191 EPSG:3857:14 655 11280 0 16383 EPSG:3857:15 1310 22561 0 32767 EPSG:3857:16 2621 45123 0 65534 EPSG:3857:17 5242 90246 0 131069 EPSG:3857:18 10485 180492 0 262138 EPSG:3857:19 20971 360984 0 524276 EPSG:3857:20 41943 721968 0 1048553 EPSG:3857:21 83886 1443936 0 2097106 EPSG:3857:22 167773 2887872 0 4194212 EPSG:3857:23 335547 5775744 0 8388425 EPSG:3857:24 671095 11551488 0 16776851 EPSG:3857:25 1342190 23102976 0 33553703 EPSG:3857:26 2684381 46205952 0 67107407 EPSG:3857:27 5368763 92411905 1 134214814 EPSG:3857:28 10737526 184823811 2 268429629 EPSG:3857:29 21475052 369647623 4 536859258 EPSG:3857:30 42950105 739295247 9 1073718516 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 4 103 0 255 EPSG:4326:8 9 207 0 511 EPSG:4326:9 18 415 0 1023 EPSG:4326:10 36 830 0 2047 EPSG:4326:11 72 1660 0 4095 EPSG:4326:12 144 3321 0 8191 EPSG:4326:13 289 6643 0 16383 EPSG:4326:14 578 13287 0 32767 EPSG:4326:15 1157 26575 0 65534 EPSG:4326:16 2315 53150 0 131069 EPSG:4326:17 4631 106301 0 262138 EPSG:4326:18 9262 212603 0 524276 EPSG:4326:19 18525 425206 0 1048553 EPSG:4326:20 37051 850412 0 2097106 EPSG:4326:21 74103 1700825 0 4194212 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 176 0 255 EPSG:3857:9 20 352 0 511 EPSG:3857:10 40 705 0 1023 EPSG:3857:11 81 1410 0 2047 EPSG:3857:12 163 2820 0 4095 EPSG:3857:13 327 5640 0 8191 EPSG:3857:14 655 11280 0 16383 EPSG:3857:15 1310 22561 0 32767 EPSG:3857:16 2621 45123 0 65534 EPSG:3857:17 5242 90246 0 131069 EPSG:3857:18 10485 180492 0 262138 EPSG:3857:19 20971 360984 0 524276 EPSG:3857:20 41943 721968 0 1048553 EPSG:3857:21 83886 1443936 0 2097106 EPSG:3857:22 167773 2887872 0 4194212 EPSG:3857:23 335547 5775744 0 8388425 EPSG:3857:24 671095 11551488 0 16776851 EPSG:3857:25 1342190 23102976 0 33553703 EPSG:3857:26 2684381 46205952 0 67107407 EPSG:3857:27 5368763 92411905 1 134214814 EPSG:3857:28 10737526 184823811 2 268429629 EPSG:3857:29 21475052 369647623 4 536859258 EPSG:3857:30 42950105 739295247 9 1073718516 Burned area 2018 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2018 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2015 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2015 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2016 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2016 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Human footprint 2000 Brooke A. Williams, Oscar Venter, James R. Allan, Scott C. Atkinson, Jose A. Rehbein, Michelle S. Ward, Moreno Di Marco, Hedley S. Grantham, Jamison Ervin, Scott Goetz, Andrew J. Hansen, Patrick Jantz, Rajeev Pillay, Susana Rodríguez-Buriticá, Christina Supples, Anne L. S. Virnig, James E.M. Watson. (2020). Change in terrestrial human footprint drives continued loss of intact ecosystems. OneEarth. http://dx.doi.org/10.2139/ssrn.3600547 -179.99999995447251 -65.25013301721049 179.99661098079287 89.89762321520959 wesr_biodiversity:hfp2000_merisINT image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12147 0 16383 EPSG:3857:15 0 24294 0 32767 EPSG:3857:16 0 48589 0 65535 EPSG:3857:17 0 97178 0 131070 EPSG:3857:18 0 194356 0 262141 EPSG:3857:19 0 388713 0 524283 EPSG:3857:20 0 777426 0 1048566 EPSG:3857:21 0 1554852 0 2097132 EPSG:3857:22 -1 3109705 0 4194264 EPSG:3857:23 -1 6219410 0 8388529 EPSG:3857:24 0 12438820 0 16777058 EPSG:3857:25 0 24877640 0 33554116 EPSG:3857:26 0 49755280 0 67108232 EPSG:3857:27 0 99510561 0 134216464 EPSG:3857:28 -1 199021122 0 268432928 EPSG:3857:29 0 398042245 0 536865857 EPSG:3857:30 0 796084491 0 1073731715 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 55 0 127 EPSG:4326:7 0 110 0 255 EPSG:4326:8 0 220 0 511 EPSG:4326:9 0 441 0 1023 EPSG:4326:10 0 883 0 2047 EPSG:4326:11 1 1766 0 4095 EPSG:4326:12 2 3532 0 8191 EPSG:4326:13 4 7065 0 16383 EPSG:4326:14 9 14131 0 32767 EPSG:4326:15 18 28262 0 65535 EPSG:4326:16 37 56524 0 131070 EPSG:4326:17 74 113049 0 262141 EPSG:4326:18 149 226099 0 524283 EPSG:4326:19 298 452198 0 1048566 EPSG:4326:20 596 904397 0 2097132 EPSG:4326:21 1192 1808795 0 4194264 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12147 0 16383 EPSG:3857:15 0 24294 0 32767 EPSG:3857:16 0 48589 0 65535 EPSG:3857:17 0 97178 0 131070 EPSG:3857:18 0 194356 0 262141 EPSG:3857:19 0 388713 0 524283 EPSG:3857:20 0 777426 0 1048566 EPSG:3857:21 -1 1554852 0 2097132 EPSG:3857:22 -1 3109705 0 4194264 EPSG:3857:23 0 6219410 0 8388529 EPSG:3857:24 0 12438820 0 16777058 EPSG:3857:25 0 24877640 0 33554116 EPSG:3857:26 0 49755280 0 67108232 EPSG:3857:27 -1 99510561 0 134216464 EPSG:3857:28 0 199021122 0 268432928 EPSG:3857:29 0 398042245 0 536865857 EPSG:3857:30 -1 796084491 0 1073731715 Burned area 2013 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2013 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2014 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2014 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 USAID_CMM_bivariate_ClimateExp_TotalFrag The first mechanism of compound risk assessment—a bivariate map—integrates the fragility and climate data before they are mapped to show the intersection of fragility and climate risks at the first administrative division level for all countries for which data are available. This approach allows comparison of countries across all fragility categories on a single map. However, it loses some granularity in the subnational climate exposure data, which must be aggregated to the first administrative division to be cross-tabulated with the fragility data. The bivariate map uses the total climate exposure data and total fragility data. It is created using the first administrative division polygon files from the Global Administrative Areas database version 2.8. In this map, each country’s national-level fragility category is applied to all administrative divisions in the country. The bivariate map thus retains the five fragility categories seen in the total fragility measure, classifying areas as having low, some, moderate, high, or highest fragility. The climate exposure category is based on a k-median clustering algorithm. The median climate exposure score for each administrative division is determined with spatial analysis in ArcGIS. These median scores are then clustered into five categories of low to high exposure using the k-median algorithm contained in Stata.15. The cross-tabulation of the five fragility categories and the five climate exposure categories are represented on the final bivariate map. The total exposure to climate retain the five exposure categories of low to high exposure (1 to 5) based on the k-median clustering algorithm. The median climate exposure score for each administrative division is determined with spatial analysis in ArcGIS. These median scores are then clustered into five categories of low to high exposure using the k-median algorithm contained in Stata. The climate exposure portion of this study aims to identify places most likely vulnerable to a combination of climate hazards. Geographic location makes some countries more susceptible to climate hazards. Within countries, some areas, such as the coasts, have more exposure to certain kinds of climate hazards. This study assesses climate hazard exposure using historical data on the frequency and magnitude of six hazards, including cyclones, flood events, wildfire events, rainfall anomalies, and chronic aridity. The sixth hazard is a measure of low-elevation coastal zones, which may be susceptible to storm surges and future sea-level rise. The goal is to identify places that in the recent historical record have faced high exposure to climaterelated hazards. This seeks to get a snapshot of places of chronic concern over a long enough time period to say that these are places that have been historically affected by climate-related hazards. The indicators included here use the most recent data available. Some of these indicators, like cyclones, have longerterm data available, while others like floods have data for fewer years. In all cases, this project uses the most recent and broadest set of years for which global data are available to get the best snapshot of climate exposure in the recent past, as close as possible to the present. The total fragility data retain the five fragility categories seen in the total fragility measure, classifying areas as having low, some, moderate, high, or highest fragility. To help achieve this study’s goal of identifying the intersection of fragility and climate risks globally, this study develops a new fragility measure. Developing a new measure specifically for this purpose provides a comprehensive fragility measure while avoiding use of existing fragility measures that include environmental indicators and thus should not be overlaid on climate hazards. This study uses open-source data to create a measure of state fragility that is similar in composition and outcome to USAID’s internal methods and framework for analyzing fragility.11 Like USAID’s internal measure, the new measure assesses fragility in state effectiveness and legitimacy in four key spheres: political, security, economic, and social. This is based on an understanding of fragility as being rooted in poor state capacity and poor state-society relationships, both of which can contribute to instability. Poor state capacity and state-society relationships can lead to and perpetuate other forms of overt instability, including conflict or an inability to address and mitigate stresses such as a changing environment, difficult global financial situations, or conflict in neighboring states. This <a href="https://pdf.usaid.gov/pdf_docs/PA00TBFH.pdf"target=_blank>document</a> provide a detailed approach on the generation of this bivariate map and its attributes. -179.99999999999994 -90.0 180.0 83.65833282470703 UN_Sahel:USAID_CMM_bivariate_exp_frag image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 40 1023 0 1023 EPSG:3857:11 80 2047 0 2047 EPSG:3857:12 161 4095 0 4095 EPSG:3857:13 323 8191 0 8191 EPSG:3857:14 647 16383 0 16383 EPSG:3857:15 1295 32767 0 32767 EPSG:3857:16 2590 65535 0 65535 EPSG:3857:17 5181 131071 0 131071 EPSG:3857:18 10362 262143 0 262143 EPSG:3857:19 20725 524287 0 524287 EPSG:3857:20 41451 1048575 0 1048575 EPSG:3857:21 82902 2097151 0 2097151 EPSG:3857:22 165805 4194303 0 4194304 EPSG:3857:23 331611 8388607 0 8388608 EPSG:3857:24 663223 16777215 0 16777215 EPSG:3857:25 1326446 33554431 0 33554431 EPSG:3857:26 2652893 67108863 0 67108863 EPSG:3857:27 5305787 134217727 0 134217727 EPSG:3857:28 10611574 268435455 0 268435456 EPSG:3857:29 21223148 536870911 0 536870911 EPSG:3857:30 42446297 1073741823 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 9 255 0 511 EPSG:4326:9 18 511 0 1023 EPSG:4326:10 36 1023 0 2047 EPSG:4326:11 72 2047 0 4095 EPSG:4326:12 144 4095 0 8191 EPSG:4326:13 288 8191 0 16383 EPSG:4326:14 577 16383 0 32767 EPSG:4326:15 1154 32767 0 65535 EPSG:4326:16 2308 65535 0 131071 EPSG:4326:17 4617 131071 0 262143 EPSG:4326:18 9235 262143 0 524287 EPSG:4326:19 18471 524287 0 1048575 EPSG:4326:20 36942 1048575 0 2097151 EPSG:4326:21 73885 2097151 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 1 31 0 31 EPSG:900913:6 2 63 0 63 EPSG:900913:7 5 127 0 127 EPSG:900913:8 10 255 0 255 EPSG:900913:9 20 511 0 511 EPSG:900913:10 40 1023 0 1023 EPSG:900913:11 80 2047 0 2047 EPSG:900913:12 161 4095 0 4095 EPSG:900913:13 323 8191 0 8191 EPSG:900913:14 647 16383 0 16383 EPSG:900913:15 1295 32767 0 32767 EPSG:900913:16 2590 65535 0 65535 EPSG:900913:17 5181 131071 0 131071 EPSG:900913:18 10362 262143 0 262143 EPSG:900913:19 20725 524287 0 524287 EPSG:900913:20 41451 1048575 0 1048575 EPSG:900913:21 82902 2097151 0 2097151 EPSG:900913:22 165805 4194303 0 4194303 EPSG:900913:23 331611 8388607 0 8388607 EPSG:900913:24 663223 16777215 0 16777215 EPSG:900913:25 1326446 33554431 0 33554431 EPSG:900913:26 2652893 67108863 0 67108863 EPSG:900913:27 5305787 134217727 0 134217727 EPSG:900913:28 10611574 268435455 0 268435455 EPSG:900913:29 21223148 536870911 0 536870911 EPSG:900913:30 42446297 1073741823 0 1073741823 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 1 31 0 31 EPSG:3857:6 2 63 0 63 EPSG:3857:7 5 127 0 127 EPSG:3857:8 10 255 0 255 EPSG:3857:9 20 511 0 511 EPSG:3857:10 40 1023 0 1023 EPSG:3857:11 80 2047 0 2047 EPSG:3857:12 161 4095 0 4095 EPSG:3857:13 323 8191 0 8191 EPSG:3857:14 647 16383 0 16383 EPSG:3857:15 1295 32767 0 32767 EPSG:3857:16 2590 65535 0 65535 EPSG:3857:17 5181 131071 0 131071 EPSG:3857:18 10362 262143 0 262143 EPSG:3857:19 20725 524287 0 524287 EPSG:3857:20 41451 1048575 0 1048575 EPSG:3857:21 82902 2097151 0 2097152 EPSG:3857:22 165805 4194303 0 4194304 EPSG:3857:23 331611 8388607 0 8388607 EPSG:3857:24 663223 16777215 0 16777215 EPSG:3857:25 1326446 33554431 0 33554431 EPSG:3857:26 2652893 67108863 0 67108863 EPSG:3857:27 5305787 134217727 0 134217728 EPSG:3857:28 10611574 268435455 0 268435455 EPSG:3857:29 21223148 536870911 0 536870911 EPSG:3857:30 42446297 1073741823 0 1073741824 Peak Ground Acceleration PGA 250 Years (cm/s2) For the GAR Atlas, a fully probabilistic seismic hazard analysis at global level was developed by CIMNE and INGENIAR Ltda. This hazard model is a continuation and improvement of the one developed in the framework of GAR13 where a set of tectonic provinces were identified and characterized by means of a set of parameters that describe the future seismic activity on each of them based on historical records together with relationships to obtain hazard intensities as a function of magnitude and distance. The hazard analysis was performed using the program CRISIS2014, a state-of-the-art tool for these kinds of tasks and widely known and acknowledged by experts in the field across the world. The chosen hazard intensity measure for this case was spectral acceleration and to guarantee a good connection between the hazard and the exposure characteristics, results for several ordinates beteween 0.0 and 2.3 seconds were computed. More details about the probabilistic seismic hazard analysis can be found in Cardona et al. (2015). -180.0 -90.0 180.0 90.0 wesr_risk:pga_250_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Realised Clean Water Provision <span style="font-size:1em"> This dataset consists of a globally normalized map (from 0 to 1) of pixels ranked for their relative importance in delivering clean water to downstream beneficiaries. Water pollution is estimated based on the Human Footprint on Water Quality (HFWQ) index. The HFWQ is a measure of the extent to which water runoff is drawn from contaminating human land uses, both point (urban, roads, mining, oil and gas) and non-point (unprotected cropland, unprotected pasture) sources. The HFWQ is calculated relative to all runoff by cumulating the downstream runoff from polluting and non-polluting land uses and expressing the former runoff as a proportion of the total runoff. <br> <br> Realised provisioning is high where the prevailing climate and land use generate high volumes of clean water which can be used (and reused) by large numbers of downstream users. The greater the downstream population, number of dams and actual water available, the greater the service provided. If there is plenty of water, but no people or dams, then there is no realised service. In this way, not all water provides a direct service, only that water that is accessed and used. <br> <br> All analyses were carried out using the WaterWorld (Mulligan 2013) and Co$ting Nature (Mulligan et al. 2010) ecosystem services assessment tools (<a href="https://www.policysupport.org" target="_blank">www.policysupport.org</a>). <br> <br> <u>References:</u> <ul> <li> Mulligan, M. (2013). WaterWorld: a self-parameterising, physically based model for application in data-poor but problem-rich environments globally. Hydrology research 44, 5; 748-769. </li> <li> Mulligan, M.A. Guerry, K. Arkema, K. Bagstad and F. Villa (2010) Capturing and quantifying the flow of ecosystem services in Silvestri S., Kershaw F., (eds.). Framing the flow: Innovative Approaches to Understand, Protect and Value Ecosystem Services Across Linked Habitats. UN Environment Programme World Conservation Monitoring Centre, Cambridge, UK. ISBN 978-92-807-3065-4. </li> </ul> </span> -179.58826144943154 -55.983070494175905 179.5477094321325 83.99999999995521 grid_data_core:realized_clean_water_prov_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 44 0 63 EPSG:3857:7 3 88 0 127 EPSG:3857:8 7 176 0 255 EPSG:3857:9 15 352 0 511 EPSG:3857:10 31 705 1 1022 EPSG:3857:11 62 1410 2 2045 EPSG:3857:12 125 2820 4 4090 EPSG:3857:13 251 5640 9 8181 EPSG:3857:14 502 11280 18 16363 EPSG:3857:15 1005 22561 37 32726 EPSG:3857:16 2011 45123 74 65453 EPSG:3857:17 4023 90246 149 130907 EPSG:3857:18 8047 180492 299 261814 EPSG:3857:19 16095 360984 599 523629 EPSG:3857:20 32191 721968 1199 1047258 EPSG:3857:21 64382 1443936 2398 2094517 EPSG:3857:22 128764 2887873 4797 4189034 EPSG:3857:23 257528 5775746 9594 8378068 EPSG:3857:24 515056 11551492 19188 16756137 EPSG:3857:25 1030113 23102984 38376 33512275 EPSG:3857:26 2060227 46205969 76753 67024550 EPSG:3857:27 4120454 92411938 153507 134049101 EPSG:3857:28 8240909 184823877 307014 268098203 EPSG:3857:29 16481819 369647754 614028 536196407 EPSG:3857:30 32963639 739295508 1228057 1072392814 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 4 103 0 255 EPSG:4326:8 8 207 0 511 EPSG:4326:9 17 415 1 1022 EPSG:4326:10 34 830 2 2045 EPSG:4326:11 68 1660 4 4090 EPSG:4326:12 136 3321 9 8181 EPSG:4326:13 273 6643 18 16363 EPSG:4326:14 546 13287 37 32726 EPSG:4326:15 1092 26575 74 65453 EPSG:4326:16 2184 53150 149 130907 EPSG:4326:17 4369 106301 299 261814 EPSG:4326:18 8738 212603 599 523629 EPSG:4326:19 17476 425206 1199 1047258 EPSG:4326:20 34952 850413 2398 2094517 EPSG:4326:21 69905 1700826 4797 4189034 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 1 44 0 63 EPSG:3857:7 3 88 0 127 EPSG:3857:8 7 176 0 255 EPSG:3857:9 15 352 0 511 EPSG:3857:10 31 705 1 1022 EPSG:3857:11 62 1410 2 2045 EPSG:3857:12 125 2820 4 4090 EPSG:3857:13 251 5640 9 8181 EPSG:3857:14 502 11280 18 16363 EPSG:3857:15 1005 22561 37 32726 EPSG:3857:16 2011 45123 74 65453 EPSG:3857:17 4023 90246 149 130907 EPSG:3857:18 8047 180492 299 261814 EPSG:3857:19 16095 360984 599 523629 EPSG:3857:20 32191 721968 1199 1047258 EPSG:3857:21 64382 1443936 2398 2094517 EPSG:3857:22 128764 2887873 4797 4189034 EPSG:3857:23 257528 5775746 9594 8378068 EPSG:3857:24 515056 11551492 19188 16756137 EPSG:3857:25 1030113 23102984 38376 33512275 EPSG:3857:26 2060227 46205969 76753 67024550 EPSG:3857:27 4120454 92411938 153507 134049101 EPSG:3857:28 8240909 184823877 307014 268098203 EPSG:3857:29 16481819 369647754 614028 536196407 EPSG:3857:30 32963639 739295508 1228057 1072392814 Burned area 2011 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2011 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Yearly emissions of CH4 - 2018 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -85.19999999999004 179.99999999997954 90.0 wesr_climat:v60_CH4_2018_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 0 62 0 127 EPSG:4326:7 0 124 0 255 EPSG:4326:8 0 249 0 511 EPSG:4326:9 0 498 0 1023 EPSG:4326:10 0 996 0 2047 EPSG:4326:11 0 1993 0 4095 EPSG:4326:12 0 3986 0 8191 EPSG:4326:13 0 7973 0 16383 EPSG:4326:14 0 15947 0 32767 EPSG:4326:15 0 31894 0 65535 EPSG:4326:16 0 63788 0 131071 EPSG:4326:17 0 127576 0 262143 EPSG:4326:18 0 255153 0 524287 EPSG:4326:19 0 510306 0 1048575 EPSG:4326:20 0 1020613 0 2097151 EPSG:4326:21 0 2041227 0 4194303 EPSG:900913 EPSG:3857_512 Burned area 2012 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2012 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Human footprint 2013 Brooke A. Williams, Oscar Venter, James R. Allan, Scott C. Atkinson, Jose A. Rehbein, Michelle S. Ward, Moreno Di Marco, Hedley S. Grantham, Jamison Ervin, Scott Goetz, Andrew J. Hansen, Patrick Jantz, Rajeev Pillay, Susana Rodríguez-Buriticá, Christina Supples, Anne L. S. Virnig, James E.M. Watson. (2020). Change in terrestrial human footprint drives continued loss of intact ecosystems. 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(2022). Nature Geoscience. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. ------------------------------------------------------------------------------------- This is a raster file representing modelled peat thickness (in m below the surface) across the central Congo Basin peatland complex. For each pixel, the median value of 100 Random Forest (RF) regressions is provided. Each RF regression was trained on 463 peat thickness measurements in the field, and using 4 predictor variables: - distance from the peatland margin, - precipitation seasonality, - climatic water balance (precipitation minus potential evapotranspiration), - distance from the nearest drainage point. For each of the 100 regressions, a different input map of distance from the peatland margin was constructed, by randomly selecting (with replacement) a minimum peat probability threshold > 0 and < 100 % and generating a binary peat/non-peat map from the peat probability map (combined hardwood + palm dominated peat swamp probabilities). This binary map was then used to calculate the shortest distance to a non-peat pixel. ---------------------------------------------------------------------------------------- Projection and file details: The file is a GeoTIFF in a lat/long WGS-84 projection and a pixel size of 0.00044444 degrees (c. 50 m). --------------------------------------------------------------------------------------- You are free to use these data for any purpose provided you cite the original paper. The file was created by Bart Crezee and Edward Mitchard. 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EPSG:3857:10 402 406 494 501 EPSG:3857:11 804 813 988 1002 EPSG:3857:12 1609 1627 1976 2004 EPSG:3857:13 3219 3254 3953 4009 EPSG:3857:14 6438 6508 7907 8018 EPSG:3857:15 12876 13016 15815 16037 EPSG:3857:16 25752 26032 31631 32075 EPSG:3857:17 51505 52064 63262 64150 EPSG:3857:18 103011 104129 126525 128301 EPSG:3857:19 206023 208258 253051 256603 EPSG:3857:20 412046 416516 506103 513207 EPSG:3857:21 824093 833033 1012207 1026415 EPSG:3857:22 1648187 1666066 2024415 2052830 EPSG:3857:23 3296374 3332133 4048830 4105660 EPSG:3857:24 6592749 6664267 8097660 8211320 EPSG:3857:25 13185498 13328535 16195321 16422641 EPSG:3857:26 26370997 26657071 32390642 32845283 EPSG:3857:27 52741994 53314142 64781284 65690567 EPSG:3857:28 105483988 106628284 129562568 131381135 EPSG:3857:29 210967976 213256568 259125136 262762271 EPSG:3857:30 421935953 426513136 518250273 525524542 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 2 2 7 7 EPSG:4326:4 4 4 15 15 EPSG:4326:5 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579874153 618804814 Spectral Acceleration 0.2 Sec 2475 Years -180.0 -90.0 180.0 90.0 wesr_risk:spectral_acceleration_02_s_2475_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Global mercury emissions to air from anthropogenic sources in 2015 (kg/cell) Geospatially distributed (gridded) global mercury emissions to air from anthropogenic sources in 2015. Emissions are derived from the AMAP/UNEP global inventory (AMAP/UN-Environment, 2019), geospatially distributed according to methods described in Steenhuisen and Wilson (2019). The dataset is the version dated 5 January 2018. -180.0 -90.0 180.0 90.0 wesr_pollution:HgT_2015_allsectors_025d__kg_cell image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Drought recurrence map between 1995 and 2024 In the context of global warming, drought is becoming more frequent and intense, particularly in West Africa, where erratic rainfall and rising temperatures are exacerbating water deficits. Senegal, located in the Sahel region, is an emblematic case: since the 1970s, the country has been undergoing progressive aridification, with major impacts on rain-fed agriculture, water resources, and ecosystems. And the Kédougou region is no exception. -13.239460488881921 12.307817707721565 -11.342218608821492 13.461254532531031 risk_southeast_senegal:drought image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491251 EPSG:4326:20 445870 452589 971450 982502 EPSG:4326:21 891741 905179 1942901 1965005 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242356 244079 242862 245625 EPSG:3857:20 484713 488159 485725 491251 EPSG:3857:21 969426 976319 971450 982502 EPSG:3857:22 1938853 1952639 1942901 1965005 EPSG:3857:23 3877707 3905279 3885802 3930011 EPSG:3857:24 7755415 7810559 7771604 7860022 EPSG:3857:25 15510831 15621118 15543208 15720044 EPSG:3857:26 31021663 31242237 31086417 31440089 EPSG:3857:27 62043326 62484474 62172835 62880178 EPSG:3857:28 124086652 124968948 124345670 125760356 EPSG:3857:29 248173304 249937896 248691341 251520713 EPSG:3857:30 496346609 499875793 497382682 503041427 Average year temperature (2011-2020) Average year temperature in °Celsius across the period 2011-2020. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_11_20_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tropical cyclone surge/ Forest at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_for6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 site_0060_Landsat_an -10.858176899138206 8.079534492312552 -10.189521743955197 8.79879002262406 test_antonio_mosaics:site_0060_Landsat_an image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 30 30 EPSG:4326:6 28 29 60 60 EPSG:4326:7 57 58 120 120 EPSG:4326:8 115 116 240 241 EPSG:4326:9 230 233 481 483 EPSG:4326:10 461 466 962 966 EPSG:4326:11 923 932 1924 1932 EPSG:4326:12 1847 1864 3848 3864 EPSG:4326:13 3695 3728 7697 7728 EPSG:4326:14 7391 7456 15395 15456 EPSG:4326:15 14782 14913 30791 30913 EPSG:4326:16 29564 29826 61582 61826 EPSG:4326:17 59128 59652 123165 123652 EPSG:4326:18 118257 119305 246330 247304 EPSG:4326:19 236515 238610 492661 494608 EPSG:4326:20 473031 477221 985322 989217 EPSG:4326:21 946062 954442 1970645 1978435 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 30 30 EPSG:3857:7 60 61 60 60 EPSG:3857:8 121 122 120 120 EPSG:3857:9 243 244 240 241 EPSG:3857:10 486 488 481 483 EPSG:3857:11 973 977 962 966 EPSG:3857:12 1947 1955 1924 1932 EPSG:3857:13 3894 3911 3848 3864 EPSG:3857:14 7789 7823 7697 7728 EPSG:3857:15 15579 15646 15395 15456 EPSG:3857:16 31159 31292 30791 30913 EPSG:3857:17 62319 62584 61582 61826 EPSG:3857:18 124639 125169 123165 123652 EPSG:3857:19 249279 250338 246330 247304 EPSG:3857:20 498558 500676 492661 494608 EPSG:3857:21 997116 1001352 985322 989217 EPSG:3857:22 1994233 2002705 1970645 1978435 EPSG:3857:23 3988466 4005410 3941290 3956870 EPSG:3857:24 7976933 8010820 7882580 7913741 EPSG:3857:25 15953866 16021640 15765160 15827483 EPSG:3857:26 31907733 32043281 31530321 31654967 EPSG:3857:27 63815467 64086562 63060642 63309934 EPSG:3857:28 127630934 128173124 126121284 126619869 EPSG:3857:29 255261868 256346248 252242568 253239739 EPSG:3857:30 510523736 512692496 504485137 506479479 Burnt areas in Kedougou between 2005 and 2014 Forest fire hazard assessment is based on a retrospective analysis of burnt areas, using satellite data from different time periods. The methodology uses the Normalized Burn Ratio (NBR) index, calculated from the near-infrared (NIR) and short-wave infrared (SWIR) spectral bands of the Landsat. -13.238921499711449 12.308356696892037 -11.345452543844322 13.463410489212919 risk_southeast_senegal:burn_2005_2014 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30702 EPSG:3857:17 60588 61019 60715 61405 EPSG:3857:18 121176 122039 121431 122810 EPSG:3857:19 242353 244079 242863 245620 EPSG:3857:20 484707 488158 485726 491241 EPSG:3857:21 969414 976316 971453 982483 EPSG:3857:22 1938828 1952633 1942907 1964967 EPSG:3857:23 3877656 3905266 3885814 3929935 EPSG:3857:24 7755312 7810533 7771629 7859871 EPSG:3857:25 15510624 15621067 15543259 15719743 EPSG:3857:26 31021249 31242134 31086518 31439486 EPSG:3857:27 62042499 62484268 62173036 62878972 EPSG:3857:28 124084999 124968536 124346072 125757945 EPSG:3857:29 248169998 249937073 248692145 251515890 EPSG:3857:30 496339997 499874147 497384290 503031781 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30702 EPSG:4326:16 27866 28286 60715 61405 EPSG:4326:17 55732 56573 121431 122810 EPSG:4326:18 111464 113146 242863 245620 EPSG:4326:19 222928 226293 485726 491241 EPSG:4326:20 445857 452586 971453 982483 EPSG:4326:21 891715 905173 1942907 1964967 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30702 EPSG:3857:17 60588 61019 60715 61405 EPSG:3857:18 121176 122039 121431 122810 EPSG:3857:19 242353 244079 242863 245620 EPSG:3857:20 484707 488158 485726 491241 EPSG:3857:21 969414 976316 971453 982483 EPSG:3857:22 1938828 1952633 1942907 1964967 EPSG:3857:23 3877656 3905266 3885814 3929935 EPSG:3857:24 7755312 7810533 7771629 7859871 EPSG:3857:25 15510624 15621067 15543259 15719743 EPSG:3857:26 31021249 31242134 31086518 31439486 EPSG:3857:27 62042499 62484268 62173036 62878972 EPSG:3857:28 124084999 124968536 124346072 125757945 EPSG:3857:29 248169998 249937073 248692145 251515890 EPSG:3857:30 496339997 499874147 497384290 503031781 Automn precipitations change (%) for the period 2040 - 2059 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_son_MIDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 tsm_col_zaragoza_20211025 -74.8651063820499 7.579889039548307 -74.7899249680916 7.640072688469066 rs_for_asgm:tsm_col_zaragoza_20211025 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7496 7502 9569 9576 EPSG:4326:15 14993 15004 19139 19152 EPSG:4326:16 29986 30008 38278 38305 EPSG:4326:17 59972 60016 76556 76611 EPSG:4326:18 119945 120032 153113 153223 EPSG:4326:19 239890 240065 306227 306446 EPSG:4326:20 479781 480131 612455 612893 EPSG:4326:21 959562 960263 1224910 1225786 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 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EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 3 8 8 EPSG:4326:4 5 6 16 17 EPSG:4326:5 11 13 32 34 EPSG:4326:6 23 27 64 69 EPSG:4326:7 47 55 128 139 EPSG:4326:8 94 111 256 278 EPSG:4326:9 189 222 512 557 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EPSG:900913:18 113439 122494 131193 142723 EPSG:900913:19 226879 244988 262387 285446 EPSG:900913:20 453758 489977 524775 570893 EPSG:900913:21 907517 979954 1049551 1141787 EPSG:900913:22 1815034 1959909 2099103 2283575 EPSG:900913:23 3630068 3919818 4198207 4567150 EPSG:900913:24 7260136 7839637 8396414 9134300 EPSG:900913:25 14520272 15679275 16792828 18268601 EPSG:900913:26 29040545 31358551 33585656 36537203 EPSG:900913:27 58081090 62717103 67171312 73074407 EPSG:900913:28 116162180 125434207 134342625 146148814 EPSG:900913:29 232324360 250868415 268685250 292297628 EPSG:900913:30 464648721 501736831 537370500 584595256 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 Average year temperature (1991-2022) Average year temperature in °Celsius across the period 1991-2022. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_22_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2008 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2008 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2009 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2009 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2006 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2006 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2007 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2007 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2004 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2004 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tsunami/Sea grasses at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_sea6_13_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2005 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2005 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Burned area 2003 This layer was produced by UNEP/GRID-Geneva in December 2023. -180.0 -90.0 180.0 90.0 unccd:barea2003 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Physical Exposure To Tsunamis This dataset includes an estimation of the annual physical exposure to tsunamis. It is based on three sources: 1) a comprehensive list of reports and scientific papers compiled and utilized in producing tsunami hazard maps as well as finding return periods of future events; 2) applying numerical tsunami models and zooming on selected areas; and 3) a population grid for the year 2010 (provided by LandScanTM Global Population Database, Oak Ridge National Laboratory, Oak Ridge, USA). The unit of reference is the expected average annual population (2010 as the year of reference) exposed (inhabitants). This product was designed by the International Centre for Geohazards (NGI) for the Global Assessment Report on Risk Reduction (GAR). The dataset was was modelled using global data. Credit: GIS processing International Centre for Geohazards (NGI) -180.0 -90.0 179.99999999985602 83.99999999993042 wesr_risk:ts_physexp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 502 16383 0 16383 EPSG:3857:15 1005 32767 0 32767 EPSG:3857:16 2011 65535 0 65535 EPSG:3857:17 4023 131071 0 131071 EPSG:3857:18 8047 262143 0 262143 EPSG:3857:19 16095 524287 0 524287 EPSG:3857:20 32191 1048575 0 1048575 EPSG:3857:21 64382 2097151 0 2097151 EPSG:3857:22 128764 4194303 0 4194304 EPSG:3857:23 257528 8388607 0 8388608 EPSG:3857:24 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16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 Forest Integrity Index (FI) - Asia The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> 90.32202306186224 -11.768033998374744 153.42801388207823 25.91760211162399 MapX_UNDP:asiaFI image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 3 3 EPSG:3857:3 3 4 6 7 EPSG:3857:4 6 8 12 14 EPSG:3857:5 13 17 24 29 EPSG:3857:6 27 34 48 59 EPSG:3857:7 54 68 96 118 EPSG:3857:8 108 136 192 237 EPSG:3857:9 217 272 384 474 EPSG:3857:10 435 545 768 948 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EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 520 592 592 EPSG:3857:11 1041 1041 1184 1184 EPSG:3857:12 2082 2083 2368 2368 EPSG:3857:13 4165 4166 4736 4737 EPSG:3857:14 8331 8332 9473 9474 EPSG:3857:15 16663 16664 18947 18949 EPSG:3857:16 33326 33328 37895 37898 EPSG:3857:17 66652 66656 75791 75796 EPSG:3857:18 133304 133312 151582 151592 EPSG:3857:19 266608 266625 303165 303185 EPSG:3857:20 533217 533250 606330 606371 EPSG:3857:21 1066435 1066501 1212660 1212743 EPSG:3857:22 2132870 2133003 2425321 2425486 EPSG:3857:23 4265740 4266007 4850642 4850973 EPSG:3857:24 8531481 8532014 9701284 9701947 EPSG:3857:25 17062963 17064028 19402568 19403894 EPSG:3857:26 34125926 34128057 38805137 38807789 EPSG:3857:27 68251853 68256114 77610274 77615579 EPSG:3857:28 136503706 136512228 155220549 155231158 EPSG:3857:29 273007413 273024457 310441098 310462317 EPSG:3857:30 546014827 546048915 620882196 620924635 Tree cover fraction - 2019 (Copernicus) The layer shows the tree cover expressed as a percentage of ground cover per pixel. It is sourced from the Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2019: Globe (https://zenodo.org/record/3939050#.X33YymgzaUk). Please visit https://land.copernicus.eu/global/products/lc for more information. Credits: Buchhorn, M.; Smets, B.; Bertels, L.; Lesiv, M.; Tsendbazar, N.-E.; Masiliunas, D.; Linlin, L.; Herold, M.; Fritz, S. (2020). Copernicus Global Land Service: Land Cover 100m: Collection 3: epoch <2019>: Globe (Version V3.0.1) [Data set]. Zenodo. DOI: 10.5281/zenodo.3939050 -180.0 -59.999999999999545 179.9999999999988 80.0 wesr_biodiversity:Copernicus_PROBAV_LC100_global_v3.0.1_2019-nrt_Tree-CoverFraction-layer_EPSG-4326_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1839 11626 0 16383 EPSG:3857:15 3678 23252 0 32767 EPSG:3857:16 7357 46504 0 65535 EPSG:3857:17 14714 93008 0 131071 EPSG:3857:18 29428 186017 0 262143 EPSG:3857:19 58856 372034 0 524287 EPSG:3857:20 117712 744069 0 1048575 EPSG:3857:21 235425 1488139 0 2097151 EPSG:3857:22 470850 2976279 0 4194304 EPSG:3857:23 941700 5952559 0 8388608 EPSG:3857:24 1883400 11905118 0 16777215 EPSG:3857:25 3766800 23810236 0 33554431 EPSG:3857:26 7533600 47620473 0 67108863 EPSG:3857:27 15067201 95240947 0 134217727 EPSG:3857:28 30134402 190481895 0 268435456 EPSG:3857:29 60268805 380963791 0 536870911 EPSG:3857:30 120537610 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 3 53 0 127 EPSG:4326:7 7 106 0 255 EPSG:4326:8 14 213 0 511 EPSG:4326:9 28 426 0 1023 EPSG:4326:10 56 853 0 2047 EPSG:4326:11 113 1706 0 4095 EPSG:4326:12 227 3413 0 8191 EPSG:4326:13 455 6826 0 16383 EPSG:4326:14 910 13653 0 32767 EPSG:4326:15 1820 27306 0 65535 EPSG:4326:16 3640 54613 0 131071 EPSG:4326:17 7281 109226 0 262143 EPSG:4326:18 14563 218453 0 524287 EPSG:4326:19 29127 436906 0 1048575 EPSG:4326:20 58254 873813 0 2097151 EPSG:4326:21 116508 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5813 0 8191 EPSG:3857:14 1839 11626 0 16383 EPSG:3857:15 3678 23252 0 32767 EPSG:3857:16 7357 46504 0 65535 EPSG:3857:17 14714 93008 0 131071 EPSG:3857:18 29428 186017 0 262143 EPSG:3857:19 58856 372034 0 524287 EPSG:3857:20 117712 744069 0 1048575 EPSG:3857:21 235425 1488139 0 2097152 EPSG:3857:22 470850 2976279 0 4194304 EPSG:3857:23 941700 5952559 0 8388607 EPSG:3857:24 1883400 11905118 0 16777215 EPSG:3857:25 3766800 23810236 0 33554431 EPSG:3857:26 7533600 47620473 0 67108863 EPSG:3857:27 15067201 95240947 0 134217728 EPSG:3857:28 30134402 190481895 0 268435455 EPSG:3857:29 60268805 380963791 0 536870911 EPSG:3857:30 120537610 761927583 0 1073741824 Average temperature of the 3 coldest months (1991-2020) Average temperature of the 3 coldest months per pixel in °Celsius across the period 1991-2020. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_20_3coldest_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Forest Fragmentation (2000) 1000m The fragmentation dataset classifies forested areas into several fragmentation classes using spatial pattern analysis, and includes effects of both deforestation and regrowth on forest fragmentation. Multiple variations of this dataset are available for the years 2000 and 2012, each making different assumptions about: the distance that fragmentation effects extend into forests (500 metres or 1000 metres); the canopy cover (%) that defines forest area (25 or 50%); and the minimum area (in hectares) of a fragment to be be considered a forest fragment (0, 1 or 5 ha). The map presented here shows effects extending 500 metres into forest interiors. This dataset has a 30-metre spatial resolution. Data derived from: Hansen, M.C., et al. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342, 850–853. 10.1126/science.1244693 Created as part of the GEF-funded Global Support to Sixth National Report Project in collaboration with the NASA-funded Forest Integrity Project. -119.36170706306382 -34.213866389533806 179.99995545035347 30.001378 MapX_UNDP_nd:frag_2000_1000_25_0 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 13 19 5 31 EPSG:3857:6 26 38 10 63 EPSG:3857:7 52 76 21 127 EPSG:3857:8 105 153 43 255 EPSG:3857:9 211 307 86 511 EPSG:3857:10 422 615 172 1023 EPSG:3857:11 844 1231 344 2047 EPSG:3857:12 1689 2462 689 4095 EPSG:3857:13 3379 4925 1379 8191 EPSG:3857:14 6759 9850 2759 16383 EPSG:3857:15 13519 19701 5519 32767 EPSG:3857:16 27038 39403 11038 65535 EPSG:3857:17 54076 78806 22077 131071 EPSG:3857:18 108152 157613 44155 262143 EPSG:3857:19 216305 315227 88310 524287 EPSG:3857:20 432611 630455 176621 1048575 EPSG:3857:21 865223 1260910 353243 2097151 EPSG:3857:22 1730447 2521821 706487 4194303 EPSG:3857:23 3460894 5043642 1412974 8388606 EPSG:3857:24 6921789 10087284 2825949 16777213 EPSG:3857:25 13843578 20174568 5651898 33554427 EPSG:3857:26 27687157 40349137 11303797 67108855 EPSG:3857:27 55374314 80698274 22607594 134217711 EPSG:3857:28 110748628 161396549 45215188 268435422 EPSG:3857:29 221497257 322793098 90430376 536870845 EPSG:3857:30 442994514 645586197 180860753 1073741691 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 1 2 1 7 EPSG:4326:3 2 5 2 15 EPSG:4326:4 5 11 5 31 EPSG:4326:5 10 22 10 63 EPSG:4326:6 21 44 21 127 EPSG:4326:7 42 88 43 255 EPSG:4326:8 85 176 86 511 EPSG:4326:9 170 353 172 1023 EPSG:4326:10 341 706 344 2047 EPSG:4326:11 682 1413 689 4095 EPSG:4326:12 1365 2826 1379 8191 EPSG:4326:13 2730 5653 2759 16383 EPSG:4326:14 5461 11306 5519 32767 EPSG:4326:15 10922 22612 11038 65535 EPSG:4326:16 21844 45224 22077 131071 EPSG:4326:17 43689 90449 44155 262143 EPSG:4326:18 87379 180899 88310 524287 EPSG:4326:19 174758 361799 176621 1048575 EPSG:4326:20 349517 723598 353243 2097151 EPSG:4326:21 699034 1447196 706487 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 13 19 5 31 EPSG:3857:6 26 38 10 63 EPSG:3857:7 52 76 21 127 EPSG:3857:8 105 153 43 255 EPSG:3857:9 211 307 86 511 EPSG:3857:10 422 615 172 1023 EPSG:3857:11 844 1231 344 2047 EPSG:3857:12 1689 2462 689 4095 EPSG:3857:13 3379 4925 1379 8191 EPSG:3857:14 6759 9850 2759 16383 EPSG:3857:15 13519 19701 5519 32767 EPSG:3857:16 27038 39403 11038 65535 EPSG:3857:17 54076 78806 22077 131071 EPSG:3857:18 108152 157613 44155 262143 EPSG:3857:19 216305 315227 88310 524287 EPSG:3857:20 432611 630455 176621 1048575 EPSG:3857:21 865223 1260910 353243 2097151 EPSG:3857:22 1730447 2521821 706487 4194303 EPSG:3857:23 3460894 5043642 1412974 8388606 EPSG:3857:24 6921789 10087284 2825949 16777213 EPSG:3857:25 13843578 20174568 5651898 33554427 EPSG:3857:26 27687157 40349137 11303797 67108855 EPSG:3857:27 55374314 80698274 22607594 134217711 EPSG:3857:28 110748628 161396549 45215188 268435422 EPSG:3857:29 221497257 322793098 90430376 536870845 EPSG:3857:30 442994514 645586197 180860753 1073741691 Aboveground live woody carbon density change (2003-2014) Aboveground live woody carbon density change (2003-2014): The data provided here are the result of a time-series analysis of carbon density change between 2003-2014 spanning tropical America, Africa, and Asia (23.45 N lat.-23.45 S lat.). For further information about these results please see the associated journal article (Baccini et al. 2017, Science). Spatial (raster) and tabular data described in the journal article are available for download from the links below. Data can be visualized at www.thecarbonsource.org. The visualization includes the ability to select a given change pixel (loss or gain) and display the trajectory of carbon density during the 2003-2014 study period. Raster Data Information: The carbon density change data are divided into three regions: America, Africa, and Asia. For each region there are two raster (.tif) files representing: 1) carbon density net gain, and 2) carbon density net loss. The value of each pixel (463 x 463 m) represents the total net carbon density change (Mg/ha) over the period 2003-2014. Only pixels exhibiting statistical significance at the 95% level are reported. All raster files are in the original MODIS sinusoidal projection. Baccini, A., W. Walker, L. Carvalho, M. Farina, D. Sulla-Menashe, R.A. Houghton. 2017. Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science 2017 Vol. 358, Issue 6360, pp. 230-234 DOI:10.1126/science.aam5962. Data available online from www.thecarbonsource.org. -119.85892985444444 -23.402497460000003 170.00430119527778 23.400000000555554 MapX_UNDP_nd:baccini_carbon_change_global_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 13 18 5 31 EPSG:3857:6 27 36 10 62 EPSG:3857:7 55 72 21 124 EPSG:3857:8 110 145 42 248 EPSG:3857:9 221 290 85 497 EPSG:3857:10 443 580 171 995 EPSG:3857:11 887 1160 342 1991 EPSG:3857:12 1774 2321 684 3982 EPSG:3857:13 3548 4643 1368 7964 EPSG:3857:14 7096 9287 2737 15929 EPSG:3857:15 14192 18575 5474 31858 EPSG:3857:16 28384 37151 10948 63716 EPSG:3857:17 56769 74303 21896 127432 EPSG:3857:18 113538 148607 43793 254865 EPSG:3857:19 227076 297215 87586 509730 EPSG:3857:20 454152 594431 175173 1019461 EPSG:3857:21 908305 1188862 350347 2038922 EPSG:3857:22 1816611 2377724 700694 4077845 EPSG:3857:23 3633222 4755449 1401388 8155691 EPSG:3857:24 7266444 9510898 2802777 16311382 EPSG:3857:25 14532888 19021796 5605554 32622765 EPSG:3857:26 29065777 38043593 11211108 65245530 EPSG:3857:27 58131555 76087187 22422216 130491061 EPSG:3857:28 116263110 152174374 44844432 260982122 EPSG:3857:29 232526220 304348749 89688864 521964245 EPSG:3857:30 465052441 608697498 179377728 1043928491 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 1 2 1 7 EPSG:4326:3 2 5 2 15 EPSG:4326:4 5 10 5 31 EPSG:4326:5 11 20 10 62 EPSG:4326:6 23 40 21 124 EPSG:4326:7 47 80 42 248 EPSG:4326:8 94 161 85 497 EPSG:4326:9 189 322 171 995 EPSG:4326:10 378 645 342 1991 EPSG:4326:11 757 1290 684 3982 EPSG:4326:12 1515 2580 1368 7964 EPSG:4326:13 3031 5161 2737 15929 EPSG:4326:14 6062 10322 5474 31858 EPSG:4326:15 12124 20644 10948 63716 EPSG:4326:16 24248 41288 21896 127432 EPSG:4326:17 48496 82577 43793 254865 EPSG:4326:18 96993 165154 87586 509730 EPSG:4326:19 193986 330308 175173 1019461 EPSG:4326:20 387973 660617 350347 2038922 EPSG:4326:21 775946 1321234 700694 4077845 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 13 18 5 31 EPSG:3857:6 27 36 10 62 EPSG:3857:7 55 72 21 124 EPSG:3857:8 110 145 42 248 EPSG:3857:9 221 290 85 497 EPSG:3857:10 443 580 171 995 EPSG:3857:11 887 1160 342 1991 EPSG:3857:12 1774 2321 684 3982 EPSG:3857:13 3548 4643 1368 7964 EPSG:3857:14 7096 9287 2737 15929 EPSG:3857:15 14192 18575 5474 31858 EPSG:3857:16 28384 37151 10948 63716 EPSG:3857:17 56769 74303 21896 127432 EPSG:3857:18 113538 148607 43793 254865 EPSG:3857:19 227076 297215 87586 509730 EPSG:3857:20 454152 594431 175173 1019461 EPSG:3857:21 908305 1188862 350347 2038922 EPSG:3857:22 1816611 2377724 700694 4077845 EPSG:3857:23 3633222 4755449 1401388 8155691 EPSG:3857:24 7266444 9510898 2802777 16311382 EPSG:3857:25 14532888 19021796 5605554 32622765 EPSG:3857:26 29065777 38043593 11211108 65245530 EPSG:3857:27 58131555 76087187 22422216 130491061 EPSG:3857:28 116263110 152174374 44844432 260982122 EPSG:3857:29 232526220 304348749 89688864 521964245 EPSG:3857:30 465052441 608697498 179377728 1043928491 Kerala SWBD SRTM Water Body Data for Kerala State 74.85874450133333 8.253748373333334 77.49289430933334 12.84288566933333 ECO-DRR:Kerala_SWBD image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 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EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185582 187500 EPSG:4326:18 112368 119051 371164 375001 EPSG:4326:19 224736 238103 742329 750002 EPSG:4326:20 449472 476206 1484659 1500004 EPSG:4326:21 898945 952412 2969319 3000009 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892505 4001309 5938639 6000019 EPSG:3857:24 7785010 8002618 11877278 12000038 EPSG:3857:25 15570020 16005236 23754556 24000077 EPSG:3857:26 31140041 32010472 47509113 48000154 EPSG:3857:27 62280082 64020945 95018226 96000309 EPSG:3857:28 124560164 128041890 190036453 192000618 EPSG:3857:29 249120329 256083780 380072907 384001236 EPSG:3857:30 498240658 512167560 760145814 768002472 gpcc_precipitation_quantile_12month_19912020 Precipitation quantiles are based on the twelve months aggregated GPCC Monitoring Product and First Guess Monthly product. The baseline period is 1991-2020, using Full Data Monthly in its latest version. Quality controlled rain gauge (in situ) data are used and the quality control protocol depends on the data set. The percentiles are not calculated for those grid cells, where the precipitation total aggregated in the reference period is below ten millimetres. -180.0 -90.0 180.0 90.0 wmo:gpcc_precipitation_quantile_12month_19912020 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tsunami/Mangroves at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_man6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Mean temperatures 2012 - Central African Republic Mean observed temperatures in 2012 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2012_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from Max Planck Institute for Meteorology, Germany, ECHAM5 / MPI OM Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_mpi_echam5_5km_2041-2060_debiasedmean_tas_av12mon_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Land Surface Temperature in Dakar Senegal (2025) This layer shows the estimated temperature at a 100m resolution derived from Landsat 8 imagery. The temporal statistics from January 2025 to June 2025 have been aggregated and invalide values were filtered. This layer serves as as a base for the project, identifying areas that are warmer and susceptible to indicate waste decomposition. This layer serves as a base for the broader project, identifying areas that are warmer and potentially indicate the susceptibility of illegal waste. -17.55611637429027 14.634522359756563 -17.19121319151092 14.86324689854362 dakar_waste:LST_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 463 EPSG:3857:11 938 939 924 926 EPSG:3857:12 1876 1879 1848 1852 EPSG:3857:13 3753 3759 3696 3704 EPSG:3857:14 7507 7518 7393 7409 EPSG:3857:15 15015 15037 14786 14819 EPSG:3857:16 30031 30074 29572 29638 EPSG:3857:17 60062 60148 59144 59276 EPSG:3857:18 120125 120297 118288 118553 EPSG:3857:19 240250 240595 236576 237107 EPSG:3857:20 480501 481190 473152 474214 EPSG:3857:21 961003 962381 946304 948429 EPSG:3857:22 1922007 1924762 1892608 1896859 EPSG:3857:23 3844014 3849525 3785216 3793719 EPSG:3857:24 7688028 7699050 7570433 7587439 EPSG:3857:25 15376056 15398101 15140867 15174878 EPSG:3857:26 30752112 30796203 30281734 30349757 EPSG:3857:27 61504225 61592406 60563469 60699515 EPSG:3857:28 123008451 123184812 121126938 121399030 EPSG:3857:29 246016903 246369624 242253877 242798060 EPSG:3857:30 492033806 492739248 484507755 485596121 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 463 EPSG:4326:10 427 428 924 926 EPSG:4326:11 854 857 1848 1852 EPSG:4326:12 1709 1714 3696 3704 EPSG:4326:13 3419 3429 7393 7409 EPSG:4326:14 6839 6859 14786 14819 EPSG:4326:15 13678 13719 29572 29638 EPSG:4326:16 27356 27439 59144 59276 EPSG:4326:17 54712 54879 118288 118553 EPSG:4326:18 109425 109758 236576 237107 EPSG:4326:19 218851 219517 473152 474214 EPSG:4326:20 437703 439035 946304 948429 EPSG:4326:21 875406 878071 1892608 1896859 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 463 EPSG:3857:11 938 939 924 926 EPSG:3857:12 1876 1879 1848 1852 EPSG:3857:13 3753 3759 3696 3704 EPSG:3857:14 7507 7518 7393 7409 EPSG:3857:15 15015 15037 14786 14819 EPSG:3857:16 30031 30074 29572 29638 EPSG:3857:17 60062 60148 59144 59276 EPSG:3857:18 120125 120297 118288 118553 EPSG:3857:19 240250 240595 236576 237107 EPSG:3857:20 480501 481190 473152 474214 EPSG:3857:21 961003 962381 946304 948429 EPSG:3857:22 1922007 1924762 1892608 1896859 EPSG:3857:23 3844014 3849525 3785216 3793719 EPSG:3857:24 7688028 7699050 7570433 7587439 EPSG:3857:25 15376056 15398101 15140867 15174878 EPSG:3857:26 30752112 30796203 30281734 30349757 EPSG:3857:27 61504225 61592406 60563469 60699515 EPSG:3857:28 123008451 123184812 121126938 121399030 EPSG:3857:29 246016903 246369624 242253877 242798060 EPSG:3857:30 492033806 492739248 484507755 485596121 Forest Fragmentation (2000) 500m The fragmentation dataset classifies forested areas into several fragmentation classes using spatial pattern analysis, and includes effects of both deforestation and regrowth on forest fragmentation. Multiple variations of this dataset are available for the years 2000 and 2012, each making different assumptions about: the distance that fragmentation effects extend into forests (500 metres or 1000 metres); the canopy cover (%) that defines forest area (25 or 50%); and the minimum area (in hectares) of a fragment to be be considered a forest fragment (0, 1 or 5 ha). The map presented here shows effects extending 500 metres into forest interiors. This dataset has a 30-metre spatial resolution. Data derived from: Hansen, M.C., et al. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342, 850–853. 10.1126/science.1244693 Created as part of the GEF-funded Global Support to Sixth National Report Project in collaboration with the NASA-funded Forest Integrity Project. -119.36170706306382 -34.213866389533806 179.99995545035347 30.001378 MapX_UNDP_nd:frag_2000_500_25_0 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 3 4 1 7 EPSG:3857:4 6 9 2 15 EPSG:3857:5 13 19 5 31 EPSG:3857:6 26 38 10 63 EPSG:3857:7 52 76 21 127 EPSG:3857:8 105 153 43 255 EPSG:3857:9 211 307 86 511 EPSG:3857:10 422 615 172 1023 EPSG:3857:11 844 1231 344 2047 EPSG:3857:12 1689 2462 689 4095 EPSG:3857:13 3379 4925 1379 8191 EPSG:3857:14 6759 9850 2759 16383 EPSG:3857:15 13519 19701 5519 32767 EPSG:3857:16 27038 39403 11038 65535 EPSG:3857:17 54076 78806 22077 131071 EPSG:3857:18 108152 157613 44155 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EPSG:3857:23 3460894 5043642 1412974 8388606 EPSG:3857:24 6921789 10087284 2825949 16777213 EPSG:3857:25 13843578 20174568 5651898 33554427 EPSG:3857:26 27687157 40349137 11303797 67108855 EPSG:3857:27 55374314 80698274 22607594 134217711 EPSG:3857:28 110748628 161396549 45215188 268435422 EPSG:3857:29 221497257 322793098 90430376 536870845 EPSG:3857:30 442994514 645586197 180860753 1073741691 MudugLoss Georefenced Somalia 46.10560211084111 3.8984477246665126 50.10348179017403 7.956060931758941 MAPX_nd:som__MudugLoss_georef image/png image/vnd.jpeg-png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 10 10 EPSG:4326:4 7 7 20 20 EPSG:4326:5 14 15 40 40 EPSG:4326:6 29 30 80 81 EPSG:4326:7 58 61 160 163 EPSG:4326:8 116 122 321 327 EPSG:4326:9 233 244 643 654 EPSG:4326:10 466 489 1286 1309 EPSG:4326:11 933 979 2572 2618 EPSG:4326:12 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329290 335112 EPSG:900913:20 501039 512924 658580 670224 EPSG:900913:21 1002078 1025848 1317160 1340449 EPSG:900913:22 2004157 2051696 2634321 2680899 EPSG:900913:23 4008315 4103393 5268642 5361799 EPSG:900913:24 8016631 8206786 10537284 10723599 EPSG:900913:25 16033262 16413573 21074569 21447198 EPSG:900913:26 32066525 32827147 42149139 42894397 EPSG:900913:27 64133050 65654294 84298278 85788795 EPSG:900913:28 128266101 131308589 168596556 171577591 EPSG:900913:29 256532203 262617178 337193113 343155183 EPSG:900913:30 513064406 525234356 674386226 686310367 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from Meteo-France, Centre National de Recherches Meteorologiques, CM3 Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_cnrm_cm3_5km_2041-2060_debiasedmean_tas_av_12month_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Precipitation Anomalies Oct_2017_(mm) - CHIRPS https://earlywarning.usgs.gov/fews/ewx/index.html?region=af -19.125063083055668 -35.37238257858172 52.6296893492118 38.256795423617206 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346922537 EPSG:900913:30 413199317 649794003 479828189 693845074 site_5002_Sentinel2x1000int 31.324122782194696 45.97193313327075 35.46956590263507 47.821654606374786 hotspots:site_5002_Sentinel2x1000int image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 2 4 4 EPSG:3857:4 5 5 9 9 EPSG:3857:5 11 11 18 19 EPSG:3857:6 22 22 37 38 EPSG:3857:7 44 45 75 76 EPSG:3857:8 89 91 150 153 EPSG:3857:9 178 182 300 306 EPSG:3857:10 356 364 601 612 EPSG:3857:11 713 728 1202 1225 EPSG:3857:12 1426 1457 2404 2451 EPSG:3857:13 2853 2915 4808 4903 EPSG:3857:14 5707 5830 9617 9806 EPSG:3857:15 11414 11661 19235 19612 EPSG:3857:16 22829 23322 38470 39225 EPSG:3857:17 45659 46645 76940 78450 EPSG:3857:18 91318 93290 153881 156900 EPSG:3857:19 182637 186580 307763 313800 EPSG:3857:20 365275 373160 615526 627600 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11688804 11941149 19696835 20083219 EPSG:3857:26 23377608 23882298 39393671 40166438 EPSG:3857:27 46755216 47764597 78787343 80332876 EPSG:3857:28 93510433 95529194 157574686 160665753 EPSG:3857:29 187020866 191058388 315149373 321331506 EPSG:3857:30 374041732 382116777 630298747 642663013 Human footprint 2010 Brooke A. Williams, Oscar Venter, James R. Allan, Scott C. Atkinson, Jose A. Rehbein, Michelle S. Ward, Moreno Di Marco, Hedley S. Grantham, Jamison Ervin, Scott Goetz, Andrew J. Hansen, Patrick Jantz, Rajeev Pillay, Susana Rodríguez-Buriticá, Christina Supples, Anne L. S. Virnig, James E.M. Watson. (2020). Change in terrestrial human footprint drives continued loss of intact ecosystems. OneEarth. http://dx.doi.org/10.2139/ssrn.3600547 -179.99999995447251 -65.25013301721049 179.99661098079287 89.89762321520959 wesr_biodiversity:hfp2010_merisINT image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12147 0 16383 EPSG:3857:15 0 24294 0 32767 EPSG:3857:16 0 48589 0 65535 EPSG:3857:17 0 97178 0 131070 EPSG:3857:18 0 194356 0 262141 EPSG:3857:19 0 388713 0 524283 EPSG:3857:20 0 777426 0 1048566 EPSG:3857:21 0 1554852 0 2097132 EPSG:3857:22 -1 3109705 0 4194264 EPSG:3857:23 -1 6219410 0 8388529 EPSG:3857:24 0 12438820 0 16777058 EPSG:3857:25 0 24877640 0 33554116 EPSG:3857:26 0 49755280 0 67108232 EPSG:3857:27 0 99510561 0 134216464 EPSG:3857:28 -1 199021122 0 268432928 EPSG:3857:29 0 398042245 0 536865857 EPSG:3857:30 0 796084491 0 1073731715 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 55 0 127 EPSG:4326:7 0 110 0 255 EPSG:4326:8 0 220 0 511 EPSG:4326:9 0 441 0 1023 EPSG:4326:10 0 883 0 2047 EPSG:4326:11 1 1766 0 4095 EPSG:4326:12 2 3532 0 8191 EPSG:4326:13 4 7065 0 16383 EPSG:4326:14 9 14131 0 32767 EPSG:4326:15 18 28262 0 65535 EPSG:4326:16 37 56524 0 131070 EPSG:4326:17 74 113049 0 262141 EPSG:4326:18 149 226099 0 524283 EPSG:4326:19 298 452198 0 1048566 EPSG:4326:20 596 904397 0 2097132 EPSG:4326:21 1192 1808795 0 4194264 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12147 0 16383 EPSG:3857:15 0 24294 0 32767 EPSG:3857:16 0 48589 0 65535 EPSG:3857:17 0 97178 0 131070 EPSG:3857:18 0 194356 0 262141 EPSG:3857:19 0 388713 0 524283 EPSG:3857:20 0 777426 0 1048566 EPSG:3857:21 -1 1554852 0 2097132 EPSG:3857:22 -1 3109705 0 4194264 EPSG:3857:23 0 6219410 0 8388529 EPSG:3857:24 0 12438820 0 16777058 EPSG:3857:25 0 24877640 0 33554116 EPSG:3857:26 0 49755280 0 67108232 EPSG:3857:27 -1 99510561 0 134216464 EPSG:3857:28 0 199021122 0 268432928 EPSG:3857:29 0 398042245 0 536865857 EPSG:3857:30 -1 796084491 0 1073731715 Forest Structual Condition Index (SCI) - Asia The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> 90.32202306186224 -11.768033998374701 153.4280138820783 25.91760211162399 MapX_UNDP:asiaSCI image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 3 3 EPSG:3857:3 3 4 6 7 EPSG:3857:4 6 8 12 14 EPSG:3857:5 13 17 24 29 EPSG:3857:6 27 34 48 59 EPSG:3857:7 54 68 96 118 EPSG:3857:8 108 136 192 237 EPSG:3857:9 217 272 384 474 EPSG:3857:10 435 545 768 948 EPSG:3857:11 871 1091 1537 1896 EPSG:3857:12 1742 2182 3075 3793 EPSG:3857:13 3485 4365 6151 7587 EPSG:3857:14 6970 8731 12302 15174 EPSG:3857:15 13940 17462 24605 30349 EPSG:3857:16 27880 34925 49210 60698 EPSG:3857:17 55760 69851 98421 121397 EPSG:3857:18 111520 139702 196842 242794 EPSG:3857:19 223041 279404 393684 485589 EPSG:3857:20 446082 558808 787369 971179 EPSG:3857:21 892165 1117616 1574739 1942358 EPSG:3857:22 1784331 2235233 3149479 3884717 EPSG:3857:23 3568663 4470467 6298959 7769435 EPSG:3857:24 7137327 8940935 12597919 15538871 EPSG:3857:25 14274655 17881870 25195838 31077743 EPSG:3857:26 28549311 35763741 50391677 62155486 EPSG:3857:27 57098623 71527482 100783354 124310973 EPSG:3857:28 114197246 143054964 201566709 248621947 EPSG:3857:29 228394492 286109928 403133419 497243894 EPSG:3857:30 456788984 572219857 806266839 994487788 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 3 3 EPSG:4326:2 1 2 6 7 EPSG:4326:3 2 4 12 14 EPSG:4326:4 5 9 24 29 EPSG:4326:5 11 18 48 59 EPSG:4326:6 22 36 96 118 EPSG:4326:7 45 72 192 237 EPSG:4326:8 91 144 384 474 EPSG:4326:9 182 289 768 948 EPSG:4326:10 364 578 1537 1896 EPSG:4326:11 729 1157 3075 3793 EPSG:4326:12 1458 2315 6151 7587 EPSG:4326:13 2916 4631 12302 15174 EPSG:4326:14 5832 9263 24605 30349 EPSG:4326:15 11665 18526 49210 60698 EPSG:4326:16 23331 37052 98421 121397 EPSG:4326:17 46663 74105 196842 242794 EPSG:4326:18 93326 148210 393684 485589 EPSG:4326:19 186653 296420 787369 971179 EPSG:4326:20 373307 592841 1574739 1942358 EPSG:4326:21 746614 1185683 3149479 3884717 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 3 3 EPSG:3857:3 3 4 6 7 EPSG:3857:4 6 8 12 14 EPSG:3857:5 13 17 24 29 EPSG:3857:6 27 34 48 59 EPSG:3857:7 54 68 96 118 EPSG:3857:8 108 136 192 237 EPSG:3857:9 217 272 384 474 EPSG:3857:10 435 545 768 948 EPSG:3857:11 871 1091 1537 1896 EPSG:3857:12 1742 2182 3075 3793 EPSG:3857:13 3485 4365 6151 7587 EPSG:3857:14 6970 8731 12302 15174 EPSG:3857:15 13940 17462 24605 30349 EPSG:3857:16 27880 34925 49210 60698 EPSG:3857:17 55760 69851 98421 121397 EPSG:3857:18 111520 139702 196842 242794 EPSG:3857:19 223041 279404 393684 485589 EPSG:3857:20 446082 558808 787369 971179 EPSG:3857:21 892165 1117616 1574739 1942358 EPSG:3857:22 1784331 2235233 3149479 3884717 EPSG:3857:23 3568663 4470467 6298959 7769435 EPSG:3857:24 7137327 8940935 12597919 15538871 EPSG:3857:25 14274655 17881870 25195838 31077743 EPSG:3857:26 28549311 35763741 50391677 62155486 EPSG:3857:27 57098623 71527482 100783354 124310973 EPSG:3857:28 114197246 143054964 201566709 248621947 EPSG:3857:29 228394492 286109928 403133419 497243894 EPSG:3857:30 456788984 572219857 806266839 994487788 Yearly emissions of CO2 (short cycle organic Carbon) - 2010 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -55.59999999999239 179.99999999997954 78.3 wesr_climat:v60_CO2_org_short-cycle_C_2010_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 10 0 15 EPSG:3857:5 4 21 0 31 EPSG:3857:6 8 43 0 63 EPSG:3857:7 17 87 0 127 EPSG:3857:8 35 175 0 255 EPSG:3857:9 70 351 0 511 EPSG:3857:10 140 703 0 1023 EPSG:3857:11 281 1406 0 2047 EPSG:3857:12 562 2812 0 4095 EPSG:3857:13 1125 5624 0 8191 EPSG:3857:14 2251 11249 0 16383 EPSG:3857:15 4502 22499 0 32767 EPSG:3857:16 9004 44998 0 65535 EPSG:3857:17 18008 89997 0 131071 EPSG:3857:18 36017 179995 0 262143 EPSG:3857:19 72035 359991 0 524287 EPSG:3857:20 144071 719983 0 1048575 EPSG:3857:21 288142 1439967 0 2097151 EPSG:3857:22 576284 2879934 0 4194304 EPSG:3857:23 1152569 5759868 0 8388608 EPSG:3857:24 2305138 11519737 0 16777215 EPSG:3857:25 4610277 23039475 0 33554431 EPSG:3857:26 9220555 46078951 0 67108863 EPSG:3857:27 18441111 92157902 0 134217727 EPSG:3857:28 36882223 184315805 0 268435456 EPSG:3857:29 73764447 368631610 0 536870911 EPSG:3857:30 147528894 737263220 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 0 31 EPSG:4326:5 2 25 0 63 EPSG:4326:6 4 51 0 127 EPSG:4326:7 8 103 0 255 EPSG:4326:8 16 207 0 511 EPSG:4326:9 33 414 0 1023 EPSG:4326:10 66 828 0 2047 EPSG:4326:11 133 1656 0 4095 EPSG:4326:12 266 3313 0 8191 EPSG:4326:13 532 6626 0 16383 EPSG:4326:14 1064 13252 0 32767 EPSG:4326:15 2129 26505 0 65535 EPSG:4326:16 4259 53011 0 131071 EPSG:4326:17 8519 106022 0 262143 EPSG:4326:18 17039 212045 0 524287 EPSG:4326:19 34078 424090 0 1048575 EPSG:4326:20 68157 848181 0 2097151 EPSG:4326:21 136314 1696362 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 10 0 15 EPSG:3857:5 4 21 0 31 EPSG:3857:6 8 43 0 63 EPSG:3857:7 17 87 0 127 EPSG:3857:8 35 175 0 255 EPSG:3857:9 70 351 0 511 EPSG:3857:10 140 703 0 1023 EPSG:3857:11 281 1406 0 2047 EPSG:3857:12 562 2812 0 4095 EPSG:3857:13 1125 5624 0 8191 EPSG:3857:14 2251 11249 0 16383 EPSG:3857:15 4502 22499 0 32767 EPSG:3857:16 9004 44998 0 65535 EPSG:3857:17 18008 89997 0 131071 EPSG:3857:18 36017 179995 0 262143 EPSG:3857:19 72035 359991 0 524287 EPSG:3857:20 144071 719983 0 1048575 EPSG:3857:21 288142 1439967 0 2097152 EPSG:3857:22 576284 2879934 0 4194304 EPSG:3857:23 1152569 5759868 0 8388607 EPSG:3857:24 2305138 11519737 0 16777215 EPSG:3857:25 4610277 23039475 0 33554431 EPSG:3857:26 9220555 46078951 0 67108863 EPSG:3857:27 18441111 92157902 0 134217728 EPSG:3857:28 36882223 184315805 0 268435455 EPSG:3857:29 73764447 368631610 0 536870911 EPSG:3857:30 147528894 737263220 0 1073741824 Forest total area in km2 -180.0 -90.0 180.0 90.0 ECO-DRR:forestkm2a_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 World Cities (Esri) -177.928436279297 -55.4569625854492 180.0 78.8649673461914 grid_data_core:city_esri image/png image/jpeg text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 3 51 0 127 EPSG:4326:7 7 103 1 255 EPSG:4326:8 15 206 2 511 EPSG:4326:9 31 413 5 1023 EPSG:4326:10 63 827 11 2047 EPSG:4326:11 126 1654 23 4095 EPSG:4326:12 253 3309 47 8191 EPSG:4326:13 506 6619 94 16383 EPSG:4326:14 1013 13239 188 32767 EPSG:4326:15 2027 26479 377 65535 EPSG:4326:16 4054 52959 754 131071 EPSG:4326:17 8108 105918 1508 262143 EPSG:4326:18 16216 211837 3016 524287 EPSG:4326:19 32433 423674 6033 1048575 EPSG:4326:20 64866 847348 12067 2097151 EPSG:4326:21 129732 1694696 24135 4194303 EPSG:900913 International Boundaries Coastalines Level 0 - UNGIWG International boundary resources are prepared by United Nations Cartographic Section. The 1:1million dataset derived initially from VMAP0 has been corrected to better reflect the cartographic practise of UN Cartographic Section. -180.0 -90.0 180.0 84.4950561523438 grid_data_core_pro:_2012_ungiwg_cst_ln_01 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 0 31 0 63 EPSG:4326:6 1 63 0 127 EPSG:4326:7 3 127 0 255 EPSG:4326:8 7 255 0 511 EPSG:4326:9 15 511 0 1023 EPSG:4326:10 31 1023 0 2047 EPSG:4326:11 62 2047 0 4095 EPSG:4326:12 125 4095 0 8191 EPSG:4326:13 250 8191 0 16383 EPSG:4326:14 501 16383 0 32767 EPSG:4326:15 1002 32767 0 65535 EPSG:4326:16 2004 65535 0 131071 EPSG:4326:17 4008 131071 0 262143 EPSG:4326:18 8017 262143 0 524287 EPSG:4326:19 16034 524287 0 1048575 EPSG:4326:20 32068 1048575 0 2097151 EPSG:4326:21 64137 2097151 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 3 0 3 EPSG:900913:3 0 7 0 7 EPSG:900913:4 0 15 0 15 EPSG:900913:5 0 31 0 31 EPSG:900913:6 1 63 0 63 EPSG:900913:7 2 127 0 127 EPSG:900913:8 4 255 0 255 EPSG:900913:9 8 511 0 511 EPSG:900913:10 17 1023 0 1023 EPSG:900913:11 34 2047 0 2047 EPSG:900913:12 69 4095 0 4095 EPSG:900913:13 139 8191 0 8191 EPSG:900913:14 278 16383 0 16383 EPSG:900913:15 556 32767 0 32767 EPSG:900913:16 1112 65535 0 65535 EPSG:900913:17 2224 131071 0 131071 EPSG:900913:18 4448 262143 0 262143 EPSG:900913:19 8897 524287 0 524287 EPSG:900913:20 17795 1048575 0 1048575 EPSG:900913:21 35591 2097151 0 2097151 EPSG:900913:22 71183 4194303 0 4194303 EPSG:900913:23 142366 8388607 0 8388607 EPSG:900913:24 284733 16777215 0 16777215 EPSG:900913:25 569467 33554431 0 33554431 EPSG:900913:26 1138934 67108863 0 67108863 EPSG:900913:27 2277869 134217727 0 134217727 EPSG:900913:28 4555738 268435455 0 268435455 EPSG:900913:29 9111477 536870911 0 536870911 EPSG:900913:30 18222955 1073741823 0 1073741823 Annual Mean Temperature [°C/10] (2041-2060) RCP4.5 - CIMP5 Mean annual daily mean air temperatures averaged over 1 year [°C/10] for the period 2041-2060 based on RCP4.5. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. Version 1.2 -180.0 -90.0 179.99985967115003 83.99986041515001 UN_Sahel:CHELSA_bio_mon_ACCESS1-0_rcp45_r1i1p1_g025.nc_1_2041-2060_V1.2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 15 0 31 EPSG:4326:5 1 31 0 63 EPSG:4326:6 2 63 0 127 EPSG:4326:7 4 127 0 255 EPSG:4326:8 8 255 0 511 EPSG:4326:9 17 511 0 1023 EPSG:4326:10 34 1023 0 2047 EPSG:4326:11 68 2047 0 4095 EPSG:4326:12 136 4095 0 8191 EPSG:4326:13 273 8191 0 16383 EPSG:4326:14 546 16383 0 32767 EPSG:4326:15 1092 32767 0 65535 EPSG:4326:16 2184 65535 0 131071 EPSG:4326:17 4369 131071 0 262143 EPSG:4326:18 8738 262143 0 524287 EPSG:4326:19 17476 524287 0 1048575 EPSG:4326:20 34953 1048575 0 2097151 EPSG:4326:21 69906 2097151 0 4194302 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 7 0 7 EPSG:3857:4 0 15 0 15 EPSG:3857:5 0 31 0 31 EPSG:3857:6 1 63 0 63 EPSG:3857:7 3 127 0 127 EPSG:3857:8 7 255 0 255 EPSG:3857:9 15 511 0 511 EPSG:3857:10 31 1023 0 1023 EPSG:3857:11 62 2047 0 2047 EPSG:3857:12 125 4095 0 4095 EPSG:3857:13 251 8191 0 8191 EPSG:3857:14 503 16383 0 16383 EPSG:3857:15 1006 32767 0 32767 EPSG:3857:16 2012 65535 0 65535 EPSG:3857:17 4024 131071 0 131071 EPSG:3857:18 8048 262143 0 262143 EPSG:3857:19 16097 524287 0 524287 EPSG:3857:20 32194 1048575 0 1048575 EPSG:3857:21 64389 2097151 0 2097151 EPSG:3857:22 128779 4194303 0 4194302 EPSG:3857:23 257559 8388607 0 8388604 EPSG:3857:24 515119 16777215 0 16777209 EPSG:3857:25 1030238 33554431 0 33554418 EPSG:3857:26 2060476 67108863 0 67108837 EPSG:3857:27 4120952 134217727 0 134217675 EPSG:3857:28 8241905 268435455 0 268435351 EPSG:3857:29 16483810 536870911 0 536870702 EPSG:3857:30 32967621 1073741823 0 1073741405 Areas of Global Significance for Restoration <span style="font-size:1em"> This map shows the results of a global prioritization analysis for the restoration of habitats for terrestrial species and carbon sequestering. Species data used in the analysis consisted in fine-scale distributions maps of more than 20,000 mammals, birds, amphibians, and a geographically-unbiased sample of over 14,000 plant species. The carbon-related benefit was measured by the amount of carbon dioxide sequestered following restoration up to a reference ecosystem structure in each geographical zone, considering above and below-ground biomass and soil carbon. <br> <br> <u>References:</u> <ul> <li> Dinerstein, E., et al. (2017). An ecoregion-based approach to protecting half the terrestrial realm. Bioscience 67:534-545. </li> <li> Erb, K.H., et al.(2018). Unexpectedly large impact of forest management and grazing on global vegetation biomass. Nature 553:73-76. </li> <li> Erb, K.-H., V. Gaube, F. Krausmann, C. Plutzar, A. Bondeau, and H. Haberl. 2007. A comprehensive global 5 min resolution land-use data set for the year 2000 consistent with national census data. Journal of Land Use Science 2:191-224. </li> <li> IUCN (International Union for Conservation of Nature) 2019. The IUCN Red List of Threatened Species. Version 2019-1. <a href="http://www.iucnredlist.org" target="_blank">www.iucnredlist.org</a>. Downloaded on July 2019. </li> <li> Roll U, Feldman A, Novosolov M, Allison A, Bauer A, Bernard R, et al. (2017) The global distribution of tetrapods reveals a need for targeted reptile conservation. Nature Ecology and Evolution; 1, 1677–1682. </li> <li>Sanderman, J., T. Hengl, and G. J. Fiske. 2017. Soil carbon debt of 12,000 years of human land use. Proceedings of the National Academy of Sciences 115. </li> </<ul> </span> -179.87896164729798 -72.35059978902385 179.85992227851924 85.07288135595564 MapX_UNDP:areas_global_significance_restoration_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 12 0 15 EPSG:3857:5 0 25 0 31 EPSG:3857:6 0 50 0 63 EPSG:3857:7 0 101 0 127 EPSG:3857:8 0 203 0 255 EPSG:3857:9 0 407 0 511 EPSG:3857:10 0 815 0 1023 EPSG:3857:11 0 1631 0 2047 EPSG:3857:12 0 3262 1 4094 EPSG:3857:13 0 6524 2 8188 EPSG:3857:14 0 13049 5 16377 EPSG:3857:15 0 26098 11 32755 EPSG:3857:16 0 52196 22 65510 EPSG:3857:17 0 104393 44 131020 EPSG:3857:18 0 208787 88 262041 EPSG:3857:19 0 417575 176 524083 EPSG:3857:20 0 835150 352 1048167 EPSG:3857:21 0 1670300 705 2096335 EPSG:3857:22 -1 3340600 1410 4192671 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1182399 EPSG:4326:21 1009423 1023364 2351192 2364799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 sen_wb_buffer -17.55246539577028 12.283484750909368 -11.263233441297636 16.697303506881106 mapx_chemobs:sen_wb_buffer image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 28 29 28 29 EPSG:3857:7 57 59 57 59 EPSG:3857:8 115 119 115 119 EPSG:3857:9 231 238 231 239 EPSG:3857:10 463 476 462 479 EPSG:3857:11 927 953 924 959 EPSG:3857:12 1855 1907 1848 1919 EPSG:3857:13 3710 3814 3696 3839 EPSG:3857:14 7421 7628 7393 7679 EPSG:3857:15 14842 15257 14786 15358 EPSG:3857:16 29684 30514 29572 30717 EPSG:3857:17 59368 61029 59145 61435 EPSG:3857:18 118737 122058 118290 122870 EPSG:3857:19 237475 244116 236581 245740 EPSG:3857:20 474950 488232 473162 491481 EPSG:3857:21 949900 976464 946325 982962 EPSG:3857:22 1899800 1952929 1892650 1965925 EPSG:3857:23 3799601 3905859 3785301 3931851 EPSG:3857:24 7599203 7811719 7570603 7863703 EPSG:3857:25 15198406 15623439 15141207 15727406 EPSG:3857:26 30396812 31246879 30282415 31454813 EPSG:3857:27 60793624 62493759 60564830 62909626 EPSG:3857:28 121587249 124987518 121129661 125819252 EPSG:3857:29 243174499 249975036 242259322 251638504 EPSG:3857:30 486348998 499950072 484518644 503277009 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 29 EPSG:4326:6 26 27 57 59 EPSG:4326:7 52 55 115 119 EPSG:4326:8 104 110 231 239 EPSG:4326:9 208 221 462 479 EPSG:4326:10 417 442 924 959 EPSG:4326:11 834 884 1848 1919 EPSG:4326:12 1668 1768 3696 3839 EPSG:4326:13 3336 3536 7393 7679 EPSG:4326:14 6672 7073 14786 15358 EPSG:4326:15 13344 14147 29572 30717 EPSG:4326:16 26688 28295 59145 61435 EPSG:4326:17 53377 56591 118290 122870 EPSG:4326:18 106754 113182 236581 245740 EPSG:4326:19 213509 226365 473162 491481 EPSG:4326:20 427019 452731 946325 982962 EPSG:4326:21 854038 905463 1892650 1965925 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 28 29 28 29 EPSG:3857:7 57 59 57 59 EPSG:3857:8 115 119 115 119 EPSG:3857:9 231 238 231 239 EPSG:3857:10 463 476 462 479 EPSG:3857:11 927 953 924 959 EPSG:3857:12 1855 1907 1848 1919 EPSG:3857:13 3710 3814 3696 3839 EPSG:3857:14 7421 7628 7393 7679 EPSG:3857:15 14842 15257 14786 15358 EPSG:3857:16 29684 30514 29572 30717 EPSG:3857:17 59368 61029 59145 61435 EPSG:3857:18 118737 122058 118290 122870 EPSG:3857:19 237475 244116 236581 245740 EPSG:3857:20 474950 488232 473162 491481 EPSG:3857:21 949900 976464 946325 982962 EPSG:3857:22 1899800 1952929 1892650 1965925 EPSG:3857:23 3799601 3905859 3785301 3931851 EPSG:3857:24 7599203 7811719 7570603 7863703 EPSG:3857:25 15198406 15623439 15141207 15727406 EPSG:3857:26 30396812 31246879 30282415 31454813 EPSG:3857:27 60793624 62493759 60564830 62909626 EPSG:3857:28 121587249 124987518 121129661 125819252 EPSG:3857:29 243174499 249975036 242259322 251638504 EPSG:3857:30 486348998 499950072 484518644 503277009 Combination Tsunami/Mangroves at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_man6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Year precipitations 2020 - Central African Republic Total precipitations observed in 2020 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2020_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 site_0336_19860908_visual_average 21.804453393351142 2.163950346428799 22.972377367092143 3.360478793316272 hotspots:site_0336_19860908_visual_average image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 15 15 35 36 EPSG:4326:6 30 31 71 72 EPSG:4326:7 61 62 143 144 EPSG:4326:8 123 124 287 288 EPSG:4326:9 246 249 574 577 EPSG:4326:10 492 499 1148 1154 EPSG:4326:11 985 999 2296 2309 EPSG:4326:12 1971 1998 4592 4618 EPSG:4326:13 3943 3997 9184 9237 EPSG:4326:14 7886 7995 18368 18474 EPSG:4326:15 15772 15990 36737 36949 EPSG:4326:16 31544 31980 73474 73899 EPSG:4326:17 63088 63960 146949 147799 EPSG:4326:18 126177 127920 293899 295599 EPSG:4326:19 252355 255841 587798 591199 EPSG:4326:20 504711 511682 1175596 1182399 EPSG:4326:21 1009423 1023364 2351192 2364799 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 31 31 35 36 EPSG:3857:7 62 63 71 72 EPSG:3857:8 125 126 143 144 EPSG:3857:9 251 252 287 288 EPSG:3857:10 502 505 574 577 EPSG:3857:11 1004 1011 1148 1154 EPSG:3857:12 2009 2023 2296 2309 EPSG:3857:13 4019 4046 4592 4618 EPSG:3857:14 8038 8093 9184 9237 EPSG:3857:15 16077 16186 18368 18474 EPSG:3857:16 32155 32373 36737 36949 EPSG:3857:17 64311 64747 73474 73899 EPSG:3857:18 128623 129495 146949 147799 EPSG:3857:19 257247 258991 293899 295599 EPSG:3857:20 514494 517983 587798 591199 EPSG:3857:21 1028988 1035967 1175596 1182399 EPSG:3857:22 2057977 2071934 2351192 2364799 EPSG:3857:23 4115954 4143868 4702384 4729599 EPSG:3857:24 8231908 8287736 9404769 9459198 EPSG:3857:25 16463816 16575473 18809538 18918396 EPSG:3857:26 32927633 33150946 37619076 37836793 EPSG:3857:27 65855267 66301892 75238153 75673587 EPSG:3857:28 131710535 132603785 150476306 151347174 EPSG:3857:29 263421071 265207571 300952613 302694348 EPSG:3857:30 526842142 530415143 601905227 605388696 Combination Tropical cyclone surge/ Coral reefs at global level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_cor6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 land_cover_copernicus_africa_2015 -30.00049603174603 -34.99950396825388 59.99950396825387 45.00049603174603 MAPX:land_cover_copernicus_africa_2015 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 9 6 10 EPSG:3857:5 11 19 13 21 EPSG:3857:6 23 38 26 42 EPSG:3857:7 46 77 53 85 EPSG:3857:8 92 154 106 170 EPSG:3857:9 184 309 213 341 EPSG:3857:10 368 618 426 682 EPSG:3857:11 736 1236 853 1365 EPSG:3857:12 1473 2473 1706 2730 EPSG:3857:13 2946 4947 3413 5461 EPSG:3857:14 5893 9894 6826 10922 EPSG:3857:15 11787 19788 13653 21845 EPSG:3857:16 23574 39577 27306 43690 EPSG:3857:17 47149 79154 54613 87381 EPSG:3857:18 94299 158308 109226 174762 EPSG:3857:19 188598 316617 218452 349524 EPSG:3857:20 377196 633235 436905 699049 EPSG:3857:21 754393 1266471 873810 1398098 EPSG:3857:22 1508787 2532942 1747620 2796196 EPSG:3857:23 3017575 5065884 3495241 5592393 EPSG:3857:24 6035151 10131768 6990483 11184787 EPSG:3857:25 12070303 20263537 13980967 22369575 EPSG:3857:26 24140607 40527075 27961934 44739150 EPSG:3857:27 48281215 81054151 55923868 89478300 EPSG:3857:28 96562431 162108302 111847736 178956600 EPSG:3857:29 193124862 324216605 223695473 357913201 EPSG:3857:30 386249724 648433210 447390947 715826403 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 5 6 10 EPSG:4326:4 3 11 13 21 EPSG:4326:5 7 22 26 42 EPSG:4326:6 15 44 53 85 EPSG:4326:7 31 88 106 170 EPSG:4326:8 63 177 213 341 EPSG:4326:9 127 355 426 682 EPSG:4326:10 255 711 853 1365 EPSG:4326:11 511 1422 1706 2730 EPSG:4326:12 1023 2844 3413 5461 EPSG:4326:13 2047 5688 6826 10922 EPSG:4326:14 4095 11377 13653 21845 EPSG:4326:15 8191 22755 27306 43690 EPSG:4326:16 16383 45510 54613 87381 EPSG:4326:17 32767 91021 109226 174762 EPSG:4326:18 65535 182043 218452 349524 EPSG:4326:19 131070 364087 436905 699049 EPSG:4326:20 262141 728174 873810 1398098 EPSG:4326:21 524282 1456349 1747620 2796196 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 1 2 1 2 EPSG:900913:3 2 4 3 5 EPSG:900913:4 5 9 6 10 EPSG:900913:5 11 19 13 21 EPSG:900913:6 23 38 26 42 EPSG:900913:7 46 77 53 85 EPSG:900913:8 92 154 106 170 EPSG:900913:9 184 309 213 341 EPSG:900913:10 368 618 426 682 EPSG:900913:11 736 1236 853 1365 EPSG:900913:12 1473 2473 1706 2730 EPSG:900913:13 2946 4947 3413 5461 EPSG:900913:14 5893 9894 6826 10922 EPSG:900913:15 11787 19788 13653 21845 EPSG:900913:16 23574 39577 27306 43690 EPSG:900913:17 47149 79154 54613 87381 EPSG:900913:18 94299 158308 109226 174762 EPSG:900913:19 188598 316617 218452 349524 EPSG:900913:20 377196 633235 436905 699049 EPSG:900913:21 754393 1266471 873810 1398098 EPSG:900913:22 1508787 2532942 1747620 2796196 EPSG:900913:23 3017575 5065884 3495241 5592393 EPSG:900913:24 6035151 10131768 6990483 11184787 EPSG:900913:25 12070303 20263537 13980967 22369575 EPSG:900913:26 24140607 40527075 27961934 44739150 EPSG:900913:27 48281215 81054151 55923868 89478300 EPSG:900913:28 96562431 162108302 111847736 178956600 EPSG:900913:29 193124862 324216605 223695473 357913201 EPSG:900913:30 386249724 648433210 447390947 715826403 POP_FACEBOOK_Lekoumou_2019_92m_UTM_opt 12.79605904597841 -4.052850314579793 14.350819887086997 -2.0880026703818593 AccessMod:POP_FACEBOOK_Lekoumou_2019_92m_UTM_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 8 8 EPSG:3857:5 16 16 17 17 EPSG:3857:6 32 32 34 34 EPSG:3857:7 64 65 68 69 EPSG:3857:8 129 130 137 138 EPSG:3857:9 258 261 274 276 EPSG:3857:10 517 523 548 552 EPSG:3857:11 1035 1047 1096 1105 EPSG:3857:12 2071 2094 2193 2211 EPSG:3857:13 4143 4188 4387 4422 EPSG:3857:14 8287 8376 8774 8845 EPSG:3857:15 16574 16753 17548 17690 EPSG:3857:16 33148 33506 35097 35380 EPSG:3857:17 66296 67012 70194 70760 EPSG:3857:18 132592 134025 140389 141521 EPSG:3857:19 265185 268051 280779 283043 EPSG:3857:20 530371 536102 561559 566087 EPSG:3857:21 1060742 1072205 1123118 1132175 EPSG:3857:22 2121484 2144410 2246236 2264351 EPSG:3857:23 4242968 4288821 4492473 4528702 EPSG:3857:24 8485937 8577642 8984947 9057404 EPSG:3857:25 16971875 17155284 17969895 18114809 EPSG:3857:26 33943750 34310568 35939790 36229618 EPSG:3857:27 67887500 68621137 71879580 72459237 EPSG:3857:28 135775000 137242275 143759161 144918474 EPSG:3857:29 271550000 274484551 287518322 289836949 EPSG:3857:30 543100001 548969102 575036644 579673899 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 8 8 EPSG:4326:4 8 8 17 17 EPSG:4326:5 16 16 34 34 EPSG:4326:6 32 33 68 69 EPSG:4326:7 65 66 137 138 EPSG:4326:8 130 133 274 276 EPSG:4326:9 261 267 548 552 EPSG:4326:10 523 535 1096 1105 EPSG:4326:11 1047 1070 2193 2211 EPSG:4326:12 2095 2140 4387 4422 EPSG:4326:13 4191 4280 8774 8845 EPSG:4326:14 8382 8560 17548 17690 EPSG:4326:15 16764 17121 35097 35380 EPSG:4326:16 33528 34243 70194 70760 EPSG:4326:17 67056 68487 140389 141521 EPSG:4326:18 134112 136974 280779 283043 EPSG:4326:19 268225 273948 561559 566087 EPSG:4326:20 536451 547897 1123118 1132175 EPSG:4326:21 1072902 1095795 2246236 2264351 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 8 8 EPSG:3857:5 16 16 17 17 EPSG:3857:6 32 32 34 34 EPSG:3857:7 64 65 68 69 EPSG:3857:8 129 130 137 138 EPSG:3857:9 258 261 274 276 EPSG:3857:10 517 523 548 552 EPSG:3857:11 1035 1047 1096 1105 EPSG:3857:12 2071 2094 2193 2211 EPSG:3857:13 4143 4188 4387 4422 EPSG:3857:14 8287 8376 8774 8845 EPSG:3857:15 16574 16753 17548 17690 EPSG:3857:16 33148 33506 35097 35380 EPSG:3857:17 66296 67012 70194 70760 EPSG:3857:18 132592 134025 140389 141521 EPSG:3857:19 265185 268051 280779 283043 EPSG:3857:20 530371 536102 561559 566087 EPSG:3857:21 1060742 1072205 1123118 1132175 EPSG:3857:22 2121484 2144410 2246236 2264351 EPSG:3857:23 4242968 4288821 4492473 4528702 EPSG:3857:24 8485937 8577642 8984947 9057404 EPSG:3857:25 16971875 17155284 17969895 18114809 EPSG:3857:26 33943750 34310568 35939790 36229618 EPSG:3857:27 67887500 68621137 71879580 72459237 EPSG:3857:28 135775000 137242275 143759161 144918474 EPSG:3857:29 271550000 274484551 287518322 289836949 EPSG:3857:30 543100001 548969102 575036644 579673899 Average year temperature anomalies (2011-2020) over 1991-2020 climatology Average year temperature anomalies in °Celsius across the period 2011-2020 calculated over the average temperatures per year in the period 1991-2020 (climatology). Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_11_20_anom9120 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Spring precipitations change (%) for the period 2080 - 2099 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_mam_ENDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Temperature change trend (1991-2000) Trend of year temperatures change in '°C per year' across the period 1991-2000. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_00_lm image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 dfo 0.1675000015994978 11.697500041616369 16.000833334932196 23.52416670828256 risk_niger_undp:dfo image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 2 3 8 8 EPSG:4326:4 5 6 16 17 EPSG:4326:5 11 13 32 34 EPSG:4326:6 23 27 64 69 EPSG:4326:7 47 55 128 139 EPSG:4326:8 94 111 256 278 EPSG:4326:9 189 222 512 557 EPSG:4326:10 378 445 1024 1115 EPSG:4326:11 756 890 2049 2230 EPSG:4326:12 1512 1781 4099 4460 EPSG:4326:13 3025 3563 8199 8920 EPSG:4326:14 6050 7127 16399 17840 EPSG:4326:15 12101 14254 32798 35680 EPSG:4326:16 24203 28509 65596 71361 EPSG:4326:17 48406 57018 131193 142723 EPSG:4326:18 96812 114036 262387 285446 EPSG:4326:19 193624 228072 524775 570893 EPSG:4326:20 387249 456145 1049551 1141787 EPSG:4326:21 774499 912290 2099103 2283575 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 6 7 8 8 EPSG:3857:5 13 14 16 17 EPSG:3857:6 27 29 32 34 EPSG:3857:7 55 59 64 69 EPSG:3857:8 110 119 128 139 EPSG:3857:9 221 239 256 278 EPSG:3857:10 443 478 512 557 EPSG:3857:11 886 956 1024 1115 EPSG:3857:12 1772 1913 2049 2230 EPSG:3857:13 3544 3827 4099 4460 EPSG:3857:14 7089 7655 8199 8920 EPSG:3857:15 14179 15311 16399 17840 EPSG:3857:16 28359 30623 32798 35680 EPSG:3857:17 56719 61247 65596 71361 EPSG:3857:18 113439 122494 131193 142723 EPSG:3857:19 226879 244988 262387 285446 EPSG:3857:20 453758 489977 524775 570893 EPSG:3857:21 907517 979954 1049551 1141787 EPSG:3857:22 1815034 1959909 2099103 2283575 EPSG:3857:23 3630068 3919818 4198207 4567150 EPSG:3857:24 7260136 7839637 8396414 9134300 EPSG:3857:25 14520272 15679275 16792828 18268601 EPSG:3857:26 29040545 31358551 33585656 36537203 EPSG:3857:27 58081090 62717103 67171312 73074407 EPSG:3857:28 116162180 125434207 134342625 146148814 EPSG:3857:29 232324360 250868415 268685250 292297628 EPSG:3857:30 464648721 501736831 537370500 584595256 Habitat Quality difference 2010 - 2030 (Mitigation scenario) New map generated at GRID 88.733529924 26.684796595 92.146928137 28.247811534 TEEB:BHU_HQ_30-10 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 3 EPSG:3857:3 3 3 5 6 EPSG:3857:4 6 6 11 12 EPSG:3857:5 13 13 23 24 EPSG:3857:6 26 27 47 48 EPSG:3857:7 53 54 95 96 EPSG:3857:8 107 108 191 193 EPSG:3857:9 214 216 382 387 EPSG:3857:10 428 433 764 774 EPSG:3857:11 856 866 1528 1548 EPSG:3857:12 1712 1732 3057 3096 EPSG:3857:13 3425 3465 6115 6192 EPSG:3857:14 6850 6931 12230 12385 EPSG:3857:15 13701 13862 24460 24771 EPSG:3857:16 27403 27724 48921 49542 EPSG:3857:17 54807 55448 97842 99085 EPSG:3857:18 109614 110897 195685 198171 EPSG:3857:19 219229 221795 391371 396342 EPSG:3857:20 438459 443590 782743 792685 EPSG:3857:21 876918 887180 1565486 1585370 EPSG:3857:22 1753836 1774361 3130972 3170741 EPSG:3857:23 3507672 3548722 6261945 6341483 EPSG:3857:24 7015345 7097444 12523890 12682966 EPSG:3857:25 14030691 14194889 25047780 25365932 EPSG:3857:26 28061382 28389779 50095560 50731864 EPSG:3857:27 56122764 56779558 100191121 101463728 EPSG:3857:28 112245528 113559117 200382243 202927457 EPSG:3857:29 224491056 227118234 400764486 405854915 EPSG:3857:30 448982112 454236468 801528973 811709830 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 3 EPSG:4326:2 1 1 5 6 EPSG:4326:3 2 2 11 12 EPSG:4326:4 5 5 23 24 EPSG:4326:5 10 11 47 48 EPSG:4326:6 21 22 95 96 EPSG:4326:7 43 45 191 193 EPSG:4326:8 87 90 382 387 EPSG:4326:9 175 180 764 774 EPSG:4326:10 351 360 1528 1548 EPSG:4326:11 702 720 3057 3096 EPSG:4326:12 1405 1440 6115 6192 EPSG:4326:13 2810 2881 12230 12385 EPSG:4326:14 5620 5763 24460 24771 EPSG:4326:15 11241 11526 48921 49542 EPSG:4326:16 22483 23052 97842 99085 EPSG:4326:17 44966 46104 195685 198171 EPSG:4326:18 89933 92209 391371 396342 EPSG:4326:19 179866 184418 782743 792685 EPSG:4326:20 359732 368837 1565486 1585370 EPSG:4326:21 719465 737675 3130972 3170741 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 3 EPSG:3857:3 3 3 5 6 EPSG:3857:4 6 6 11 12 EPSG:3857:5 13 13 23 24 EPSG:3857:6 26 27 47 48 EPSG:3857:7 53 54 95 96 EPSG:3857:8 107 108 191 193 EPSG:3857:9 214 216 382 387 EPSG:3857:10 428 433 764 774 EPSG:3857:11 856 866 1528 1548 EPSG:3857:12 1712 1732 3057 3096 EPSG:3857:13 3425 3465 6115 6192 EPSG:3857:14 6850 6931 12230 12385 EPSG:3857:15 13701 13862 24460 24771 EPSG:3857:16 27403 27724 48921 49542 EPSG:3857:17 54807 55448 97842 99085 EPSG:3857:18 109614 110897 195685 198171 EPSG:3857:19 219229 221795 391371 396342 EPSG:3857:20 438459 443590 782743 792685 EPSG:3857:21 876918 887180 1565486 1585370 EPSG:3857:22 1753836 1774361 3130972 3170741 EPSG:3857:23 3507672 3548722 6261945 6341483 EPSG:3857:24 7015345 7097444 12523890 12682966 EPSG:3857:25 14030691 14194889 25047780 25365932 EPSG:3857:26 28061382 28389779 50095560 50731864 EPSG:3857:27 56122764 56779558 100191121 101463728 EPSG:3857:28 112245528 113559117 200382243 202927457 EPSG:3857:29 224491056 227118234 400764486 405854915 EPSG:3857:30 448982112 454236468 801528973 811709830 Dogondoutchi_Intensity_78_T50 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Intensity_78_T50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 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122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 Flood Hazard 50 Years (cm) The GAR Atlas global flood hazard assessment uses a probabilistic approach for modelling riverine flood major river basins around the globe. This has been possible after compiling a global database of stream-flow data, merging different sources and gathering more than 8000 stations over the globe in order to calculate the range of possible discharges from very low to the maximum possible scales at different locations along the rivers. The calculated discharges were introduced in the river sections to model water levels downstream. This procedure allowed for the determination of stochastic event-sets of riverine floods from which hazard maps for several return periods (25, 50, 100, 200, 500, 1000 years) were obtained. The hazard maps are developed at 1kmx1km resolution and have been validated against satellite flood footprints from different sources (DFO archive, UNOSAT flood portal) performing well especially for big events For smaller events (lower return periods), the GAR Atlas flood hazard maps tend to overestimate with respect to similar maps produced locally (hazard maps where available for some countries and were used as benchmark). The main issue being that, due to the resolution, the GAR Atlas flood hazard maps do not take into account flood defenses that are normally present to preserve the value exposed to floods. 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CSIRO Atmospheric Research, Australia, Mk3.5 Model Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_csiro_mk3_5_5km_2041-2060_debiasedmean_tas_av_12month_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 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EPSG:3857:30 535827005 536808174 634124691 635020494 Flood Hazard 200 Years (cm) The GAR Atlas global flood hazard assessment uses a probabilistic approach for modelling riverine flood major river basins around the globe. This has been possible after compiling a global database of stream-flow data, merging different sources and gathering more than 8000 stations over the globe in order to calculate the range of possible discharges from very low to the maximum possible scales at different locations along the rivers. The calculated discharges were introduced in the river sections to model water levels downstream. This procedure allowed for the determination of stochastic event-sets of riverine floods from which hazard maps for several return periods (25, 50, 100, 200, 500, 1000 years) were obtained. The hazard maps are developed at 1kmx1km resolution and have been validated against satellite flood footprints from different sources (DFO archive, UNOSAT flood portal) performing well especially for big events For smaller events (lower return periods), the GAR Atlas flood hazard maps tend to overestimate with respect to similar maps produced locally (hazard maps where available for some countries and were used as benchmark). The main issue being that, due to the resolution, the GAR Atlas flood hazard maps do not take into account flood defenses that are normally present to preserve the value exposed to floods. More information about the flood hazard assessment can be found in the background paper (Rudari et al., 2015). -141.09900045782885 -56.085762831133565 180.0 60.09233546603441 wesr_risk:fl_hazard_200_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 1 15 EPSG:3857:5 9 22 3 31 EPSG:3857:6 18 44 6 63 EPSG:3857:7 37 88 13 127 EPSG:3857:8 74 176 27 255 EPSG:3857:9 148 352 55 511 EPSG:3857:10 296 705 110 1023 EPSG:3857:11 593 1411 221 2047 EPSG:3857:12 1187 2822 442 4095 EPSG:3857:13 2374 5644 885 8191 EPSG:3857:14 4749 11289 1770 16383 EPSG:3857:15 9498 22578 3540 32767 EPSG:3857:16 18997 45156 7081 65535 EPSG:3857:17 37995 90312 14163 131071 EPSG:3857:18 75991 180625 28326 262143 EPSG:3857:19 151983 361251 56653 524287 EPSG:3857:20 303967 722503 113307 1048575 EPSG:3857:21 607934 1445007 226614 2097151 EPSG:3857:22 1215869 2890014 453229 4194304 EPSG:3857:23 2431739 5780029 906458 8388608 EPSG:3857:24 4863479 11560058 1812917 16777215 EPSG:3857:25 9726958 23120116 3625835 33554431 EPSG:3857:26 19453916 46240233 7251671 67108863 EPSG:3857:27 38907833 92480467 14503343 134217727 EPSG:3857:28 77815666 184960934 29006687 268435456 EPSG:3857:29 155631333 369921868 58013375 536870911 EPSG:3857:30 311262667 739843736 116026750 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 1 15 EPSG:4326:4 2 12 3 31 EPSG:4326:5 5 25 6 63 EPSG:4326:6 10 51 13 127 EPSG:4326:7 21 103 27 255 EPSG:4326:8 42 207 55 511 EPSG:4326:9 85 415 110 1023 EPSG:4326:10 170 831 221 2047 EPSG:4326:11 340 1662 442 4095 EPSG:4326:12 680 3324 885 8191 EPSG:4326:13 1361 6648 1770 16383 EPSG:4326:14 2722 13297 3540 32767 EPSG:4326:15 5444 26594 7081 65535 EPSG:4326:16 10889 53188 14163 131071 EPSG:4326:17 21778 106376 28326 262143 EPSG:4326:18 43556 212752 56653 524287 EPSG:4326:19 87112 425505 113307 1048575 EPSG:4326:20 174224 851011 226614 2097151 EPSG:4326:21 348449 1702022 453229 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 1 15 EPSG:3857:5 9 22 3 31 EPSG:3857:6 18 44 6 63 EPSG:3857:7 37 88 13 127 EPSG:3857:8 74 176 27 255 EPSG:3857:9 148 352 55 511 EPSG:3857:10 296 705 110 1023 EPSG:3857:11 593 1411 221 2047 EPSG:3857:12 1187 2822 442 4095 EPSG:3857:13 2374 5644 885 8191 EPSG:3857:14 4749 11289 1770 16383 EPSG:3857:15 9498 22578 3540 32767 EPSG:3857:16 18997 45156 7081 65535 EPSG:3857:17 37995 90312 14163 131071 EPSG:3857:18 75991 180625 28326 262143 EPSG:3857:19 151983 361251 56653 524287 EPSG:3857:20 303967 722503 113307 1048575 EPSG:3857:21 607934 1445007 226614 2097152 EPSG:3857:22 1215869 2890014 453229 4194304 EPSG:3857:23 2431739 5780029 906458 8388607 EPSG:3857:24 4863479 11560058 1812917 16777215 EPSG:3857:25 9726958 23120116 3625835 33554431 EPSG:3857:26 19453916 46240233 7251671 67108863 EPSG:3857:27 38907833 92480467 14503343 134217728 EPSG:3857:28 77815666 184960934 29006687 268435455 EPSG:3857:29 155631333 369921868 58013375 536870911 EPSG:3857:30 311262667 739843736 116026750 1073741824 Mean predicted temperatures 2023 - Reference + Hydro - Central African Republic Mean predicted temperatures in 2023 in the Central African Republic. Reference layer. 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EPSG:4326:18 114980 128068 282938 302243 EPSG:4326:19 229960 256137 565876 604487 EPSG:4326:20 459921 512274 1131753 1208975 EPSG:4326:21 919842 1024548 2263506 2417951 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 253 276 295 EPSG:3857:10 480 506 552 590 EPSG:3857:11 960 1012 1105 1180 EPSG:3857:12 1921 2024 2210 2361 EPSG:3857:13 3842 4049 4420 4722 EPSG:3857:14 7685 8098 8841 9445 EPSG:3857:15 15371 16196 17683 18890 EPSG:3857:16 30743 32392 35367 37780 EPSG:3857:17 61487 64784 70734 75560 EPSG:3857:18 122975 129569 141469 151121 EPSG:3857:19 245951 259139 282938 302243 EPSG:3857:20 491903 518279 565876 604487 EPSG:3857:21 983806 1036559 1131753 1208975 EPSG:3857:22 1967613 2073119 2263506 2417951 EPSG:3857:23 3935226 4146238 4527013 4835902 EPSG:3857:24 7870452 8292477 9054027 9671805 EPSG:3857:25 15740905 16584954 18108054 19343610 EPSG:3857:26 31481810 33169909 36216109 38687220 EPSG:3857:27 62963620 66339819 72432218 77374440 EPSG:3857:28 125927241 132679639 144864436 154748881 EPSG:3857:29 251854483 265359278 289728872 309497763 EPSG:3857:30 503708967 530718556 579457744 618995526 20130401 7.983671848622689 46.30059103015211 8.218081323368821 46.46654729416933 hotspots:20130401 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 2 4 4 EPSG:3857:4 5 5 8 8 EPSG:3857:5 11 11 16 16 EPSG:3857:6 22 22 33 33 EPSG:3857:7 45 45 66 66 EPSG:3857:8 90 90 133 133 EPSG:3857:9 181 181 267 267 EPSG:3857:10 362 363 534 535 EPSG:3857:11 724 726 1069 1070 EPSG:3857:12 1449 1452 2138 2141 EPSG:3857:13 2899 2904 4277 4283 EPSG:3857:14 5798 5809 8555 8566 EPSG:3857:15 11596 11618 17110 17132 EPSG:3857:16 23192 23236 34221 34264 EPSG:3857:17 46384 46472 68442 68528 EPSG:3857:18 92769 92944 136885 137056 EPSG:3857:19 185539 185889 273771 274112 EPSG:3857:20 371078 371779 547542 548224 EPSG:3857:21 742157 743558 1095084 1096449 EPSG:3857:22 1484314 1487117 2190168 2192899 EPSG:3857:23 2968629 2974235 4380337 4385799 EPSG:3857:24 5937259 5948470 8760674 8771598 EPSG:3857:25 11874518 11896941 17521348 17543196 EPSG:3857:26 23749037 23793883 35042696 35086393 EPSG:3857:27 47498074 47587767 70085392 70172786 EPSG:3857:28 94996148 95175535 140170785 140345573 EPSG:3857:29 189992297 190351071 280341570 280691147 EPSG:3857:30 379984594 380702143 560683140 561382294 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 0 0 4 4 EPSG:4326:3 1 1 8 8 EPSG:4326:4 3 3 16 16 EPSG:4326:5 7 7 33 33 EPSG:4326:6 15 15 66 66 EPSG:4326:7 30 31 133 133 EPSG:4326:8 61 62 267 267 EPSG:4326:9 123 124 534 535 EPSG:4326:10 247 248 1069 1070 EPSG:4326:11 495 497 2138 2141 EPSG:4326:12 990 994 4277 4283 EPSG:4326:13 1981 1988 8555 8566 EPSG:4326:14 3962 3977 17110 17132 EPSG:4326:15 7925 7955 34221 34264 EPSG:4326:16 15850 15910 68442 68528 EPSG:4326:17 31700 31820 136885 137056 EPSG:4326:18 63400 63641 273771 274112 EPSG:4326:19 126800 127283 547542 548224 EPSG:4326:20 253600 254567 1095084 1096449 EPSG:4326:21 507201 509135 2190168 2192899 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 2 4 4 EPSG:3857:4 5 5 8 8 EPSG:3857:5 11 11 16 16 EPSG:3857:6 22 22 33 33 EPSG:3857:7 45 45 66 66 EPSG:3857:8 90 90 133 133 EPSG:3857:9 181 181 267 267 EPSG:3857:10 362 363 534 535 EPSG:3857:11 724 726 1069 1070 EPSG:3857:12 1449 1452 2138 2141 EPSG:3857:13 2899 2904 4277 4283 EPSG:3857:14 5798 5809 8555 8566 EPSG:3857:15 11596 11618 17110 17132 EPSG:3857:16 23192 23236 34221 34264 EPSG:3857:17 46384 46472 68442 68528 EPSG:3857:18 92769 92944 136885 137056 EPSG:3857:19 185539 185889 273771 274112 EPSG:3857:20 371078 371779 547542 548224 EPSG:3857:21 742157 743558 1095084 1096449 EPSG:3857:22 1484314 1487117 2190168 2192899 EPSG:3857:23 2968629 2974235 4380337 4385799 EPSG:3857:24 5937259 5948470 8760674 8771598 EPSG:3857:25 11874518 11896941 17521348 17543196 EPSG:3857:26 23749037 23793883 35042696 35086393 EPSG:3857:27 47498074 47587767 70085392 70172786 EPSG:3857:28 94996148 95175535 140170785 140345573 EPSG:3857:29 189992297 190351071 280341570 280691147 EPSG:3857:30 379984594 380702143 560683140 561382294 wesr_climate_perma_histo -180.0 -90.0 180.0 90.0 wesr_climat:wesr_climate_perma_histo image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Forest Integrity Index (FI) The distribution of forest biomass vertically and horizontally is an important predictor of biodiversity, disturbance risk, carbon storage, and hydrological flows. Human activities may alter the influence of forest structure on biodiversity through hunting, introducing non-native species, and altering disturbance regimes. The authors introduce two new remotely sensed indices describing forest structure and human pressure in tropical forests. The Forest Structural Condition Index (SCI) uses best existing global forest data sets to represent a gradient from low to high forest structure development. Remotely sensed estimates of canopy height, tree cover, and time since disturbance comprise inputs of the index. The index distinguishes short, open-canopy, or recently disturbed stands such as those recently deforested from tall, closed-canopy, older stands typical of primary of late secondary forest. The SCI was validated against estimates of foliage height diversity derived from airborne lidar and estimates of aboveground biomass derived from forest inventory plots. The Forest Integrity Index overlays an index of human pressure, the Human Footprint, on SCI to identify structurally complex forests with low human pressure that are likely to be most valuable for biodiversity and ecosystem services. The SCI and Forest Integrity Index are being used to assess progress for countries in reaching the 2020 forest fragmentation and connectivity targets under the Convention on Biodiversity. Broader potential applications include using the SCI and Forest Integrity as predictors of habitat quality, community richness, carbon storage, hydrological yield, and restoration of secondary forest.<br><br>This dataset is provided from the University of Montana through a partnerhsip with the NASA Biodiversity and Ecological Forecasting Program.<br/><br>License information: <a href "https://creativecommons.org/licenses/by/4.0/" target="_blank">CC-4.0 Attribution</a>.<br/> -81.70875583396088 -20.582447168229265 153.42801388207823 25.91760211162399 MapX_UNDP:forest_int_index_19 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 871 1143 559 1896 EPSG:3857:12 1742 2287 1118 3793 EPSG:3857:13 3485 4574 2236 7587 EPSG:3857:14 6970 9149 4473 15174 EPSG:3857:15 13940 18299 8946 30349 EPSG:3857:16 27880 36598 17893 60698 EPSG:3857:17 55760 73196 35786 121397 EPSG:3857:18 111520 146392 71573 242794 EPSG:3857:19 223041 292785 143146 485589 EPSG:3857:20 446082 585571 286293 971179 EPSG:3857:21 892165 1171142 572587 1942358 EPSG:3857:22 1784331 2342285 1145175 3884717 EPSG:3857:23 3568663 4684570 2290351 7769435 EPSG:3857:24 7137327 9369141 4580703 15538871 EPSG:3857:25 14274655 18738283 9161407 31077743 EPSG:3857:26 28549311 37476567 18322815 62155486 EPSG:3857:27 57098623 74953134 36645631 124310973 EPSG:3857:28 114197246 149906268 73291263 248621947 EPSG:3857:29 228394492 299812536 146582527 497243894 EPSG:3857:30 456788984 599625072 293165054 994487788 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 3 EPSG:4326:2 1 2 2 7 EPSG:4326:3 2 4 4 14 EPSG:4326:4 5 9 8 29 EPSG:4326:5 11 19 17 59 EPSG:4326:6 22 39 34 118 EPSG:4326:7 45 78 69 237 EPSG:4326:8 91 157 139 474 EPSG:4326:9 182 314 279 948 EPSG:4326:10 364 629 559 1896 EPSG:4326:11 729 1258 1118 3793 EPSG:4326:12 1458 2516 2236 7587 EPSG:4326:13 2916 5032 4473 15174 EPSG:4326:14 5832 10065 8946 30349 EPSG:4326:15 11665 20130 17893 60698 EPSG:4326:16 23331 40261 35786 121397 EPSG:4326:17 46663 80523 71573 242794 EPSG:4326:18 93326 161047 143146 485589 EPSG:4326:19 186653 322094 286293 971179 EPSG:4326:20 373307 644189 572587 1942358 EPSG:4326:21 746614 1288378 1145175 3884717 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 3 EPSG:3857:3 3 4 2 7 EPSG:3857:4 6 8 4 14 EPSG:3857:5 13 17 8 29 EPSG:3857:6 27 35 17 59 EPSG:3857:7 54 71 34 118 EPSG:3857:8 108 142 69 237 EPSG:3857:9 217 285 139 474 EPSG:3857:10 435 571 279 948 EPSG:3857:11 871 1143 559 1896 EPSG:3857:12 1742 2287 1118 3793 EPSG:3857:13 3485 4574 2236 7587 EPSG:3857:14 6970 9149 4473 15174 EPSG:3857:15 13940 18299 8946 30349 EPSG:3857:16 27880 36598 17893 60698 EPSG:3857:17 55760 73196 35786 121397 EPSG:3857:18 111520 146392 71573 242794 EPSG:3857:19 223041 292785 143146 485589 EPSG:3857:20 446082 585571 286293 971179 EPSG:3857:21 892165 1171142 572587 1942358 EPSG:3857:22 1784331 2342285 1145175 3884717 EPSG:3857:23 3568663 4684570 2290351 7769435 EPSG:3857:24 7137327 9369141 4580703 15538871 EPSG:3857:25 14274655 18738283 9161407 31077743 EPSG:3857:26 28549311 37476567 18322815 62155486 EPSG:3857:27 57098623 74953134 36645631 124310973 EPSG:3857:28 114197246 149906268 73291263 248621947 EPSG:3857:29 228394492 299812536 146582527 497243894 EPSG:3857:30 456788984 599625072 293165054 994487788 Global mercury emissions to air from anthropogenic sources in 2015 (g/km2) Geospatially distributed (gridded) global mercury emissions to air from anthropogenic sources in 2015. Emissions are derived from the AMAP/UNEP global inventory (AMAP/UN-Environment, 2019), geospatially distributed according to methods described in Steenhuisen and Wilson (2019). The dataset is the version dated 5 January 2018. -180.0 -90.0 180.0 90.0 wesr_pollution:HgT_2015_allsectors_025d__g_km2_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Global Intertidal Change (1984-2016) The intertidal environment is one of the last remaining unmapped coastal ecosystems on Earth. Here we present an analysis of over 700,000 satellite images that maps the global extent of and change in tidal flats over the course of 33 years (1984–2016). About 70% of the global extent of tidal flats is found in three continents (Asia (44% of total), North America (15.5% of total) and South America (11% of total)), with 49.2% being concentrated in just eight countries (Indonesia, China, Australia, the United States, Canada, India, Brazil and Myanmar). For regions with sufficient data to develop a consistent multi-decadal time series—which included East Asia, the Middle East and North America—we estimate that 16.02% (15.62–16.47%, 95% confidence interval) of tidal flats were lost between 1984 and 2016. Extensive degradation from coastal development, reduced sediment delivery from major rivers, sinking of riverine deltas, increased coastal erosion and sea-level rise signal a continuing negative trajectory for tidal flat ecosystems around the world.<br><br> For complete information please see: <a href="http://dx.doi.org/10.1038/s41586-018-0805-8"target="_blank">Murray N. J., Phinn S. R., DeWitt M., Ferrari R., Johnston R., Lyons M. B., Clinton N., Thau D. & Fuller R. A. (2019) The global distribution and trajectory of tidal flats. Nature. 565:222-225</a><br/><br>or visit the<br/><br><a href="https://www.intertidal.app/home"target="_blank">Global Intertidal Change</a> website>.<br/> -179.9997453923923 -60.00000496232559 179.9997453923915 60.000004962325846 MapX_UNDP:murray_intertidal_global image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 0 15 EPSG:3857:5 9 22 0 31 EPSG:3857:6 18 45 0 63 EPSG:3857:7 37 90 0 127 EPSG:3857:8 74 181 0 255 EPSG:3857:9 148 363 0 511 EPSG:3857:10 297 726 0 1023 EPSG:3857:11 594 1453 0 2047 EPSG:3857:12 1189 2906 0 4095 EPSG:3857:13 2378 5813 0 8191 EPSG:3857:14 4757 11626 0 16383 EPSG:3857:15 9515 23252 0 32767 EPSG:3857:16 19031 46504 0 65535 EPSG:3857:17 38063 93008 0 131071 EPSG:3857:18 76126 186017 0 262143 EPSG:3857:19 152253 372034 0 524287 EPSG:3857:20 304506 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EPSG:4326:20 174762 873813 1 2097150 EPSG:4326:21 349525 1747626 2 4194301 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 0 15 EPSG:3857:5 9 22 0 31 EPSG:3857:6 18 45 0 63 EPSG:3857:7 37 90 0 127 EPSG:3857:8 74 181 0 255 EPSG:3857:9 148 363 0 511 EPSG:3857:10 297 726 0 1023 EPSG:3857:11 594 1453 0 2047 EPSG:3857:12 1189 2906 0 4095 EPSG:3857:13 2378 5813 0 8191 EPSG:3857:14 4757 11626 0 16383 EPSG:3857:15 9515 23252 0 32767 EPSG:3857:16 19031 46504 0 65535 EPSG:3857:17 38063 93008 0 131071 EPSG:3857:18 76126 186017 0 262143 EPSG:3857:19 152253 372034 0 524287 EPSG:3857:20 304506 744069 0 1048575 EPSG:3857:21 609012 1488139 1 2097150 EPSG:3857:22 1218024 2976279 2 4194301 EPSG:3857:23 2436048 5952559 5 8388602 EPSG:3857:24 4872097 11905118 11 16777204 EPSG:3857:25 9744194 23810237 23 33554408 EPSG:3857:26 19488388 47620475 47 67108816 EPSG:3857:27 38976776 95240951 94 134217633 EPSG:3857:28 77953552 190481903 189 268435266 EPSG:3857:29 155907105 380963806 379 536870532 EPSG:3857:30 311814210 761927613 759 1073741064 v432_CO2_excl_C_1990_opt_deflate -180.0 -77.95 179.95 88.15000000000002 wesr_climat:v432_CO2_excl_C_1990_opt_deflate image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 0 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 -1 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 0 115142440 0 134199086 EPSG:3857:28 -1 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 0 921139526 0 1073592693 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 7 0 15 EPSG:4326:4 0 14 0 31 EPSG:4326:5 0 29 0 63 EPSG:4326:6 0 59 0 127 EPSG:4326:7 1 119 0 255 EPSG:4326:8 2 238 0 511 EPSG:4326:9 5 477 0 1023 EPSG:4326:10 10 955 0 2047 EPSG:4326:11 21 1910 0 4095 EPSG:4326:12 42 3821 0 8190 EPSG:4326:13 84 7643 0 16381 EPSG:4326:14 168 15287 0 32763 EPSG:4326:15 336 30574 0 65526 EPSG:4326:16 673 61148 0 131053 EPSG:4326:17 1347 122297 0 262107 EPSG:4326:18 2694 244594 0 524215 EPSG:4326:19 5388 489189 0 1048430 EPSG:4326:20 10777 978379 0 2096860 EPSG:4326:21 21554 1956759 0 4193721 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 3 0 3 EPSG:3857:3 0 6 0 7 EPSG:3857:4 0 13 0 15 EPSG:3857:5 0 27 0 31 EPSG:3857:6 0 54 0 63 EPSG:3857:7 0 109 0 127 EPSG:3857:8 0 219 0 255 EPSG:3857:9 0 439 0 511 EPSG:3857:10 0 878 0 1023 EPSG:3857:11 0 1756 0 2047 EPSG:3857:12 0 3513 0 4095 EPSG:3857:13 0 7027 0 8190 EPSG:3857:14 0 14055 0 16381 EPSG:3857:15 0 28110 0 32763 EPSG:3857:16 0 56221 0 65526 EPSG:3857:17 0 112443 0 131053 EPSG:3857:18 0 224887 0 262107 EPSG:3857:19 0 449775 0 524215 EPSG:3857:20 0 899550 0 1048430 EPSG:3857:21 -1 1799100 0 2096860 EPSG:3857:22 -1 3598201 0 4193721 EPSG:3857:23 0 7196402 0 8387442 EPSG:3857:24 0 14392805 0 16774885 EPSG:3857:25 0 28785610 0 33549771 EPSG:3857:26 0 57571220 0 67099543 EPSG:3857:27 -1 115142440 0 134199086 EPSG:3857:28 0 230284881 0 268398173 EPSG:3857:29 0 460569763 0 536796346 EPSG:3857:30 -1 921139526 0 1073592693 Global Built-up Reference Layer (BUREF 2010) -180.0 -59.999999994239985 180.0 84.00827573576002 grid_data_core_pro:buref09 image/png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 1 26 0 63 EPSG:4326:6 2 53 0 127 EPSG:4326:7 4 106 0 255 EPSG:4326:8 8 213 0 511 EPSG:4326:9 17 426 0 1023 EPSG:4326:10 34 853 0 2047 EPSG:4326:11 68 1706 0 4095 EPSG:4326:12 136 3413 0 8191 EPSG:4326:13 272 6826 0 16383 EPSG:4326:14 545 13653 0 32767 EPSG:4326:15 1090 27306 0 65535 EPSG:4326:16 2181 54613 0 131071 EPSG:4326:17 4363 109226 0 262143 EPSG:4326:18 8726 218453 0 524287 EPSG:4326:19 17452 436906 0 1048575 EPSG:4326:20 34904 873813 0 2097151 EPSG:4326:21 69808 1747626 0 4194303 EPSG:900913 EPSG:900913:0 0 0 0 0 EPSG:900913:1 0 1 0 1 EPSG:900913:2 0 2 0 3 EPSG:900913:3 0 5 0 7 EPSG:900913:4 0 11 0 15 EPSG:900913:5 0 22 0 31 EPSG:900913:6 1 45 0 63 EPSG:900913:7 3 90 0 127 EPSG:900913:8 7 181 0 255 EPSG:900913:9 15 363 0 511 EPSG:900913:10 31 726 0 1023 EPSG:900913:11 62 1453 0 2047 EPSG:900913:12 124 2906 0 4095 EPSG:900913:13 249 5813 0 8191 EPSG:900913:14 499 11626 0 16383 EPSG:900913:15 998 23252 0 32767 EPSG:900913:16 1997 46504 0 65535 EPSG:900913:17 3995 93008 0 131071 EPSG:900913:18 7990 186017 0 262143 EPSG:900913:19 15980 372034 0 524287 EPSG:900913:20 31960 744069 0 1048575 EPSG:900913:21 63920 1488139 0 2097151 EPSG:900913:22 127841 2976279 0 4194303 EPSG:900913:23 255682 5952559 0 8388607 EPSG:900913:24 511364 11905118 0 16777215 EPSG:900913:25 1022729 23810236 0 33554431 EPSG:900913:26 2045458 47620473 0 67108863 EPSG:900913:27 4090917 95240947 0 134217727 EPSG:900913:28 8181834 190481895 0 268435455 EPSG:900913:29 16363668 380963791 0 536870911 EPSG:900913:30 32727336 761927583 0 1073741823 Combination Tropical cyclone surge/ Coral reefs at national level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_cor6_46 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 GDP - 2019 The GDP data includes 175 countries (or regions). It also provides electricity consumption data for 134 countries (or regions). As such, the research scope covers over 70% of the global land area, and over 90% of the GDP and electricity consumption. It is provided as millions of 2017 US dollars. "We employed nighttime light data to revise the real GDP growth rate. In particular, the real GDP growth rate was estimated using Eq: y∗i,t=ρyi,t+(1−ρ)y′i,t where y∗i,t is the ith country’s real GDP growth in period t; yi,t is the official GDP growth of the ith country in period t; y′i,t presents the ith country’s predicted GDP growth based on the night-time light data in period t; and (1−ρ) is the optimal weight of predicted growth based on the night-time light data." "Next, based on the gridded real GDP growth rate during 1993–2019, the gridded GDP data in 1992 or 2019 were estimated as basic values to obtain the gridded real GDP data in other years. Since the DN values in newly built-up areas were zero in 1992, these areas’ basic GDP values in 1992 were also zero, thereby leading to values of zero in subsequent years. Thus, the gridded GDP data in 2019 was selected as the basic value, which was calculated based on the top-down method. Finally, the gridded real GDP based on the real growth rate can be calculated." Credits: Global 1km×1km gridded revised real gross domestic product and electricity consumption during 1992–2019 based on calibrated nighttime light data (Chen et al., 2022) https://www.nature.com/articles/s41597-022-01322-5 Download from: https://figshare.com/articles/dataset/Global_1_km_1_km_gridded_revised_real_gross_domestic_product_and_electricity_consumption_during_1992-2019_based_on_calibrated_nighttime_light_data/17004523/1 -179.99999957737955 -65.03459342294055 179.99807001075922 75.00630943315629 unccd:gdp2019_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 11 0 15 EPSG:3857:5 5 23 0 31 EPSG:3857:6 11 47 0 63 EPSG:3857:7 22 94 0 127 EPSG:3857:8 45 189 0 255 EPSG:3857:9 90 378 0 511 EPSG:3857:10 181 757 0 1023 EPSG:3857:11 362 1515 0 2047 EPSG:3857:12 725 3030 0 4095 EPSG:3857:13 1451 6061 0 8191 EPSG:3857:14 2903 12123 0 16383 EPSG:3857:15 5807 24247 0 32767 EPSG:3857:16 11615 48495 0 65535 EPSG:3857:17 23230 96991 0 131071 EPSG:3857:18 46460 193983 0 262142 EPSG:3857:19 92920 387966 0 524285 EPSG:3857:20 185840 775932 0 1048570 EPSG:3857:21 371681 1551865 0 2097140 EPSG:3857:22 743362 3103731 0 4194281 EPSG:3857:23 1486724 6207462 0 8388563 EPSG:3857:24 2973449 12414924 0 16777126 EPSG:3857:25 5946898 24829848 0 33554252 EPSG:3857:26 11893797 49659697 0 67108504 EPSG:3857:27 23787594 99319395 0 134217008 EPSG:3857:28 47575189 198638790 0 268434016 EPSG:3857:29 95150378 397277581 0 536868033 EPSG:3857:30 190300756 794555163 1 1073736067 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 13 0 31 EPSG:4326:5 2 27 0 63 EPSG:4326:6 5 55 0 127 EPSG:4326:7 10 110 0 255 EPSG:4326:8 21 220 0 511 EPSG:4326:9 42 440 0 1023 EPSG:4326:10 85 881 0 2047 EPSG:4326:11 170 1763 0 4095 EPSG:4326:12 341 3527 0 8191 EPSG:4326:13 682 7055 0 16383 EPSG:4326:14 1364 14111 0 32767 EPSG:4326:15 2729 28223 0 65535 EPSG:4326:16 5459 56446 0 131071 EPSG:4326:17 10918 112892 0 262142 EPSG:4326:18 21836 225785 0 524285 EPSG:4326:19 43672 451570 0 1048570 EPSG:4326:20 87344 903141 0 2097140 EPSG:4326:21 174689 1806283 0 4194281 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 2 11 0 15 EPSG:3857:5 5 23 0 31 EPSG:3857:6 11 47 0 63 EPSG:3857:7 22 94 0 127 EPSG:3857:8 45 189 0 255 EPSG:3857:9 90 378 0 511 EPSG:3857:10 181 757 0 1023 EPSG:3857:11 362 1515 0 2047 EPSG:3857:12 725 3030 0 4095 EPSG:3857:13 1451 6061 0 8191 EPSG:3857:14 2903 12123 0 16383 EPSG:3857:15 5807 24247 0 32767 EPSG:3857:16 11615 48495 0 65535 EPSG:3857:17 23230 96991 0 131071 EPSG:3857:18 46460 193983 0 262142 EPSG:3857:19 92920 387966 0 524285 EPSG:3857:20 185840 775932 0 1048570 EPSG:3857:21 371681 1551865 0 2097140 EPSG:3857:22 743362 3103731 0 4194281 EPSG:3857:23 1486724 6207462 0 8388563 EPSG:3857:24 2973449 12414924 0 16777126 EPSG:3857:25 5946898 24829848 0 33554252 EPSG:3857:26 11893797 49659697 0 67108504 EPSG:3857:27 23787594 99319395 0 134217008 EPSG:3857:28 47575189 198638790 0 268434016 EPSG:3857:29 95150378 397277581 0 536868033 EPSG:3857:30 190300756 794555163 1 1073736067 tsm_mambo_bado_20190824 27.5809572578242 1.3227299095392917 27.610087434421537 1.351053414069064 rs_for_asgm:tsm_mambo_bado_20190824 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 7 7 18 18 EPSG:4326:5 15 15 36 36 EPSG:4326:6 31 31 73 73 EPSG:4326:7 63 63 147 147 EPSG:4326:8 126 126 295 295 EPSG:4326:9 252 252 590 590 EPSG:4326:10 504 504 1180 1181 EPSG:4326:11 1008 1008 2361 2362 EPSG:4326:12 2017 2017 4723 4724 EPSG:4326:13 4034 4035 9447 9448 EPSG:4326:14 8069 8071 18894 18897 EPSG:4326:15 16138 16143 37788 37794 EPSG:4326:16 32276 32286 75577 75588 EPSG:4326:17 64552 64572 151155 151177 EPSG:4326:18 129104 129145 302311 302354 EPSG:4326:19 258208 258291 604623 604708 EPSG:4326:20 516417 516582 1209246 1209416 EPSG:4326:21 1032835 1033165 2418493 2418832 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 15 15 18 18 EPSG:3857:6 31 31 36 36 EPSG:3857:7 63 63 73 73 EPSG:3857:8 127 127 147 147 EPSG:3857:9 254 254 295 295 EPSG:3857:10 508 508 590 590 EPSG:3857:11 1016 1016 1180 1181 EPSG:3857:12 2032 2032 2361 2362 EPSG:3857:13 4065 4065 4723 4724 EPSG:3857:14 8130 8131 9447 9448 EPSG:3857:15 16261 16263 18894 18897 EPSG:3857:16 32522 32527 37788 37794 EPSG:3857:17 65044 65054 75577 75588 EPSG:3857:18 130088 130108 151155 151177 EPSG:3857:19 260176 260217 302311 302354 EPSG:3857:20 520352 520434 604623 604708 EPSG:3857:21 1040704 1040869 1209246 1209416 EPSG:3857:22 2081409 2081739 2418493 2418832 EPSG:3857:23 4162819 4163479 4836986 4837665 EPSG:3857:24 8325638 8326958 9673973 9675331 EPSG:3857:25 16651277 16653917 19347947 19350662 EPSG:3857:26 33302554 33307835 38695895 38701325 EPSG:3857:27 66605108 66615670 77391790 77402650 EPSG:3857:28 133210216 133231341 154783580 154805301 EPSG:3857:29 266420432 266462682 309567160 309610602 EPSG:3857:30 532840864 532925365 619134321 619221205 Combination Tropical cyclone / Forest at national level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcw_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Precipitation trend (% of change) Oct to Dec (Deyr wet Season) 2008-2018 in Somalia (ICPAC) (ICPAC) Seasonal trends expressed as percentage of change of rainfall time series (Deyr season October to December 2008-2018) reconstructed from station observations, remote sensing and other proxies. The rainfall data were created by combining quality-controlled station observations with satellite rainfall estimates and were reconstructed over land areas on a 0.05 x 0.05 lat/lon grid. Data downloaded from http://digilib.icpac.net/maproom/Climatology/Climate_Analysis/Seasonal_Trend.html.en 40.93000030517578 -1.7000011578202248 51.43000124394894 11.999999046325684 wesr_cca:SOM_ICPAC_prec_trend_perc_Oct_Dec_2008_2018_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 7 8 9 10 EPSG:3857:5 14 16 19 20 EPSG:3857:6 29 32 39 41 EPSG:3857:7 59 64 78 82 EPSG:3857:8 119 129 157 164 EPSG:3857:9 238 258 314 329 EPSG:3857:10 477 516 628 658 EPSG:3857:11 955 1033 1256 1316 EPSG:3857:12 1910 2067 2513 2633 EPSG:3857:13 3820 4134 5027 5266 EPSG:3857:14 7641 8269 10054 10532 EPSG:3857:15 15283 16538 20109 21065 EPSG:3857:16 30567 33077 40219 42130 EPSG:3857:17 61134 66155 80438 84261 EPSG:3857:18 122269 132310 160876 168522 EPSG:3857:19 244538 264620 321752 337044 EPSG:3857:20 489077 529240 643505 674088 EPSG:3857:21 978154 1058480 1287010 1348177 EPSG:3857:22 1956308 2116961 2574021 2696354 EPSG:3857:23 3912616 4233922 5148042 5392709 EPSG:3857:24 7825233 8467845 10296084 10785419 EPSG:3857:25 15650467 16935690 20592168 21570839 EPSG:3857:26 31300934 33871381 41184337 43141679 EPSG:3857:27 62601868 67742763 82368674 86283358 EPSG:3857:28 125203737 135485526 164737348 172566716 EPSG:3857:29 250407474 270971053 329474696 345133432 EPSG:3857:30 500814949 541942107 658949393 690266865 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 5 EPSG:4326:3 3 4 9 10 EPSG:4326:4 6 8 19 20 EPSG:4326:5 13 16 39 41 EPSG:4326:6 27 32 78 82 EPSG:4326:7 55 65 157 164 EPSG:4326:8 110 130 314 329 EPSG:4326:9 221 260 628 658 EPSG:4326:10 443 521 1256 1316 EPSG:4326:11 887 1043 2513 2633 EPSG:4326:12 1774 2086 5027 5266 EPSG:4326:13 3549 4173 10054 10532 EPSG:4326:14 7099 8346 20109 21065 EPSG:4326:15 14199 16693 40219 42130 EPSG:4326:16 28398 33386 80438 84261 EPSG:4326:17 56797 66773 160876 168522 EPSG:4326:18 113595 133547 321752 337044 EPSG:4326:19 227191 267095 643505 674088 EPSG:4326:20 454382 534191 1287010 1348177 EPSG:4326:21 908765 1068382 2574021 2696354 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 5 EPSG:3857:4 7 8 9 10 EPSG:3857:5 14 16 19 20 EPSG:3857:6 29 32 39 41 EPSG:3857:7 59 64 78 82 EPSG:3857:8 119 129 157 164 EPSG:3857:9 238 258 314 329 EPSG:3857:10 477 516 628 658 EPSG:3857:11 955 1033 1256 1316 EPSG:3857:12 1910 2067 2513 2633 EPSG:3857:13 3820 4134 5027 5266 EPSG:3857:14 7641 8269 10054 10532 EPSG:3857:15 15283 16538 20109 21065 EPSG:3857:16 30567 33077 40219 42130 EPSG:3857:17 61134 66155 80438 84261 EPSG:3857:18 122269 132310 160876 168522 EPSG:3857:19 244538 264620 321752 337044 EPSG:3857:20 489077 529240 643505 674088 EPSG:3857:21 978154 1058480 1287010 1348177 EPSG:3857:22 1956308 2116961 2574021 2696354 EPSG:3857:23 3912616 4233922 5148042 5392709 EPSG:3857:24 7825233 8467845 10296084 10785419 EPSG:3857:25 15650467 16935690 20592168 21570839 EPSG:3857:26 31300934 33871381 41184337 43141679 EPSG:3857:27 62601868 67742763 82368674 86283358 EPSG:3857:28 125203737 135485526 164737348 172566716 EPSG:3857:29 250407474 270971053 329474696 345133432 EPSG:3857:30 500814949 541942107 658949393 690266865 Year precipitations 2007 - Central African Republic Total precipitations observed in 2007 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2007_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 frac_cats_2020_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_2020_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Yearly emissions of N2O - 1970 (EDGAR v6.0) EDGARv6.0 provides emissions of the three main greenhouse gases (CO2, CH4, N2O) and fluorinated gases (coming soon) per sector and country. CO2 emissions are provided separately for CO2_excl_short-cycle_org_C and CO2_short-cycle_org_C. Emissions of CO2_excl_short-cycle_org_C include all fossil CO2 sources, such as fossil fuel combustion, non-metallic mineral processes (e.g. cement production), metal (ferrous and non-ferrous) production processes, urea production, agricultural liming and solvents use. Large scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change and forestry (LULUCF) are excluded. For the energy related sectors the activity data are primarily based on IEA data from IEA (2019) World Energy Balances, (Internet: link), All rights reserved, as modified by Joint Research Centre, European Commission, whereas the activity data for the agricultural sectors originate primarily from FAO (2020) (Internet: link). United States Geological Survey (USGS), International Fertiliser Association (IFA), Gas Flaring Reduction Partnership (GGFR)/U.S. National Oceanic and Atmospheric Administration (NOAA), UNFCCC and World Steel Association (worldsteel) recent statistics are also used for activity data. Additional information can be found in Crippa et al. (2021). Compared to EDGARv5.0 the following updates have been included: updates of all activity data up to 2018; inclusion of CO2 emissions from coal mining based on the IPCC 2019 refinements; new international shipping proxies and monthly profiles (Jalkanen et al. (2012), Johansson et al. (2017)). Reference: Crippa, Monica; Guizzardi, Diego; Muntean, Marilena; Schaaf, Edwin; Lo Vullo, Eleonora; Solazzo, Efisio; Monforti-Ferrario, Fabio; Olivier, Jos; Vignati, Elisabetta (2021): EDGAR v6.0 Greenhouse Gas Emissions. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/97a67d67-c62e-4826-b873-9d972c4f670b https://edgar.jrc.ec.europa.eu/dataset_ghg60 -180.0 -90.0 180.0 90.0 wesr_climat:v60_N2O_1970_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Summer precipitations change (%) for the period 2040 - 2059 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_jja_MIDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Flood hazard frequency -180.0 -90.0 180.0 90.0 ECO-DRR:fl_freq image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Pop_wgs84_opt -0.1462858377440157 5.639838970946034 1.8324070818850766 11.150878574337117 AccessMod:Pop_Togo_wgs84_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 3 3 3 4 EPSG:3857:4 7 7 7 8 EPSG:3857:5 15 15 15 16 EPSG:3857:6 30 30 31 32 EPSG:3857:7 60 61 63 64 EPSG:3857:8 120 123 127 129 EPSG:3857:9 240 247 255 258 EPSG:3857:10 480 495 511 517 EPSG:3857:11 960 991 1023 1034 EPSG:3857:12 1920 1983 2046 2068 EPSG:3857:13 3840 3967 4092 4137 EPSG:3857:14 7681 7934 8185 8275 EPSG:3857:15 15362 15869 16370 16550 EPSG:3857:16 30725 31739 32741 33101 EPSG:3857:17 61450 63479 65482 66203 EPSG:3857:18 122900 126958 130965 132406 EPSG:3857:19 245800 253917 261930 264812 EPSG:3857:20 491601 507834 523861 529625 EPSG:3857:21 983203 1015668 1047723 1059250 EPSG:3857:22 1966406 2031336 2095447 2118501 EPSG:3857:23 3932813 4062673 4190895 4237002 EPSG:3857:24 7865627 8125346 8381790 8474004 EPSG:3857:25 15731254 16250693 16763581 16948008 EPSG:3857:26 31462509 32501387 33527162 33896017 EPSG:3857:27 62925019 65002775 67054324 67792034 EPSG:3857:28 125850038 130005551 134108649 135584069 EPSG:3857:29 251700077 260011103 268217298 271168139 EPSG:3857:30 503400154 520022206 536434597 542336279 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 1 1 3 4 EPSG:4326:3 3 3 7 8 EPSG:4326:4 7 7 15 16 EPSG:4326:5 14 14 31 32 EPSG:4326:6 28 29 63 64 EPSG:4326:7 56 59 127 129 EPSG:4326:8 112 119 255 258 EPSG:4326:9 224 239 511 517 EPSG:4326:10 448 479 1023 1034 EPSG:4326:11 897 959 2046 2068 EPSG:4326:12 1794 1919 4092 4137 EPSG:4326:13 3588 3839 8185 8275 EPSG:4326:14 7177 7678 16370 16550 EPSG:4326:15 14354 15357 32741 33101 EPSG:4326:16 28708 30714 65482 66203 EPSG:4326:17 57416 61429 130965 132406 EPSG:4326:18 114832 122858 261930 264812 EPSG:4326:19 229664 245716 523861 529625 EPSG:4326:20 459329 491433 1047723 1059250 EPSG:4326:21 918658 982867 2095447 2118501 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 3 3 3 4 EPSG:3857:4 7 7 7 8 EPSG:3857:5 15 15 15 16 EPSG:3857:6 30 30 31 32 EPSG:3857:7 60 61 63 64 EPSG:3857:8 120 123 127 129 EPSG:3857:9 240 247 255 258 EPSG:3857:10 480 495 511 517 EPSG:3857:11 960 991 1023 1034 EPSG:3857:12 1920 1983 2046 2068 EPSG:3857:13 3840 3967 4092 4137 EPSG:3857:14 7681 7934 8185 8275 EPSG:3857:15 15362 15869 16370 16550 EPSG:3857:16 30725 31739 32741 33101 EPSG:3857:17 61450 63479 65482 66203 EPSG:3857:18 122900 126958 130965 132406 EPSG:3857:19 245800 253917 261930 264812 EPSG:3857:20 491601 507834 523861 529625 EPSG:3857:21 983203 1015668 1047723 1059250 EPSG:3857:22 1966406 2031336 2095447 2118501 EPSG:3857:23 3932813 4062673 4190895 4237002 EPSG:3857:24 7865627 8125346 8381790 8474004 EPSG:3857:25 15731254 16250693 16763581 16948008 EPSG:3857:26 31462509 32501387 33527162 33896017 EPSG:3857:27 62925019 65002775 67054324 67792034 EPSG:3857:28 125850038 130005551 134108649 135584069 EPSG:3857:29 251700077 260011103 268217298 271168139 EPSG:3857:30 503400154 520022206 536434597 542336279 Average annual temperature for future climate using SRES A2 Scenario (2041 - 2060) from National Center for Atmospheric Research, CCSM3.0 Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis. <br> Downscaled Future Climate Scenarios 2.5-minute resolution, 2009. This is a product of Conservation International based on techniques developed in collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin. Additional support provided by the National Center of Ecological Analysis and Synthesis. http://futureclimates.conservation.org (accessed: 06/03/19) -180.0 -60.0 180.0 90.0 LWP:sresa2_ncar_ccsm3_0_5km_2041-2060_debiasedmean_tas_av12_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 0 1488139 0 2097151 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 -1 5952559 0 8388608 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 0 95240947 0 134217727 EPSG:3857:28 -1 190481895 0 268435456 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 0 761927583 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 26 0 63 EPSG:4326:6 0 53 0 127 EPSG:4326:7 0 106 0 255 EPSG:4326:8 0 213 0 511 EPSG:4326:9 0 426 0 1023 EPSG:4326:10 0 853 0 2047 EPSG:4326:11 0 1706 0 4095 EPSG:4326:12 0 3413 0 8191 EPSG:4326:13 0 6826 0 16383 EPSG:4326:14 0 13653 0 32767 EPSG:4326:15 0 27306 0 65535 EPSG:4326:16 0 54613 0 131071 EPSG:4326:17 0 109226 0 262143 EPSG:4326:18 0 218453 0 524287 EPSG:4326:19 0 436906 0 1048575 EPSG:4326:20 0 873813 0 2097151 EPSG:4326:21 0 1747626 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 22 0 31 EPSG:3857:6 0 45 0 63 EPSG:3857:7 0 90 0 127 EPSG:3857:8 0 181 0 255 EPSG:3857:9 0 363 0 511 EPSG:3857:10 0 726 0 1023 EPSG:3857:11 0 1453 0 2047 EPSG:3857:12 0 2906 0 4095 EPSG:3857:13 0 5813 0 8191 EPSG:3857:14 0 11626 0 16383 EPSG:3857:15 0 23252 0 32767 EPSG:3857:16 0 46504 0 65535 EPSG:3857:17 0 93008 0 131071 EPSG:3857:18 0 186017 0 262143 EPSG:3857:19 0 372034 0 524287 EPSG:3857:20 0 744069 0 1048575 EPSG:3857:21 -1 1488139 0 2097152 EPSG:3857:22 -1 2976279 0 4194304 EPSG:3857:23 0 5952559 0 8388607 EPSG:3857:24 0 11905118 0 16777215 EPSG:3857:25 0 23810236 0 33554431 EPSG:3857:26 0 47620473 0 67108863 EPSG:3857:27 -1 95240947 0 134217728 EPSG:3857:28 0 190481895 0 268435455 EPSG:3857:29 0 380963791 0 536870911 EPSG:3857:30 -1 761927583 0 1073741824 Flood Hazard 100 Years (cm) The GAR Atlas global flood hazard assessment uses a probabilistic approach for modelling riverine flood major river basins around the globe. This has been possible after compiling a global database of stream-flow data, merging different sources and gathering more than 8000 stations over the globe in order to calculate the range of possible discharges from very low to the maximum possible scales at different locations along the rivers. The calculated discharges were introduced in the river sections to model water levels downstream. This procedure allowed for the determination of stochastic event-sets of riverine floods from which hazard maps for several return periods (25, 50, 100, 200, 500, 1000 years) were obtained. The hazard maps are developed at 1kmx1km resolution and have been validated against satellite flood footprints from different sources (DFO archive, UNOSAT flood portal) performing well especially for big events For smaller events (lower return periods), the GAR Atlas flood hazard maps tend to overestimate with respect to similar maps produced locally (hazard maps where available for some countries and were used as benchmark). The main issue being that, due to the resolution, the GAR Atlas flood hazard maps do not take into account flood defenses that are normally present to preserve the value exposed to floods. More information about the flood hazard assessment can be found in the background paper (Rudari et al., 2015). -141.09900045782885 -56.085762831133565 180.0 60.09233546603441 wesr_risk:fl_hazard_100_yrp image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 1 15 EPSG:3857:5 9 22 3 31 EPSG:3857:6 18 44 6 63 EPSG:3857:7 37 88 13 127 EPSG:3857:8 74 176 27 255 EPSG:3857:9 148 352 55 511 EPSG:3857:10 296 705 110 1023 EPSG:3857:11 593 1411 221 2047 EPSG:3857:12 1187 2822 442 4095 EPSG:3857:13 2374 5644 885 8191 EPSG:3857:14 4749 11289 1770 16383 EPSG:3857:15 9498 22578 3540 32767 EPSG:3857:16 18997 45156 7081 65535 EPSG:3857:17 37995 90312 14163 131071 EPSG:3857:18 75991 180625 28326 262143 EPSG:3857:19 151983 361251 56653 524287 EPSG:3857:20 303967 722503 113307 1048575 EPSG:3857:21 607934 1445007 226614 2097151 EPSG:3857:22 1215869 2890014 453229 4194304 EPSG:3857:23 2431739 5780029 906458 8388608 EPSG:3857:24 4863479 11560058 1812917 16777215 EPSG:3857:25 9726958 23120116 3625835 33554431 EPSG:3857:26 19453916 46240233 7251671 67108863 EPSG:3857:27 38907833 92480467 14503343 134217727 EPSG:3857:28 77815666 184960934 29006687 268435456 EPSG:3857:29 155631333 369921868 58013375 536870911 EPSG:3857:30 311262667 739843736 116026750 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 1 6 1 15 EPSG:4326:4 2 12 3 31 EPSG:4326:5 5 25 6 63 EPSG:4326:6 10 51 13 127 EPSG:4326:7 21 103 27 255 EPSG:4326:8 42 207 55 511 EPSG:4326:9 85 415 110 1023 EPSG:4326:10 170 831 221 2047 EPSG:4326:11 340 1662 442 4095 EPSG:4326:12 680 3324 885 8191 EPSG:4326:13 1361 6648 1770 16383 EPSG:4326:14 2722 13297 3540 32767 EPSG:4326:15 5444 26594 7081 65535 EPSG:4326:16 10889 53188 14163 131071 EPSG:4326:17 21778 106376 28326 262143 EPSG:4326:18 43556 212752 56653 524287 EPSG:4326:19 87112 425505 113307 1048575 EPSG:4326:20 174224 851011 226614 2097151 EPSG:4326:21 348449 1702022 453229 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 0 3 EPSG:3857:3 2 5 0 7 EPSG:3857:4 4 11 1 15 EPSG:3857:5 9 22 3 31 EPSG:3857:6 18 44 6 63 EPSG:3857:7 37 88 13 127 EPSG:3857:8 74 176 27 255 EPSG:3857:9 148 352 55 511 EPSG:3857:10 296 705 110 1023 EPSG:3857:11 593 1411 221 2047 EPSG:3857:12 1187 2822 442 4095 EPSG:3857:13 2374 5644 885 8191 EPSG:3857:14 4749 11289 1770 16383 EPSG:3857:15 9498 22578 3540 32767 EPSG:3857:16 18997 45156 7081 65535 EPSG:3857:17 37995 90312 14163 131071 EPSG:3857:18 75991 180625 28326 262143 EPSG:3857:19 151983 361251 56653 524287 EPSG:3857:20 303967 722503 113307 1048575 EPSG:3857:21 607934 1445007 226614 2097152 EPSG:3857:22 1215869 2890014 453229 4194304 EPSG:3857:23 2431739 5780029 906458 8388607 EPSG:3857:24 4863479 11560058 1812917 16777215 EPSG:3857:25 9726958 23120116 3625835 33554431 EPSG:3857:26 19453916 46240233 7251671 67108863 EPSG:3857:27 38907833 92480467 14503343 134217728 EPSG:3857:28 77815666 184960934 29006687 268435455 EPSG:3857:29 155631333 369921868 58013375 536870911 EPSG:3857:30 311262667 739843736 116026750 1073741824 Dogondoutchi_Intensity_78_T25 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Intensity_78_T25 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 6 6 16 16 EPSG:4326:5 13 13 32 33 EPSG:4326:6 26 27 64 66 EPSG:4326:7 52 55 129 132 EPSG:4326:8 105 111 259 264 EPSG:4326:9 211 222 518 529 EPSG:4326:10 423 444 1037 1058 EPSG:4326:11 846 888 2075 2117 EPSG:4326:12 1693 1776 4151 4234 EPSG:4326:13 3387 3552 8302 8468 EPSG:4326:14 6774 7105 16605 16936 EPSG:4326:15 13549 14211 33210 33872 EPSG:4326:16 27099 28423 66421 67745 EPSG:4326:17 54199 56847 132842 135490 EPSG:4326:18 108399 113695 265685 270981 EPSG:4326:19 216798 227390 531371 541962 EPSG:4326:20 433596 454780 1062742 1083925 EPSG:4326:21 867193 909560 2125484 2167851 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 Combination Tropical cyclone surge/ Sea grasses at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tcs_sea9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Dogondoutchi_Severity_78_T250 2.431818181818182 11.93181818181818 6.068181818181818 15.568181818181818 risk_niger_undp:Dogondoutchi_Severity_78_T250 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 8 EPSG:4326:4 6 6 16 16 EPSG:4326:5 13 13 32 33 EPSG:4326:6 26 27 64 66 EPSG:4326:7 52 55 129 132 EPSG:4326:8 105 111 259 264 EPSG:4326:9 211 222 518 529 EPSG:4326:10 423 444 1037 1058 EPSG:4326:11 846 888 2075 2117 EPSG:4326:12 1693 1776 4151 4234 EPSG:4326:13 3387 3552 8302 8468 EPSG:4326:14 6774 7105 16605 16936 EPSG:4326:15 13549 14211 33210 33872 EPSG:4326:16 27099 28423 66421 67745 EPSG:4326:17 54199 56847 132842 135490 EPSG:4326:18 108399 113695 265685 270981 EPSG:4326:19 216798 227390 531371 541962 EPSG:4326:20 433596 454780 1062742 1083925 EPSG:4326:21 867193 909560 2125484 2167851 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 8 EPSG:3857:5 14 14 16 16 EPSG:3857:6 29 29 32 33 EPSG:3857:7 58 59 64 66 EPSG:3857:8 116 119 129 132 EPSG:3857:9 233 238 259 264 EPSG:3857:10 467 477 518 529 EPSG:3857:11 934 955 1037 1058 EPSG:3857:12 1868 1911 2075 2117 EPSG:3857:13 3737 3822 4151 4234 EPSG:3857:14 7474 7645 8302 8468 EPSG:3857:15 14949 15290 16605 16936 EPSG:3857:16 29898 30580 33210 33872 EPSG:3857:17 59796 61160 66421 67745 EPSG:3857:18 119593 122320 132842 135490 EPSG:3857:19 239186 244640 265685 270981 EPSG:3857:20 478373 489280 531371 541962 EPSG:3857:21 956747 978560 1062742 1083925 EPSG:3857:22 1913495 1957120 2125484 2167851 EPSG:3857:23 3826991 3914240 4250969 4335702 EPSG:3857:24 7653982 7828481 8501938 8671405 EPSG:3857:25 15307964 15656963 17003877 17342811 EPSG:3857:26 30615928 31313926 34007755 34685623 EPSG:3857:27 61231857 62627853 68015511 69371246 EPSG:3857:28 122463714 125255706 136031023 138742492 EPSG:3857:29 244927428 250511412 272062046 277484984 EPSG:3857:30 489854857 501022824 544124092 554969969 Population Density (EPI - 2018) Source: Map created by EPI (Elephant Protection Initiative) with data from CIESIN, Columbia University, USA. The map is published on UNEP's South Sudan: First State of Environment and Outlook Report 2018, using data from WCS. The UNEP's report could be found <a href="https://www.unenvironment.org/resources/report/south-sudan-first-state-environment-and-outlook-report-2018" target=_blank> here </a> <br><br> The map shows the population distribution in South Sudan. Jonglei is the most populous area, with 16 per cent of the total population, and Western Bahr el Ghazal is the least populous area with only 4 per cent of the total. The highest population densities are along the Nile River and their tributaries. 24.15069586900006 3.48747093435 35.95069586900014 12.23747093435006 MAPX:Population_Density_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4016 4645 4914 EPSG:3857:14 7630 8033 9291 9828 EPSG:3857:15 15261 16066 18582 19656 EPSG:3857:16 30523 32132 37164 39312 EPSG:3857:17 61046 64265 74329 78625 EPSG:3857:18 122092 128530 148658 157250 EPSG:3857:19 244184 257061 297316 314500 EPSG:3857:20 488369 514123 594632 629001 EPSG:3857:21 976739 1028247 1189264 1258003 EPSG:3857:22 1953478 2056494 2378528 2516007 EPSG:3857:23 3906957 4112989 4757056 5032015 EPSG:3857:24 7813914 8225979 9514112 10064031 EPSG:3857:25 15627828 16451959 19028224 20128063 EPSG:3857:26 31255657 32903918 38056448 40256127 EPSG:3857:27 62511314 65807836 76112896 80512254 EPSG:3857:28 125022629 131615673 152225792 161024509 EPSG:3857:29 250045258 263231347 304451584 322049019 EPSG:3857:30 500090517 526462695 608903168 644098039 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 6 7 18 19 EPSG:4326:5 13 15 36 38 EPSG:4326:6 27 30 72 76 EPSG:4326:7 55 61 145 153 EPSG:4326:8 110 123 290 307 EPSG:4326:9 221 246 580 614 EPSG:4326:10 442 492 1161 1228 EPSG:4326:11 884 984 2322 2457 EPSG:4326:12 1769 1968 4645 4914 EPSG:4326:13 3539 3937 9291 9828 EPSG:4326:14 7078 7874 18582 19656 EPSG:4326:15 14156 15749 37164 39312 EPSG:4326:16 28312 31498 74329 78625 EPSG:4326:17 56624 62996 148658 157250 EPSG:4326:18 113249 125993 297316 314500 EPSG:4326:19 226499 251986 594632 629001 EPSG:4326:20 452999 503972 1189264 1258003 EPSG:4326:21 905999 1007944 2378528 2516007 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4016 4645 4914 EPSG:3857:14 7630 8033 9291 9828 EPSG:3857:15 15261 16066 18582 19656 EPSG:3857:16 30523 32132 37164 39312 EPSG:3857:17 61046 64265 74329 78625 EPSG:3857:18 122092 128530 148658 157250 EPSG:3857:19 244184 257061 297316 314500 EPSG:3857:20 488369 514123 594632 629001 EPSG:3857:21 976739 1028247 1189264 1258003 EPSG:3857:22 1953478 2056494 2378528 2516007 EPSG:3857:23 3906957 4112989 4757056 5032015 EPSG:3857:24 7813914 8225979 9514112 10064031 EPSG:3857:25 15627828 16451959 19028224 20128063 EPSG:3857:26 31255657 32903918 38056448 40256127 EPSG:3857:27 62511314 65807836 76112896 80512254 EPSG:3857:28 125022629 131615673 152225792 161024509 EPSG:3857:29 250045258 263231347 304451584 322049019 EPSG:3857:30 500090517 526462695 608903168 644098039 Year precipitations 2008 - Central African Republic Total precipitations observed in 2008 in the Central African Republic. 14.417960310118321 2.218838751775218 27.47048138837497 11.013345383305333 cc_and_health:precip_2008_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 553 590 EPSG:4326:10 449 499 1106 1180 EPSG:4326:11 898 998 2212 2360 EPSG:4326:12 1797 1997 4424 4721 EPSG:4326:13 3594 3995 8848 9442 EPSG:4326:14 7189 7990 17696 18884 EPSG:4326:15 14379 15980 35392 37768 EPSG:4326:16 28758 31960 70785 75537 EPSG:4326:17 57516 63920 141570 151075 EPSG:4326:18 115032 127840 283141 302150 EPSG:4326:19 230065 255681 566283 604301 EPSG:4326:20 460130 511362 1132566 1208603 EPSG:4326:21 920261 1022724 2265133 2417206 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 553 590 EPSG:3857:11 960 1011 1106 1180 EPSG:3857:12 1921 2022 2212 2360 EPSG:3857:13 3843 4045 4424 4721 EPSG:3857:14 7687 8090 8848 9442 EPSG:3857:15 15375 16181 17696 18884 EPSG:3857:16 30750 32363 35392 37768 EPSG:3857:17 61501 64727 70785 75537 EPSG:3857:18 123002 129455 141570 151075 EPSG:3857:19 246004 258911 283141 302150 EPSG:3857:20 492009 517823 566283 604301 EPSG:3857:21 984019 1035647 1132566 1208603 EPSG:3857:22 1968039 2071294 2265133 2417206 EPSG:3857:23 3936079 4142588 4530266 4834412 EPSG:3857:24 7872158 8285176 9060533 9668825 EPSG:3857:25 15744317 16570353 18121067 19337650 EPSG:3857:26 31488634 33140707 36242134 38675300 EPSG:3857:27 62977269 66281414 72484269 77350601 EPSG:3857:28 125954539 132562828 144968538 154701203 EPSG:3857:29 251909079 265125656 289937076 309402407 EPSG:3857:30 503818158 530251312 579874153 618804814 Dust Concentration Extreme Events 2017-2022 -17.499999999999943 -1.4999999999999432 75.00000000000006 45.00000000000006 unccd:dust_extreme_events_2017_2022_output image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 231 362 EPSG:3857:10 368 516 462 725 EPSG:3857:11 736 1032 924 1450 EPSG:3857:12 1473 2065 1848 2901 EPSG:3857:13 2946 4130 3697 5802 EPSG:3857:14 5893 8260 7395 11605 EPSG:3857:15 11787 16520 14791 23210 EPSG:3857:16 23574 33041 29582 46421 EPSG:3857:17 47149 66082 59164 92842 EPSG:3857:18 94299 132164 118328 185685 EPSG:3857:19 188599 264328 236657 371370 EPSG:3857:20 377199 528657 473315 742741 EPSG:3857:21 754398 1057315 946631 1485482 EPSG:3857:22 1508796 2114630 1893262 2970965 EPSG:3857:23 3017592 4229260 3786524 5941930 EPSG:3857:24 6035184 8458521 7573048 11883861 EPSG:3857:25 12070369 16917042 15146097 23767722 EPSG:3857:26 24140738 33834084 30292195 47535445 EPSG:3857:27 48281477 67668168 60584391 95070890 EPSG:3857:28 96562954 135336336 121168782 190141781 EPSG:3857:29 193125908 270672673 242337564 380283562 EPSG:3857:30 386251817 541345347 484675128 760567125 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 1 2 EPSG:4326:2 0 2 3 5 EPSG:4326:3 1 4 7 11 EPSG:4326:4 3 8 14 22 EPSG:4326:5 7 16 28 45 EPSG:4326:6 15 32 57 90 EPSG:4326:7 31 65 115 181 EPSG:4326:8 63 130 231 362 EPSG:4326:9 127 260 462 725 EPSG:4326:10 255 520 924 1450 EPSG:4326:11 511 1041 1848 2901 EPSG:4326:12 1023 2082 3697 5802 EPSG:4326:13 2047 4164 7395 11605 EPSG:4326:14 4095 8328 14791 23210 EPSG:4326:15 8191 16657 29582 46421 EPSG:4326:16 16383 33314 59164 92842 EPSG:4326:17 32767 66628 118328 185685 EPSG:4326:18 65535 133256 236657 371370 EPSG:4326:19 131071 266513 473315 742741 EPSG:4326:20 262143 533026 946631 1485482 EPSG:4326:21 524287 1066052 1893262 2970965 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 7 11 EPSG:3857:5 11 16 14 22 EPSG:3857:6 23 32 28 45 EPSG:3857:7 46 64 57 90 EPSG:3857:8 92 129 115 181 EPSG:3857:9 184 258 231 362 EPSG:3857:10 368 516 462 725 EPSG:3857:11 736 1032 924 1450 EPSG:3857:12 1473 2065 1848 2901 EPSG:3857:13 2946 4130 3697 5802 EPSG:3857:14 5893 8260 7395 11605 EPSG:3857:15 11787 16520 14791 23210 EPSG:3857:16 23574 33041 29582 46421 EPSG:3857:17 47149 66082 59164 92842 EPSG:3857:18 94299 132164 118328 185685 EPSG:3857:19 188599 264328 236657 371370 EPSG:3857:20 377199 528657 473315 742741 EPSG:3857:21 754398 1057315 946631 1485482 EPSG:3857:22 1508796 2114630 1893262 2970965 EPSG:3857:23 3017592 4229260 3786524 5941930 EPSG:3857:24 6035184 8458521 7573048 11883861 EPSG:3857:25 12070369 16917042 15146097 23767722 EPSG:3857:26 24140738 33834084 30292195 47535445 EPSG:3857:27 48281477 67668168 60584391 95070890 EPSG:3857:28 96562954 135336336 121168782 190141781 EPSG:3857:29 193125908 270672673 242337564 380283562 EPSG:3857:30 386251817 541345347 484675128 760567125 Forest cover (Hansen) in mining concession areas in Congo - 2015 The data was generated on Google Earth Engine starting from the layer Forest_cover_2000 (Hansen) in DRC and removing the data where there was a forest loss from 2001 to 2014 (loss_year values from 1 to 14). The data was then clipped to the mining concession areas (CAMI) in DRC. 12.383333300292 -13.455676000047001 30.808333300292 5.033323999953 MAPX_nd:drc_hansen_cover_clipped_mines_2015 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 17 17 18 EPSG:3857:6 31 34 34 37 EPSG:3857:7 62 68 68 74 EPSG:3857:8 124 137 136 149 EPSG:3857:9 248 275 273 299 EPSG:3857:10 497 550 547 599 EPSG:3857:11 995 1101 1094 1199 EPSG:3857:12 1990 2202 2188 2398 EPSG:3857:13 3981 4405 4377 4797 EPSG:3857:14 7962 8810 8755 9594 EPSG:3857:15 15925 17620 17511 19188 EPSG:3857:16 31850 35240 35022 38376 EPSG:3857:17 63701 70480 70044 76752 EPSG:3857:18 127402 140961 140089 153505 EPSG:3857:19 254804 281922 280178 307011 EPSG:3857:20 509608 563845 560357 614023 EPSG:3857:21 1019216 1127691 1120714 1228047 EPSG:3857:22 2038433 2255383 2241428 2456095 EPSG:3857:23 4076867 4510766 4482856 4912190 EPSG:3857:24 8153735 9021532 8965713 9824380 EPSG:3857:25 16307471 18043065 17931426 19648760 EPSG:3857:26 32614943 36086131 35862852 39297521 EPSG:3857:27 65229886 72172263 71725705 78595043 EPSG:3857:28 130459772 144344526 143451410 157190086 EPSG:3857:29 260919545 288689052 286902821 314380172 EPSG:3857:30 521839091 577378105 573805642 628760345 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 9 17 18 EPSG:4326:5 15 18 34 37 EPSG:4326:6 30 36 68 74 EPSG:4326:7 60 73 136 149 EPSG:4326:8 120 147 273 299 EPSG:4326:9 241 294 547 599 EPSG:4326:10 483 588 1094 1199 EPSG:4326:11 966 1177 2188 2398 EPSG:4326:12 1933 2354 4377 4797 EPSG:4326:13 3866 4708 8755 9594 EPSG:4326:14 7733 9416 17511 19188 EPSG:4326:15 15467 18833 35022 38376 EPSG:4326:16 30935 37667 70044 76752 EPSG:4326:17 61870 75334 140089 153505 EPSG:4326:18 123741 150668 280178 307011 EPSG:4326:19 247483 301336 560357 614023 EPSG:4326:20 494966 602672 1120714 1228047 EPSG:4326:21 989933 1205345 2241428 2456095 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 17 17 18 EPSG:3857:6 31 34 34 37 EPSG:3857:7 62 68 68 74 EPSG:3857:8 124 137 136 149 EPSG:3857:9 248 275 273 299 EPSG:3857:10 497 550 547 599 EPSG:3857:11 995 1101 1094 1199 EPSG:3857:12 1990 2202 2188 2398 EPSG:3857:13 3981 4405 4377 4797 EPSG:3857:14 7962 8810 8755 9594 EPSG:3857:15 15925 17620 17511 19188 EPSG:3857:16 31850 35240 35022 38376 EPSG:3857:17 63701 70480 70044 76752 EPSG:3857:18 127402 140961 140089 153505 EPSG:3857:19 254804 281922 280178 307011 EPSG:3857:20 509608 563845 560357 614023 EPSG:3857:21 1019216 1127691 1120714 1228047 EPSG:3857:22 2038433 2255383 2241428 2456095 EPSG:3857:23 4076867 4510766 4482856 4912190 EPSG:3857:24 8153735 9021532 8965713 9824380 EPSG:3857:25 16307471 18043065 17931426 19648760 EPSG:3857:26 32614943 36086131 35862852 39297521 EPSG:3857:27 65229886 72172263 71725705 78595043 EPSG:3857:28 130459772 144344526 143451410 157190086 EPSG:3857:29 260919545 288689052 286902821 314380172 EPSG:3857:30 521839091 577378105 573805642 628760345 Forest cover (Hansen) in mining concession areas in Congo - 2016 The data was generated on Google Earth Engine starting from the layer Forest_cover_2000 (Hansen) in DRC and removing the data where there was a forest loss from 2001 to 2015 (loss_year values from 1 to 15). The data was then clipped to the mining concession areas (CAMI) in DRC. 10.0 -20.0 30.80825 5.033249999999999 MAPX_nd:drc_hansen_cover_clipped_mines_2016 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 17 16 18 EPSG:3857:6 31 35 33 37 EPSG:3857:7 62 71 67 74 EPSG:3857:8 124 142 135 149 EPSG:3857:9 248 285 270 299 EPSG:3857:10 497 570 540 599 EPSG:3857:11 995 1140 1080 1199 EPSG:3857:12 1990 2280 2161 2398 EPSG:3857:13 3981 4560 4323 4797 EPSG:3857:14 7962 9121 8647 9594 EPSG:3857:15 15925 18242 17294 19188 EPSG:3857:16 31850 36485 34588 38376 EPSG:3857:17 63701 72970 69176 76752 EPSG:3857:18 127402 145940 138353 153505 EPSG:3857:19 254804 291881 276707 307011 EPSG:3857:20 509608 583762 553415 614023 EPSG:3857:21 1019217 1167525 1106830 1228047 EPSG:3857:22 2038434 2335050 2213660 2456094 EPSG:3857:23 4076869 4670100 4427320 4912188 EPSG:3857:24 8153739 9340201 8854641 9824376 EPSG:3857:25 16307478 18680403 17709283 19648753 EPSG:3857:26 32614957 37360806 35418567 39297506 EPSG:3857:27 65229914 74721613 70837134 78595012 EPSG:3857:28 130459828 149443226 141674268 157190024 EPSG:3857:29 260919656 298886452 283348536 314380048 EPSG:3857:30 521839313 597772904 566697073 628760096 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 9 16 18 EPSG:4326:5 15 19 33 37 EPSG:4326:6 30 39 67 74 EPSG:4326:7 60 78 135 149 EPSG:4326:8 120 156 270 299 EPSG:4326:9 241 312 540 599 EPSG:4326:10 483 625 1080 1199 EPSG:4326:11 966 1251 2161 2398 EPSG:4326:12 1933 2503 4323 4797 EPSG:4326:13 3866 5006 8647 9594 EPSG:4326:14 7733 10012 17294 19188 EPSG:4326:15 15467 20024 34588 38376 EPSG:4326:16 30935 40049 69176 76752 EPSG:4326:17 61870 80099 138353 153505 EPSG:4326:18 123741 160199 276707 307011 EPSG:4326:19 247483 320398 553415 614023 EPSG:4326:20 494967 640796 1106830 1228047 EPSG:4326:21 989934 1281592 2213660 2456094 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 17 16 18 EPSG:3857:6 31 35 33 37 EPSG:3857:7 62 71 67 74 EPSG:3857:8 124 142 135 149 EPSG:3857:9 248 285 270 299 EPSG:3857:10 497 570 540 599 EPSG:3857:11 995 1140 1080 1199 EPSG:3857:12 1990 2280 2161 2398 EPSG:3857:13 3981 4560 4323 4797 EPSG:3857:14 7962 9121 8647 9594 EPSG:3857:15 15925 18242 17294 19188 EPSG:3857:16 31850 36485 34588 38376 EPSG:3857:17 63701 72970 69176 76752 EPSG:3857:18 127402 145940 138353 153505 EPSG:3857:19 254804 291881 276707 307011 EPSG:3857:20 509608 583762 553415 614023 EPSG:3857:21 1019217 1167525 1106830 1228047 EPSG:3857:22 2038434 2335050 2213660 2456094 EPSG:3857:23 4076869 4670100 4427320 4912188 EPSG:3857:24 8153739 9340201 8854641 9824376 EPSG:3857:25 16307478 18680403 17709283 19648753 EPSG:3857:26 32614957 37360806 35418567 39297506 EPSG:3857:27 65229914 74721613 70837134 78595012 EPSG:3857:28 130459828 149443226 141674268 157190024 EPSG:3857:29 260919656 298886452 283348536 314380048 EPSG:3857:30 521839313 597772904 566697073 628760096 frac_cats_transition_2018_2019_kamituga 28.141845709394754 -3.221071413308412 28.214936578763222 -3.0368306131003737 rs_for_asgm:frac_cats_transition_2018_2019_kamituga image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 4 9 9 EPSG:4326:4 8 8 18 18 EPSG:4326:5 16 16 37 37 EPSG:4326:6 33 33 74 74 EPSG:4326:7 66 66 148 148 EPSG:4326:8 132 132 296 296 EPSG:4326:9 264 265 592 592 EPSG:4326:10 529 530 1184 1184 EPSG:4326:11 1058 1060 2368 2369 EPSG:4326:12 2117 2121 4736 4738 EPSG:4326:13 4234 4242 9472 9476 EPSG:4326:14 8468 8485 18945 18952 EPSG:4326:15 16936 16970 37891 37904 EPSG:4326:16 33873 33940 75782 75808 EPSG:4326:17 67747 67881 151564 151617 EPSG:4326:18 135494 135763 303128 303234 EPSG:4326:19 270989 271526 606257 606469 EPSG:4326:20 541978 543052 1212514 1212939 EPSG:4326:21 1083957 1086104 2425028 2425879 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 8 9 9 EPSG:3857:5 16 16 18 18 EPSG:3857:6 32 32 37 37 EPSG:3857:7 65 65 74 74 EPSG:3857:8 130 130 148 148 EPSG:3857:9 260 260 296 296 EPSG:3857:10 520 521 592 592 EPSG:3857:11 1041 1042 1184 1184 EPSG:3857:12 2082 2084 2368 2369 EPSG:3857:13 4165 4169 4736 4738 EPSG:3857:14 8330 8338 9472 9476 EPSG:3857:15 16660 16677 18945 18952 EPSG:3857:16 33321 33354 37891 37904 EPSG:3857:17 66642 66709 75782 75808 EPSG:3857:18 133284 133418 151564 151617 EPSG:3857:19 266568 266837 303128 303234 EPSG:3857:20 533137 533674 606257 606469 EPSG:3857:21 1066275 1067349 1212514 1212939 EPSG:3857:22 2132550 2134699 2425028 2425879 EPSG:3857:23 4265100 4269399 4850056 4851759 EPSG:3857:24 8530200 8538799 9700113 9703519 EPSG:3857:25 17060401 17077599 19400226 19407038 EPSG:3857:26 34120803 34155199 38800452 38814077 EPSG:3857:27 68241607 68310399 77600904 77628154 EPSG:3857:28 136483214 136620799 155201809 155256309 EPSG:3857:29 272966428 273241598 310403618 310512619 EPSG:3857:30 545932856 546483196 620807236 621025238 Combination Tsunami/Sea grasses at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_sea6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Forest cover (Hansen) in mining concession areas in Congo - 2013 The data was generated on Google Earth Engine starting from the layer Forest_cover_2000 (Hansen) in DRC and removing the data where there was a forest loss from 2001 to 2012 (loss_year values from 1 to 12). The data was then clipped to the mining concession areas (CAMI) in DRC. 12.383333300292 -13.455676000047001 30.841583300292 5.166573999953 MAPX_nd:drc_hansen_cover_clipped_mines_2013 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 17 17 18 EPSG:3857:6 31 34 34 37 EPSG:3857:7 62 68 68 74 EPSG:3857:8 124 137 136 149 EPSG:3857:9 248 275 273 299 EPSG:3857:10 497 550 547 599 EPSG:3857:11 994 1101 1094 1199 EPSG:3857:12 1989 2202 2188 2398 EPSG:3857:13 3978 4405 4377 4797 EPSG:3857:14 7956 8810 8755 9595 EPSG:3857:15 15913 17620 17511 19191 EPSG:3857:16 31826 35240 35022 38382 EPSG:3857:17 63652 70480 70044 76765 EPSG:3857:18 127304 140961 140089 153530 EPSG:3857:19 254609 281922 280178 307060 EPSG:3857:20 509218 563845 560357 614120 EPSG:3857:21 1018437 1127691 1120714 1228241 EPSG:3857:22 2036875 2255383 2241428 2456482 EPSG:3857:23 4073750 4510766 4482856 4912964 EPSG:3857:24 8147501 9021532 8965713 9825929 EPSG:3857:25 16295002 18043065 17931426 19651859 EPSG:3857:26 32590004 36086131 35862852 39303719 EPSG:3857:27 65180009 72172263 71725705 78607439 EPSG:3857:28 130360019 144344526 143451410 157214879 EPSG:3857:29 260720039 288689052 286902821 314429758 EPSG:3857:30 521440078 577378105 573805642 628859517 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 9 17 18 EPSG:4326:5 15 18 34 37 EPSG:4326:6 30 36 68 74 EPSG:4326:7 60 73 136 149 EPSG:4326:8 120 147 273 299 EPSG:4326:9 241 294 547 599 EPSG:4326:10 482 588 1094 1199 EPSG:4326:11 965 1177 2188 2398 EPSG:4326:12 1930 2354 4377 4797 EPSG:4326:13 3860 4708 8755 9595 EPSG:4326:14 7721 9416 17511 19191 EPSG:4326:15 15443 18833 35022 38382 EPSG:4326:16 30886 37667 70044 76765 EPSG:4326:17 61773 75334 140089 153530 EPSG:4326:18 123547 150668 280178 307060 EPSG:4326:19 247095 301336 560357 614120 EPSG:4326:20 494190 602672 1120714 1228241 EPSG:4326:21 988381 1205345 2241428 2456482 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 17 17 18 EPSG:3857:6 31 34 34 37 EPSG:3857:7 62 68 68 74 EPSG:3857:8 124 137 136 149 EPSG:3857:9 248 275 273 299 EPSG:3857:10 497 550 547 599 EPSG:3857:11 994 1101 1094 1199 EPSG:3857:12 1989 2202 2188 2398 EPSG:3857:13 3978 4405 4377 4797 EPSG:3857:14 7956 8810 8755 9595 EPSG:3857:15 15913 17620 17511 19191 EPSG:3857:16 31826 35240 35022 38382 EPSG:3857:17 63652 70480 70044 76765 EPSG:3857:18 127304 140961 140089 153530 EPSG:3857:19 254609 281922 280178 307060 EPSG:3857:20 509218 563845 560357 614120 EPSG:3857:21 1018437 1127691 1120714 1228241 EPSG:3857:22 2036875 2255383 2241428 2456482 EPSG:3857:23 4073750 4510766 4482856 4912964 EPSG:3857:24 8147501 9021532 8965713 9825929 EPSG:3857:25 16295002 18043065 17931426 19651859 EPSG:3857:26 32590004 36086131 35862852 39303719 EPSG:3857:27 65180009 72172263 71725705 78607439 EPSG:3857:28 130360019 144344526 143451410 157214879 EPSG:3857:29 260720039 288689052 286902821 314429758 EPSG:3857:30 521440078 577378105 573805642 628859517 Forest cover (Hansen) in mining concession areas in Congo - 2014 The data was generated on Google Earth Engine starting from the layer Forest_cover_2000 (Hansen) in DRC and removing the data where there was a forest loss from 2001 to 2013 (loss_year values from 1 to 13). The data was then clipped to the mining concession areas (CAMI) in DRC. 12.383333300292 -13.455676000047001 30.808333300292 5.033323999953 MAPX_nd:drc_hansen_cover_clipped_mines_2014 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 17 17 18 EPSG:3857:6 31 34 34 37 EPSG:3857:7 62 68 68 74 EPSG:3857:8 124 137 136 149 EPSG:3857:9 248 275 273 299 EPSG:3857:10 497 550 547 599 EPSG:3857:11 995 1101 1094 1199 EPSG:3857:12 1990 2202 2188 2398 EPSG:3857:13 3981 4405 4377 4797 EPSG:3857:14 7962 8810 8755 9594 EPSG:3857:15 15925 17620 17511 19188 EPSG:3857:16 31850 35240 35022 38376 EPSG:3857:17 63701 70480 70044 76752 EPSG:3857:18 127402 140961 140089 153505 EPSG:3857:19 254804 281922 280178 307011 EPSG:3857:20 509608 563845 560357 614023 EPSG:3857:21 1019216 1127691 1120714 1228047 EPSG:3857:22 2038433 2255383 2241428 2456095 EPSG:3857:23 4076867 4510766 4482856 4912190 EPSG:3857:24 8153735 9021532 8965713 9824380 EPSG:3857:25 16307471 18043065 17931426 19648760 EPSG:3857:26 32614943 36086131 35862852 39297521 EPSG:3857:27 65229886 72172263 71725705 78595043 EPSG:3857:28 130459772 144344526 143451410 157190086 EPSG:3857:29 260919545 288689052 286902821 314380172 EPSG:3857:30 521839091 577378105 573805642 628760345 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 1 2 2 EPSG:4326:2 1 2 4 4 EPSG:4326:3 3 4 8 9 EPSG:4326:4 7 9 17 18 EPSG:4326:5 15 18 34 37 EPSG:4326:6 30 36 68 74 EPSG:4326:7 60 73 136 149 EPSG:4326:8 120 147 273 299 EPSG:4326:9 241 294 547 599 EPSG:4326:10 483 588 1094 1199 EPSG:4326:11 966 1177 2188 2398 EPSG:4326:12 1933 2354 4377 4797 EPSG:4326:13 3866 4708 8755 9594 EPSG:4326:14 7733 9416 17511 19188 EPSG:4326:15 15467 18833 35022 38376 EPSG:4326:16 30935 37667 70044 76752 EPSG:4326:17 61870 75334 140089 153505 EPSG:4326:18 123741 150668 280178 307011 EPSG:4326:19 247483 301336 560357 614023 EPSG:4326:20 494966 602672 1120714 1228047 EPSG:4326:21 989933 1205345 2241428 2456095 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 1 1 EPSG:3857:2 1 2 2 2 EPSG:3857:3 3 4 4 4 EPSG:3857:4 7 8 8 9 EPSG:3857:5 15 17 17 18 EPSG:3857:6 31 34 34 37 EPSG:3857:7 62 68 68 74 EPSG:3857:8 124 137 136 149 EPSG:3857:9 248 275 273 299 EPSG:3857:10 497 550 547 599 EPSG:3857:11 995 1101 1094 1199 EPSG:3857:12 1990 2202 2188 2398 EPSG:3857:13 3981 4405 4377 4797 EPSG:3857:14 7962 8810 8755 9594 EPSG:3857:15 15925 17620 17511 19188 EPSG:3857:16 31850 35240 35022 38376 EPSG:3857:17 63701 70480 70044 76752 EPSG:3857:18 127402 140961 140089 153505 EPSG:3857:19 254804 281922 280178 307011 EPSG:3857:20 509608 563845 560357 614023 EPSG:3857:21 1019216 1127691 1120714 1228047 EPSG:3857:22 2038433 2255383 2241428 2456095 EPSG:3857:23 4076867 4510766 4482856 4912190 EPSG:3857:24 8153735 9021532 8965713 9824380 EPSG:3857:25 16307471 18043065 17931426 19648760 EPSG:3857:26 32614943 36086131 35862852 39297521 EPSG:3857:27 65229886 72172263 71725705 78595043 EPSG:3857:28 130459772 144344526 143451410 157190086 EPSG:3857:29 260919545 288689052 286902821 314380172 EPSG:3857:30 521839091 577378105 573805642 628760345 Digital elevation model at 90m resolution - South Sudan This digitial elevation model (DEM) is derived from CGIAR-CSI SRTM v4.1 and ASTER GDEM v2 data products, and has been processed and mergedm inculding void-filling and smoothing of irregularities, to provide continuous coverage of ~91% of the globe.<br><br>For full processing and merging methodology see: <a href="https://www.sciencedirect.com/science/article/abs/pii/S0924271613002360"target="_blank">Robinson et al. (2014)</a>.<br/><br>Data can also be downloaded from <a href="http://www.earthenv.org/DEM"target="_blank">EarthEnv</a>. This specific layer is the cropped version by the South Sudan administrative boundaries of the global layer that is available at <a href="https://app.mapx.org?project=MX-XNI-RMZ-KKL-FMS-DVH&views=MX-AYR3I-HH9EC-LDLGC" target="_blank"> DEM90 - UnBiodiversityLab</a>. <br/><br> <br/><br>This data available under a <a href="https://creativecommons.org/licenses/by/4.0/"target="_blank">Creative Commons Attribution 4.0 International License</a> and is provided without any warranty of any kind whatsoever, either express or implied, including warranties of merchantability and fitness for a particular purpose. The creators of the product shall not be liable for incidental, consequential, or special damages arising out of the use of any data.<br/> 24.150833333259754 3.48750000002876 35.94749999992215 12.237500000025591 MAPX:SSD_dem90_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4016 4645 4914 EPSG:3857:14 7630 8033 9291 9828 EPSG:3857:15 15261 16066 18582 19656 EPSG:3857:16 30523 32132 37164 39312 EPSG:3857:17 61046 64265 74329 78624 EPSG:3857:18 122092 128530 148658 157248 EPSG:3857:19 244184 257061 297316 314496 EPSG:3857:20 488369 514123 594632 628992 EPSG:3857:21 976739 1028247 1189264 1257985 EPSG:3857:22 1953478 2056494 2378529 2515970 EPSG:3857:23 3906956 4112989 4757059 5031941 EPSG:3857:24 7813912 8225978 9514118 10063882 EPSG:3857:25 15627825 16451956 19028236 20127765 EPSG:3857:26 31255651 32903913 38056473 40255531 EPSG:3857:27 62511303 65807826 76112947 80511063 EPSG:3857:28 125022607 131615652 152225894 161022126 EPSG:3857:29 250045214 263231304 304451789 322044253 EPSG:3857:30 500090428 526462609 608903578 644088507 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 6 7 18 19 EPSG:4326:5 13 15 36 38 EPSG:4326:6 27 30 72 76 EPSG:4326:7 55 61 145 153 EPSG:4326:8 110 123 290 307 EPSG:4326:9 221 246 580 614 EPSG:4326:10 442 492 1161 1228 EPSG:4326:11 884 984 2322 2457 EPSG:4326:12 1769 1968 4645 4914 EPSG:4326:13 3539 3937 9291 9828 EPSG:4326:14 7078 7874 18582 19656 EPSG:4326:15 14156 15749 37164 39312 EPSG:4326:16 28312 31498 74329 78624 EPSG:4326:17 56624 62996 148658 157248 EPSG:4326:18 113249 125992 297316 314496 EPSG:4326:19 226499 251985 594632 628992 EPSG:4326:20 452999 503971 1189264 1257985 EPSG:4326:21 905998 1007943 2378529 2515970 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4016 4645 4914 EPSG:3857:14 7630 8033 9291 9828 EPSG:3857:15 15261 16066 18582 19656 EPSG:3857:16 30523 32132 37164 39312 EPSG:3857:17 61046 64265 74329 78624 EPSG:3857:18 122092 128530 148658 157248 EPSG:3857:19 244184 257061 297316 314496 EPSG:3857:20 488369 514123 594632 628992 EPSG:3857:21 976739 1028247 1189264 1257985 EPSG:3857:22 1953478 2056494 2378529 2515970 EPSG:3857:23 3906956 4112989 4757059 5031941 EPSG:3857:24 7813912 8225978 9514118 10063882 EPSG:3857:25 15627825 16451956 19028236 20127765 EPSG:3857:26 31255651 32903913 38056473 40255531 EPSG:3857:27 62511303 65807826 76112947 80511063 EPSG:3857:28 125022607 131615652 152225894 161022126 EPSG:3857:29 250045214 263231304 304451789 322044253 EPSG:3857:30 500090428 526462609 608903578 644088507 Combination Tsunami/Forest at global level - Others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Combination Tsunami/Mangroves at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tsu_man6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 tsm_col_zaragoza_20210309 -74.8651063820499 7.579889039548307 -74.7899249680916 7.640072688469066 rs_for_asgm:tsm_col_zaragoza_20210309 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 2 2 EPSG:4326:3 3 3 4 4 EPSG:4326:4 7 7 9 9 EPSG:4326:5 14 14 18 18 EPSG:4326:6 29 29 37 37 EPSG:4326:7 58 58 74 74 EPSG:4326:8 117 117 149 149 EPSG:4326:9 234 234 299 299 EPSG:4326:10 468 468 598 598 EPSG:4326:11 937 937 1196 1197 EPSG:4326:12 1874 1875 2392 2394 EPSG:4326:13 3748 3751 4784 4788 EPSG:4326:14 7496 7502 9569 9576 EPSG:4326:15 14993 15004 19139 19152 EPSG:4326:16 29986 30008 38278 38305 EPSG:4326:17 59972 60016 76556 76611 EPSG:4326:18 119945 120032 153113 153223 EPSG:4326:19 239890 240065 306227 306446 EPSG:4326:20 479781 480131 612455 612893 EPSG:4326:21 959562 960263 1224910 1225786 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 2 2 EPSG:3857:4 7 7 4 4 EPSG:3857:5 15 15 9 9 EPSG:3857:6 30 30 18 18 EPSG:3857:7 61 61 37 37 EPSG:3857:8 122 122 74 74 EPSG:3857:9 245 245 149 149 EPSG:3857:10 490 490 299 299 EPSG:3857:11 980 980 598 598 EPSG:3857:12 1960 1961 1196 1197 EPSG:3857:13 3921 3923 2392 2394 EPSG:3857:14 7843 7846 4784 4788 EPSG:3857:15 15686 15692 9569 9576 EPSG:3857:16 31373 31384 19139 19152 EPSG:3857:17 62746 62768 38278 38305 EPSG:3857:18 125492 125536 76556 76611 EPSG:3857:19 250984 251072 153113 153223 EPSG:3857:20 501968 502145 306227 306446 EPSG:3857:21 1003936 1004290 612455 612893 EPSG:3857:22 2007873 2008581 1224910 1225786 EPSG:3857:23 4015747 4017162 2449820 2451572 EPSG:3857:24 8031494 8034324 4899641 4903144 EPSG:3857:25 16062989 16068649 9799282 9806289 EPSG:3857:26 32125979 32137298 19598564 19612579 EPSG:3857:27 64251959 64274597 39197129 39225158 EPSG:3857:28 128503919 128549194 78394258 78450317 EPSG:3857:29 257007838 257098388 156788517 156900635 EPSG:3857:30 514015676 514196776 313577034 313801271 Combination Flood/Forest at global level - others -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_flo_for9_1112 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Temperature change trend (1991-2022) Trend of year temperatures change in '°C per year' across the period 1991-2022. Calculated at UNEP/GRID-Geneva in R based on CRU TS 4.07 data available <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/cruts.2304141047.v4.07/tmp/"target=_blank>here</a> <br> Read release notes of CRU TS 4.07 at <a href="https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/Release_Notes_CRU_TS_4.07.txt"target=_blank>this link</a> <br><br> Credits: <br> - <a href="https://sites.uea.ac.uk/cru/"target=_blank>Climatic Research Unit (University of East Anglia) and Met Office</a><br> - <a href="https://doi.org/10.1038/s41597-020-0453-3"target=_blank>Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset.Sci Data 7, 109 (2020).</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_tmp_91_22_lm image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Rivers -161.879 -49.7278 176.873 71.53 wesr_risk:rivers image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 3 10 0 15 EPSG:3857:5 6 21 1 31 EPSG:3857:6 13 42 3 63 EPSG:3857:7 26 84 6 126 EPSG:3857:8 53 168 12 253 EPSG:3857:9 107 337 25 507 EPSG:3857:10 215 675 51 1015 EPSG:3857:11 431 1351 103 2030 EPSG:3857:12 863 2702 206 4060 EPSG:3857:13 1727 5404 412 8120 EPSG:3857:14 3455 10808 824 16241 EPSG:3857:15 6910 21616 1649 32483 EPSG:3857:16 13821 43232 3298 64966 EPSG:3857:17 27642 86465 6597 129933 EPSG:3857:18 55284 172931 13195 259866 EPSG:3857:19 110568 345863 26390 519733 EPSG:3857:20 221137 691726 52781 1039467 EPSG:3857:21 442274 1383453 105562 2078935 EPSG:3857:22 884548 2766907 211124 4157871 EPSG:3857:23 1769097 5533815 422249 8315743 EPSG:3857:24 3538195 11067631 844499 16631487 EPSG:3857:25 7076390 22135262 1688999 33262974 EPSG:3857:26 14152780 44270525 3377999 66525948 EPSG:3857:27 28305561 88541051 6755998 133051897 EPSG:3857:28 56611123 177082102 13511996 266103795 EPSG:3857:29 113222246 354164204 27023993 532207591 EPSG:3857:30 226444493 708328409 54047987 1064415183 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 1 12 1 31 EPSG:4326:5 3 24 3 63 EPSG:4326:6 6 49 6 126 EPSG:4326:7 13 99 12 253 EPSG:4326:8 26 198 25 507 EPSG:4326:9 52 397 51 1015 EPSG:4326:10 105 794 103 2030 EPSG:4326:11 210 1589 206 4060 EPSG:4326:12 420 3179 412 8120 EPSG:4326:13 840 6359 824 16241 EPSG:4326:14 1681 12718 1649 32483 EPSG:4326:15 3362 25436 3298 64966 EPSG:4326:16 6724 50873 6597 129933 EPSG:4326:17 13449 101746 13195 259866 EPSG:4326:18 26898 203493 26390 519733 EPSG:4326:19 53797 406986 52781 1039467 EPSG:4326:20 107595 813973 105562 2078935 EPSG:4326:21 215191 1627946 211124 4157871 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 1 5 0 7 EPSG:3857:4 3 10 0 15 EPSG:3857:5 6 21 1 31 EPSG:3857:6 13 42 3 63 EPSG:3857:7 26 84 6 126 EPSG:3857:8 53 168 12 253 EPSG:3857:9 107 337 25 507 EPSG:3857:10 215 675 51 1015 EPSG:3857:11 431 1351 103 2030 EPSG:3857:12 863 2702 206 4060 EPSG:3857:13 1727 5404 412 8120 EPSG:3857:14 3455 10808 824 16241 EPSG:3857:15 6910 21616 1649 32483 EPSG:3857:16 13821 43232 3298 64966 EPSG:3857:17 27642 86465 6597 129933 EPSG:3857:18 55284 172931 13195 259866 EPSG:3857:19 110568 345863 26390 519733 EPSG:3857:20 221137 691726 52781 1039467 EPSG:3857:21 442274 1383453 105562 2078935 EPSG:3857:22 884548 2766907 211124 4157871 EPSG:3857:23 1769097 5533815 422249 8315743 EPSG:3857:24 3538195 11067631 844499 16631487 EPSG:3857:25 7076390 22135262 1688999 33262974 EPSG:3857:26 14152780 44270525 3377999 66525948 EPSG:3857:27 28305561 88541051 6755998 133051897 EPSG:3857:28 56611123 177082102 13511996 266103795 EPSG:3857:29 113222246 354164204 27023993 532207591 EPSG:3857:30 226444493 708328409 54047987 1064415183 Bare Soil Index in Keur Massar Senegal (2025) This layer shows the distribution of bare soil in Keur Massar (Dakar, Senegal) derived from Sentinel-2 imagery at 10 m spatial resolution. The satellite images were collected from Copernicus Browser (open access) on the 16th of April 2025. The Bare Soil Index (BSI) was calculated using the blue, red, near-infrared, and shortwave-infrared bands of Sentinel-2. Bare soil appears on the map starting from BSI values of 0.14, representing low bare soil presence, and gradually increases up to 0.3, representing high bare soil presence. This layer serves as an input for the project, providing baseline information on bare soil distribution to support the susceptibility assessment of illegal dumping sites. -17.382029187007333 14.733719739640827 -17.2719124771499 14.84106039798925 dakar_waste:BSI image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7508 7513 7400 7405 EPSG:3857:15 15017 15027 14801 14811 EPSG:3857:16 30035 30055 29603 29623 EPSG:3857:17 60071 60111 59207 59247 EPSG:3857:18 120142 120222 118414 118494 EPSG:3857:19 240284 240445 236829 236989 EPSG:3857:20 480568 480891 473659 473979 EPSG:3857:21 961137 961783 947318 947959 EPSG:3857:22 1922274 1923567 1894636 1895919 EPSG:3857:23 3844548 3847135 3789273 3791839 EPSG:3857:24 7689097 7694271 7578546 7583678 EPSG:3857:25 15378195 15388543 15157093 15167357 EPSG:3857:26 30756391 30777086 30314186 30334714 EPSG:3857:27 61512783 61554173 60628373 60669428 EPSG:3857:28 123025567 123108347 121256747 121338856 EPSG:3857:29 246051134 246216695 242513495 242677713 EPSG:3857:30 492102268 492433390 485026990 485355426 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 462 EPSG:4326:10 427 428 925 925 EPSG:4326:11 855 856 1850 1851 EPSG:4326:12 1710 1712 3700 3702 EPSG:4326:13 3420 3425 7400 7405 EPSG:4326:14 6841 6850 14801 14811 EPSG:4326:15 13682 13701 29603 29623 EPSG:4326:16 27364 27403 59207 59247 EPSG:4326:17 54729 54807 118414 118494 EPSG:4326:18 109458 109614 236829 236989 EPSG:4326:19 218916 219228 473659 473979 EPSG:4326:20 437832 438457 947318 947959 EPSG:4326:21 875665 876915 1894636 1895919 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7508 7513 7400 7405 EPSG:3857:15 15017 15027 14801 14811 EPSG:3857:16 30035 30055 29603 29623 EPSG:3857:17 60071 60111 59207 59247 EPSG:3857:18 120142 120222 118414 118494 EPSG:3857:19 240284 240445 236829 236989 EPSG:3857:20 480568 480891 473659 473979 EPSG:3857:21 961137 961783 947318 947959 EPSG:3857:22 1922274 1923567 1894636 1895919 EPSG:3857:23 3844548 3847135 3789273 3791839 EPSG:3857:24 7689097 7694271 7578546 7583678 EPSG:3857:25 15378195 15388543 15157093 15167357 EPSG:3857:26 30756391 30777086 30314186 30334714 EPSG:3857:27 61512783 61554173 60628373 60669428 EPSG:3857:28 123025567 123108347 121256747 121338856 EPSG:3857:29 246051134 246216695 242513495 242677713 EPSG:3857:30 492102268 492433390 485026990 485355426 Combination Tsunami/Coral reefs at global level - Protection -180.0 -90.0 180.0 90.0 ECO-DRR:GLO_tsu_cor6_46_P3 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Wetland Complexes (UNEP - 2018) Source: The map is published on UNEP's South Sudan: First State of Environment and Outlook Report 2018, using data from WCS. The UNEP's report could be found <a href="https://www.unenvironment.org/resources/report/south-sudan-first-state-environment-and-outlook-report-2018" target="_blank"> here </a> <br><br>The map shows the location and distribution of South Sudan’s principal wetlands, the most important of which are the Sudd and Machar swamps. 24.150695869 3.4874709339480017 35.950696484488 12.237471390348 MAPX_nd:SSD_Wetlands_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4016 4645 4914 EPSG:3857:14 7630 8033 9291 9828 EPSG:3857:15 15261 16066 18582 19656 EPSG:3857:16 30523 32132 37164 39312 EPSG:3857:17 61046 64265 74329 78625 EPSG:3857:18 122092 128530 148658 157250 EPSG:3857:19 244184 257061 297316 314500 EPSG:3857:20 488369 514123 594632 629001 EPSG:3857:21 976739 1028247 1189264 1258003 EPSG:3857:22 1953478 2056494 2378528 2516007 EPSG:3857:23 3906957 4112989 4757056 5032015 EPSG:3857:24 7813914 8225979 9514112 10064031 EPSG:3857:25 15627828 16451959 19028224 20128063 EPSG:3857:26 31255657 32903918 38056448 40256127 EPSG:3857:27 62511314 65807836 76112896 80512255 EPSG:3857:28 125022629 131615673 152225792 161024510 EPSG:3857:29 250045258 263231347 304451584 322049020 EPSG:3857:30 500090516 526462695 608903168 644098040 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 9 9 EPSG:4326:4 6 7 18 19 EPSG:4326:5 13 15 36 38 EPSG:4326:6 27 30 72 76 EPSG:4326:7 55 61 145 153 EPSG:4326:8 110 123 290 307 EPSG:4326:9 221 246 580 614 EPSG:4326:10 442 492 1161 1228 EPSG:4326:11 884 984 2322 2457 EPSG:4326:12 1769 1968 4645 4914 EPSG:4326:13 3539 3937 9291 9828 EPSG:4326:14 7078 7874 18582 19656 EPSG:4326:15 14156 15749 37164 39312 EPSG:4326:16 28312 31498 74329 78625 EPSG:4326:17 56624 62996 148658 157250 EPSG:4326:18 113249 125993 297316 314500 EPSG:4326:19 226499 251986 594632 629001 EPSG:4326:20 452999 503972 1189264 1258003 EPSG:4326:21 905999 1007944 2378528 2516007 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 9 9 EPSG:3857:5 14 15 18 19 EPSG:3857:6 29 31 36 38 EPSG:3857:7 59 62 72 76 EPSG:3857:8 119 125 145 153 EPSG:3857:9 238 251 290 307 EPSG:3857:10 476 502 580 614 EPSG:3857:11 953 1004 1161 1228 EPSG:3857:12 1907 2008 2322 2457 EPSG:3857:13 3815 4016 4645 4914 EPSG:3857:14 7630 8033 9291 9828 EPSG:3857:15 15261 16066 18582 19656 EPSG:3857:16 30523 32132 37164 39312 EPSG:3857:17 61046 64265 74329 78625 EPSG:3857:18 122092 128530 148658 157250 EPSG:3857:19 244184 257061 297316 314500 EPSG:3857:20 488369 514123 594632 629001 EPSG:3857:21 976739 1028247 1189264 1258003 EPSG:3857:22 1953478 2056494 2378528 2516007 EPSG:3857:23 3906957 4112989 4757056 5032015 EPSG:3857:24 7813914 8225979 9514112 10064031 EPSG:3857:25 15627828 16451959 19028224 20128063 EPSG:3857:26 31255657 32903918 38056448 40256127 EPSG:3857:27 62511314 65807836 76112896 80512255 EPSG:3857:28 125022629 131615673 152225792 161024510 EPSG:3857:29 250045258 263231347 304451584 322049020 EPSG:3857:30 500090516 526462695 608903168 644098040 GHS_POP_GPW42015 -179.99999680823143 -55.98302144283261 179.99218561802442 83.63964763391371 wesr_climat:GHS_POP_GPW42015 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 176 0 255 EPSG:3857:9 20 352 0 511 EPSG:3857:10 40 705 0 1023 EPSG:3857:11 81 1410 0 2047 EPSG:3857:12 163 2820 0 4095 EPSG:3857:13 327 5640 0 8191 EPSG:3857:14 655 11280 0 16383 EPSG:3857:15 1310 22561 0 32767 EPSG:3857:16 2621 45123 0 65534 EPSG:3857:17 5242 90246 0 131069 EPSG:3857:18 10485 180492 0 262138 EPSG:3857:19 20971 360984 0 524276 EPSG:3857:20 41943 721968 0 1048553 EPSG:3857:21 83886 1443936 0 2097106 EPSG:3857:22 167773 2887872 0 4194212 EPSG:3857:23 335547 5775744 0 8388425 EPSG:3857:24 671095 11551488 0 16776851 EPSG:3857:25 1342190 23102976 0 33553703 EPSG:3857:26 2684381 46205952 0 67107407 EPSG:3857:27 5368763 92411905 1 134214814 EPSG:3857:28 10737526 184823811 2 268429629 EPSG:3857:29 21475052 369647623 4 536859258 EPSG:3857:30 42950105 739295247 9 1073718516 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 12 0 31 EPSG:4326:5 1 25 0 63 EPSG:4326:6 2 51 0 127 EPSG:4326:7 4 103 0 255 EPSG:4326:8 9 207 0 511 EPSG:4326:9 18 415 0 1023 EPSG:4326:10 36 830 0 2047 EPSG:4326:11 72 1660 0 4095 EPSG:4326:12 144 3321 0 8191 EPSG:4326:13 289 6643 0 16383 EPSG:4326:14 578 13287 0 32767 EPSG:4326:15 1157 26575 0 65534 EPSG:4326:16 2315 53150 0 131069 EPSG:4326:17 4631 106301 0 262138 EPSG:4326:18 9262 212603 0 524276 EPSG:4326:19 18525 425206 0 1048553 EPSG:4326:20 37051 850412 0 2097106 EPSG:4326:21 74103 1700825 0 4194212 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 1 22 0 31 EPSG:3857:6 2 44 0 63 EPSG:3857:7 5 88 0 127 EPSG:3857:8 10 176 0 255 EPSG:3857:9 20 352 0 511 EPSG:3857:10 40 705 0 1023 EPSG:3857:11 81 1410 0 2047 EPSG:3857:12 163 2820 0 4095 EPSG:3857:13 327 5640 0 8191 EPSG:3857:14 655 11280 0 16383 EPSG:3857:15 1310 22561 0 32767 EPSG:3857:16 2621 45123 0 65534 EPSG:3857:17 5242 90246 0 131069 EPSG:3857:18 10485 180492 0 262138 EPSG:3857:19 20971 360984 0 524276 EPSG:3857:20 41943 721968 0 1048553 EPSG:3857:21 83886 1443936 0 2097106 EPSG:3857:22 167773 2887872 0 4194212 EPSG:3857:23 335547 5775744 0 8388425 EPSG:3857:24 671095 11551488 0 16776851 EPSG:3857:25 1342190 23102976 0 33553703 EPSG:3857:26 2684381 46205952 0 67107407 EPSG:3857:27 5368763 92411905 1 134214814 EPSG:3857:28 10737526 184823811 2 268429629 EPSG:3857:29 21475052 369647623 4 536859258 EPSG:3857:30 42950105 739295247 9 1073718516 Summer precipitations change (%) for the period 2080 - 2099 under the RCP 8.5 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_jja_ENDREF_rcp85_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 14 19 EPSG:4326:5 7 11 29 38 EPSG:4326:6 14 22 59 77 EPSG:4326:7 29 44 119 154 EPSG:4326:8 58 88 238 308 EPSG:4326:9 116 177 477 617 EPSG:4326:10 233 355 955 1234 EPSG:4326:11 466 711 1911 2468 EPSG:4326:12 932 1422 3822 4937 EPSG:4326:13 1865 2844 7645 9875 EPSG:4326:14 3731 5688 15291 19751 EPSG:4326:15 7463 11377 30583 39503 EPSG:4326:16 14927 22755 61166 79007 EPSG:4326:17 29855 45511 122333 158014 EPSG:4326:18 59710 91022 244667 316029 EPSG:4326:19 119421 182044 489335 632058 EPSG:4326:20 238842 364088 978670 1264116 EPSG:4326:21 477684 728177 1957341 2528233 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 5056466 EPSG:3857:24 5761666 7054770 7829367 10112932 EPSG:3857:25 11523333 14109541 15658734 20225865 EPSG:3857:26 23046667 28219082 31317469 40451731 EPSG:3857:27 46093335 56438164 62634939 80903463 EPSG:3857:28 92186671 112876329 125269879 161806927 EPSG:3857:29 184373343 225752659 250539758 323613855 EPSG:3857:30 368746687 451505318 501079517 647227710 Normalized Difference Water Index in Keur Massar Senegal This layer shows the distribution of water surfaces in Keur Massar (Dakar, Senegal) derived from Sentinel-2 imagery at 10 m spatial resolution. The satellite images were collected from Copernicus Browser (open access) on the 16th of April 2025. The Normalized Difference Water Index (NDWI) was calculated using the green and near-infrared bands of Sentinel-2. Water appears on the map starting from NDWI values of 0.01 (light blue), gradually increasing up to 0.38 (dark blue), representing areas with higher water presence. This layer serves as an input for a broader project, providing baseline information on water distribution to support the susceptibility assessment of illegal dumping sites. -17.382029187007333 14.733719739640827 -17.2719124771499 14.84106039798925 dakar_waste:NDWI image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7508 7513 7400 7405 EPSG:3857:15 15017 15027 14801 14811 EPSG:3857:16 30035 30055 29603 29623 EPSG:3857:17 60071 60111 59207 59247 EPSG:3857:18 120142 120222 118414 118494 EPSG:3857:19 240284 240445 236829 236989 EPSG:3857:20 480568 480891 473659 473979 EPSG:3857:21 961137 961783 947318 947959 EPSG:3857:22 1922274 1923567 1894636 1895919 EPSG:3857:23 3844548 3847135 3789273 3791839 EPSG:3857:24 7689097 7694271 7578546 7583678 EPSG:3857:25 15378195 15388543 15157093 15167357 EPSG:3857:26 30756391 30777086 30314186 30334714 EPSG:3857:27 61512783 61554173 60628373 60669428 EPSG:3857:28 123025567 123108347 121256747 121338856 EPSG:3857:29 246051134 246216695 242513495 242677713 EPSG:3857:30 492102268 492433390 485026990 485355426 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 28 28 EPSG:4326:6 26 26 57 57 EPSG:4326:7 53 53 115 115 EPSG:4326:8 106 107 231 231 EPSG:4326:9 213 214 462 462 EPSG:4326:10 427 428 925 925 EPSG:4326:11 855 856 1850 1851 EPSG:4326:12 1710 1712 3700 3702 EPSG:4326:13 3420 3425 7400 7405 EPSG:4326:14 6841 6850 14801 14811 EPSG:4326:15 13682 13701 29603 29623 EPSG:4326:16 27364 27403 59207 59247 EPSG:4326:17 54729 54807 118414 118494 EPSG:4326:18 109458 109614 236829 236989 EPSG:4326:19 218916 219228 473659 473979 EPSG:4326:20 437832 438457 947318 947959 EPSG:4326:21 875665 876915 1894636 1895919 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 28 28 EPSG:3857:7 58 58 57 57 EPSG:3857:8 117 117 115 115 EPSG:3857:9 234 234 231 231 EPSG:3857:10 469 469 462 462 EPSG:3857:11 938 939 925 925 EPSG:3857:12 1877 1878 1850 1851 EPSG:3857:13 3754 3756 3700 3702 EPSG:3857:14 7508 7513 7400 7405 EPSG:3857:15 15017 15027 14801 14811 EPSG:3857:16 30035 30055 29603 29623 EPSG:3857:17 60071 60111 59207 59247 EPSG:3857:18 120142 120222 118414 118494 EPSG:3857:19 240284 240445 236829 236989 EPSG:3857:20 480568 480891 473659 473979 EPSG:3857:21 961137 961783 947318 947959 EPSG:3857:22 1922274 1923567 1894636 1895919 EPSG:3857:23 3844548 3847135 3789273 3791839 EPSG:3857:24 7689097 7694271 7578546 7583678 EPSG:3857:25 15378195 15388543 15157093 15167357 EPSG:3857:26 30756391 30777086 30314186 30334714 EPSG:3857:27 61512783 61554173 60628373 60669428 EPSG:3857:28 123025567 123108347 121256747 121338856 EPSG:3857:29 246051134 246216695 242513495 242677713 EPSG:3857:30 492102268 492433390 485026990 485355426 Earthquakes PGA GSHAP (m/s2) -180.0 -65.0 180.0 90.0 wesr_risk:gshap image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 378 0 511 EPSG:3857:10 0 757 0 1023 EPSG:3857:11 0 1515 0 2047 EPSG:3857:12 0 3030 0 4095 EPSG:3857:13 0 6060 0 8191 EPSG:3857:14 0 12120 0 16383 EPSG:3857:15 0 24240 0 32767 EPSG:3857:16 0 48480 0 65535 EPSG:3857:17 0 96961 0 131071 EPSG:3857:18 0 193923 0 262143 EPSG:3857:19 0 387847 0 524287 EPSG:3857:20 0 775694 0 1048575 EPSG:3857:21 0 1551388 0 2097151 EPSG:3857:22 -1 3102776 0 4194304 EPSG:3857:23 -1 6205553 0 8388608 EPSG:3857:24 0 12411107 0 16777215 EPSG:3857:25 0 24822214 0 33554431 EPSG:3857:26 0 49644428 0 67108863 EPSG:3857:27 0 99288857 0 134217727 EPSG:3857:28 -1 198577715 0 268435456 EPSG:3857:29 0 397155431 0 536870911 EPSG:3857:30 0 794310863 0 1073741823 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 55 0 127 EPSG:4326:7 0 110 0 255 EPSG:4326:8 0 220 0 511 EPSG:4326:9 0 440 0 1023 EPSG:4326:10 0 881 0 2047 EPSG:4326:11 0 1763 0 4095 EPSG:4326:12 0 3527 0 8191 EPSG:4326:13 0 7054 0 16383 EPSG:4326:14 0 14108 0 32767 EPSG:4326:15 0 28216 0 65535 EPSG:4326:16 0 56433 0 131071 EPSG:4326:17 0 112867 0 262143 EPSG:4326:18 0 225735 0 524287 EPSG:4326:19 0 451470 0 1048575 EPSG:4326:20 0 902940 0 2097151 EPSG:4326:21 0 1805880 0 4194303 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 378 0 511 EPSG:3857:10 0 757 0 1023 EPSG:3857:11 0 1515 0 2047 EPSG:3857:12 0 3030 0 4095 EPSG:3857:13 0 6060 0 8191 EPSG:3857:14 0 12120 0 16383 EPSG:3857:15 0 24240 0 32767 EPSG:3857:16 0 48480 0 65535 EPSG:3857:17 0 96961 0 131071 EPSG:3857:18 0 193923 0 262143 EPSG:3857:19 0 387847 0 524287 EPSG:3857:20 0 775694 0 1048575 EPSG:3857:21 -1 1551388 0 2097152 EPSG:3857:22 -1 3102776 0 4194304 EPSG:3857:23 0 6205553 0 8388607 EPSG:3857:24 0 12411107 0 16777215 EPSG:3857:25 0 24822214 0 33554431 EPSG:3857:26 0 49644428 0 67108863 EPSG:3857:27 -1 99288857 0 134217728 EPSG:3857:28 0 198577715 0 268435455 EPSG:3857:29 0 397155431 0 536870911 EPSG:3857:30 -1 794310863 0 1073741824 Drought vulnerability recurrence map between 1995 and 2024 Cultivated and densely populated areas in the Kédougou region are particularly vulnerable to drought due to the intense pressure on water resources and soil quality. In this area, intensive agriculture, often practiced without appropriate rotations or soil conservation measures, leads to a degradation of soil structure and a reduction in its moisture retention capacity. At the same time, high population density increases water demand for domestic and agricultural uses, which, combined with increasingly erratic rainfall patterns due to climate change, exacerbates water stress. These combined socioeconomic and environmental factors make these areas particularly susceptible to drought. -13.243602482435989 12.296668462171974 -11.336189526734906 13.472239258295431 risk_southeast_senegal:drought_vulnerability image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60585 61024 60714 61408 EPSG:3857:18 121170 122048 121428 122817 EPSG:3857:19 242340 244096 242856 245634 EPSG:3857:20 484680 488193 485713 491268 EPSG:3857:21 969361 976386 971426 982537 EPSG:3857:22 1938722 1952772 1942852 1965075 EPSG:3857:23 3877444 3905545 3885705 3930151 EPSG:3857:24 7754889 7811091 7771411 7860303 EPSG:3857:25 15509778 15622182 15542822 15720606 EPSG:3857:26 31019557 31244364 31085645 31441213 EPSG:3857:27 62039115 62488728 62171291 62882426 EPSG:3857:28 124078230 124977457 124342582 125764852 EPSG:3857:29 248156460 249954914 248685164 251529704 EPSG:3857:30 496312920 499909828 497370328 503059409 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 221 474 479 EPSG:4326:10 435 442 948 959 EPSG:4326:11 870 884 1897 1919 EPSG:4326:12 1741 1768 3794 3838 EPSG:4326:13 3482 3536 7589 7676 EPSG:4326:14 6965 7072 15178 15352 EPSG:4326:15 13931 14145 30357 30704 EPSG:4326:16 27862 28290 60714 61408 EPSG:4326:17 55725 56581 121428 122817 EPSG:4326:18 111451 113163 242856 245634 EPSG:4326:19 222903 226327 485713 491268 EPSG:4326:20 445806 452654 971426 982537 EPSG:4326:21 891613 905309 1942852 1965075 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1907 1897 1919 EPSG:3857:13 3786 3814 3794 3838 EPSG:3857:14 7573 7628 7589 7676 EPSG:3857:15 15146 15256 15178 15352 EPSG:3857:16 30292 30512 30357 30704 EPSG:3857:17 60585 61024 60714 61408 EPSG:3857:18 121170 122048 121428 122817 EPSG:3857:19 242340 244096 242856 245634 EPSG:3857:20 484680 488193 485713 491268 EPSG:3857:21 969361 976386 971426 982537 EPSG:3857:22 1938722 1952772 1942852 1965075 EPSG:3857:23 3877444 3905545 3885705 3930151 EPSG:3857:24 7754889 7811091 7771411 7860303 EPSG:3857:25 15509778 15622182 15542822 15720606 EPSG:3857:26 31019557 31244364 31085645 31441213 EPSG:3857:27 62039115 62488728 62171291 62882426 EPSG:3857:28 124078230 124977457 124342582 125764852 EPSG:3857:29 248156460 249954914 248685164 251529704 EPSG:3857:30 496312920 499909828 497370328 503059409 Landslide hazard exposure -180.0 -90.0 180.0 90.0 ECO-DRR:ls_phex image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 L8_mosaic 5.7348574 45.675510856 10.667580872 47.916276664 sdc_test:L8_mosaic image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 2 4 4 EPSG:3857:4 5 5 8 8 EPSG:3857:5 11 11 16 16 EPSG:3857:6 22 22 33 33 EPSG:3857:7 44 45 66 67 EPSG:3857:8 89 91 132 135 EPSG:3857:9 178 182 264 271 EPSG:3857:10 356 365 528 542 EPSG:3857:11 712 731 1056 1084 EPSG:3857:12 1425 1462 2113 2169 EPSG:3857:13 2850 2924 4226 4338 EPSG:3857:14 5701 5849 8452 8677 EPSG:3857:15 11402 11699 16905 17354 EPSG:3857:16 22804 23399 33811 34709 EPSG:3857:17 45608 46799 67623 69419 EPSG:3857:18 91216 93599 135247 138839 EPSG:3857:19 182432 187199 270495 277679 EPSG:3857:20 364864 374399 540991 555359 EPSG:3857:21 729728 748799 1081983 1110719 EPSG:3857:22 1459457 1497599 2163967 2221438 EPSG:3857:23 2918914 2995199 4327935 4442876 EPSG:3857:24 5837828 5990398 8655871 8885753 EPSG:3857:25 11675657 11980796 17311743 17771506 EPSG:3857:26 23351314 23961592 34623486 35543013 EPSG:3857:27 46702628 47923184 69246973 71086026 EPSG:3857:28 93405256 95846369 138493947 142172052 EPSG:3857:29 186810513 191692738 276987895 284344105 EPSG:3857:30 373621026 383385477 553975790 568688211 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 0 0 4 4 EPSG:4326:3 1 1 8 8 EPSG:4326:4 3 3 16 16 EPSG:4326:5 7 7 33 33 EPSG:4326:6 14 15 66 67 EPSG:4326:7 29 31 132 135 EPSG:4326:8 59 63 264 271 EPSG:4326:9 119 126 528 542 EPSG:4326:10 239 252 1056 1084 EPSG:4326:11 478 504 2113 2169 EPSG:4326:12 957 1008 4226 4338 EPSG:4326:13 1915 2017 8452 8677 EPSG:4326:14 3830 4034 16905 17354 EPSG:4326:15 7661 8069 33811 34709 EPSG:4326:16 15322 16138 67623 69419 EPSG:4326:17 30644 32276 135247 138839 EPSG:4326:18 61288 64552 270495 277679 EPSG:4326:19 122577 129104 540991 555359 EPSG:4326:20 245155 258208 1081983 1110719 EPSG:4326:21 490310 516417 2163967 2221438 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 2 2 4 4 EPSG:3857:4 5 5 8 8 EPSG:3857:5 11 11 16 16 EPSG:3857:6 22 22 33 33 EPSG:3857:7 44 45 66 67 EPSG:3857:8 89 91 132 135 EPSG:3857:9 178 182 264 271 EPSG:3857:10 356 365 528 542 EPSG:3857:11 712 731 1056 1084 EPSG:3857:12 1425 1462 2113 2169 EPSG:3857:13 2850 2924 4226 4338 EPSG:3857:14 5701 5849 8452 8677 EPSG:3857:15 11402 11699 16905 17354 EPSG:3857:16 22804 23399 33811 34709 EPSG:3857:17 45608 46799 67623 69419 EPSG:3857:18 91216 93599 135247 138839 EPSG:3857:19 182432 187199 270495 277679 EPSG:3857:20 364864 374399 540991 555359 EPSG:3857:21 729728 748799 1081983 1110719 EPSG:3857:22 1459457 1497599 2163967 2221438 EPSG:3857:23 2918914 2995199 4327935 4442876 EPSG:3857:24 5837828 5990398 8655871 8885753 EPSG:3857:25 11675657 11980796 17311743 17771506 EPSG:3857:26 23351314 23961592 34623486 35543013 EPSG:3857:27 46702628 47923184 69246973 71086026 EPSG:3857:28 93405256 95846369 138493947 142172052 EPSG:3857:29 186810513 191692738 276987895 284344105 EPSG:3857:30 373621026 383385477 553975790 568688211 Combination Tropical cyclone surge/ Coral reefs at national level - Restoration -180.0 -90.0 180.0 90.0 ECO-DRR:NAT_tcs_cor6_13 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 Albedo Summer 2019 (Copernicus) Unit: ratio of the solar radiation reflected by a surface to the total incoming solar radiation, usually measured between 0 (all incident radiation absorbed) and 1 (all incident radiation refleted). Surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. The present layer represents the black-sky albedo (directional albedo), which is considered as an Essential Climate Variable by the Global Climate Observing System (GCOS). Surface albedo is a sensitive indicator of environmental vulnerability making it a key element required by climate, biogeochemical, hydrological, and weather forecast models. It has a spatial resolution of 1km and is available from the Copernicus Global Land Service (https://land.copernicus.eu/global/products/sa) as netCDF files (technical documentation available at https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_PUM_SA1km-V1_I1.40.pdf. The present raster is the broadband directional albedo over full spectrum [0.3-4µm]. It is the average of the various albedo files available in summer 2019 (3 June 2019, 13 June 2019, 23 June 2019, 3 July 2019, 13 July 2019, 24 July 2019, 3 August 2019, 13 August 2019 et 24 August 2019), then transformed into a geotiff in order to display and example of albedo reflectance in summer. -180.0 -59.995535714253904 179.9955357142039 80.00446428571429 wesr_mountains:c_gls_ALDH_2019_ete_raster_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 1 11 0 15 EPSG:3857:5 3 22 0 31 EPSG:3857:6 7 45 0 63 EPSG:3857:7 14 90 0 127 EPSG:3857:8 28 181 0 255 EPSG:3857:9 57 363 0 511 EPSG:3857:10 114 726 0 1023 EPSG:3857:11 229 1453 0 2047 EPSG:3857:12 459 2906 0 4095 EPSG:3857:13 919 5812 0 8191 EPSG:3857:14 1838 11625 0 16383 EPSG:3857:15 3676 23251 0 32767 EPSG:3857:16 7352 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EPSG:3857:30 41995652 739298331 0 1073738841 Precipitation anomalies (mm) 2081-2100 (RCP4.5) Yearly precipitation anomalies (mm) for the period 2081-2100 based on the climate scenario RCP4.5 (reference 1986-2005). -26.619999885559082 -6.819999933242798 75.4600133895874 45.10000681877136 Medicip:pr_45_81_00 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 1 2 1 2 EPSG:3857:3 2 4 3 5 EPSG:3857:4 5 8 6 11 EPSG:3857:5 11 16 13 22 EPSG:3857:6 22 33 27 45 EPSG:3857:7 45 66 54 90 EPSG:3857:8 91 132 109 181 EPSG:3857:9 183 265 218 363 EPSG:3857:10 367 531 436 726 EPSG:3857:11 735 1062 872 1453 EPSG:3857:12 1471 2125 1745 2906 EPSG:3857:13 2943 4251 3490 5813 EPSG:3857:14 5887 8503 6980 11626 EPSG:3857:15 11774 17006 13960 23252 EPSG:3857:16 23549 34012 27921 46505 EPSG:3857:17 47098 68024 55843 93010 EPSG:3857:18 94196 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EPSG:3857:18 99631 114426 172918 189776 EPSG:3857:19 199262 228853 345837 379553 EPSG:3857:20 398524 457706 691674 759106 EPSG:3857:21 797048 915412 1383349 1518213 EPSG:3857:22 1594096 1830824 2766699 3036427 EPSG:3857:23 3188192 3661649 5533398 6072854 EPSG:3857:24 6376384 7323299 11066796 12145708 EPSG:3857:25 12752769 14646599 22133593 24291416 EPSG:3857:26 25505539 29293199 44267187 48582832 EPSG:3857:27 51011079 58586399 88534374 97165665 EPSG:3857:28 102022158 117172798 177068749 194331331 EPSG:3857:29 204044317 234345597 354137498 388662663 EPSG:3857:30 408088634 468691195 708274996 777325326 Annual Mean Temperature [°C/10] (2041-2060) RCP8.5 - CIMP5 Mean annual daily mean air temperatures averaged over 1 year [°C/10] for the period 2041-2060 based on RCP8.5. CHELSA-[CMIP5] is a delta change climatological dataset for the years 2041-2060 and 2061- 2080 for mean monthly maximum temperatures, mean monthly minimum temperatures, monthly precipitation amounts, and several derived parameters. We use the delta change method by B-spline interpolation of anomalies (deltas) of the respective CMIP5 GCM dataset. Anomalies were interpolated between all CMIP5 grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2. This method has the assumption that climate only varies on the scale of the coarser (CMIP5) dataset, and the spatial pattern (from CHELSA) is consistent over time. CHELSA- [CMIP5] does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages. CHELSA V1.2 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. Methods are described in http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf. CHELSA Version 1.2 is licensed under a Creative Commons Attribution 4.0 International License. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Climatologies for the years 1979 – 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). All products of CHELSA are in a geographic coordinate system referenced to the WGS 84 horizontal datum, with the horizontal coordinates expressed in decimal degrees. The CHELSA layer extents (minimum and maximum latitude and longitude) are a result of the coordinate system inherited from the 1-arc-second GMTED2010 data which itself inherited the grid extent from the 1-arc-second SRTM data. Note that because of the pixel center referencing of the input GMTED2010 data the full extent of each CHELSA grid as defined by the outside edges of the pixels differs from an integer value of latitude or longitude by 0.000138888888 degree (or 1/2 arc-second). Users of products based on the legacy GTOPO30 product should note that the coordinate referencing of CHELSA (and GMTED2010) and GTOPO30 are not the same. In GTOPO30, the integer lines of latitude and longitude fall directly on the edges of a 30-arc-second pixel. Thus, when overlaying CHELSA with products based on GTOPO30 a slight shift of 1/2 arc-second will be observed between the edges of corresponding 30-arc-second pixels. To redistribute the data, please cite the following peer reviewed articles: <a href="https://www.nature.com/articles/sdata2017122"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.</a> <a href="https://doi.org/10.5061/dryad.kd1d4"target=_blank>Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. (2017) Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. </a> CHELSA – Climatologies at high resolution for the Earth land surface areas. 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EPSG:3857:28 130406129 137752529 159459707 165477401 EPSG:3857:29 260812258 275505058 318919414 330954802 EPSG:3857:30 521624517 551010116 637838828 661909605 Degraded lands of Peru Layer provided by Ministry of Environment of Peru. Land degradation is the long-term loss of ecosystem function and services, caused by disturbances from which the system cannot recover unaided. he following link has information on the methodology used to produce the national map pf degradation. https://geoservidor.minam.gob.pe/wp-content/uploads/2017/06/Estudio-Identificaci%C3%B3n-de-%C3%81reas-Degradadas.pdf SDG Goal 15. Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss. -82.811770420087 -19.050723822685583 -67.70058473717306 0.5435574567185314 wesr_cca:Degraded lands image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 17 8 9 EPSG:3857:6 31 35 17 19 EPSG:3857:7 63 70 34 39 EPSG:3857:8 127 141 69 79 EPSG:3857:9 255 283 138 159 EPSG:3857:10 510 567 276 319 EPSG:3857:11 1020 1134 552 638 EPSG:3857:12 2041 2268 1105 1277 EPSG:3857:13 4083 4537 2211 2555 EPSG:3857:14 8167 9075 4423 5110 EPSG:3857:15 16334 18150 8846 10221 EPSG:3857:16 32669 36301 17692 20443 EPSG:3857:17 65338 72603 35385 40886 EPSG:3857:18 130676 145207 70770 81773 EPSG:3857:19 261352 290414 141540 163547 EPSG:3857:20 522704 580828 283081 327095 EPSG:3857:21 1045409 1161657 566162 654191 EPSG:3857:22 2090819 2323315 1132324 1308383 EPSG:3857:23 4181638 4646631 2264649 2616766 EPSG:3857:24 8363276 9293262 4529299 5233532 EPSG:3857:25 16726552 18586524 9058599 10467064 EPSG:3857:26 33453104 37173048 18117199 20934128 EPSG:3857:27 66906208 74346097 36234398 41868256 EPSG:3857:28 133812416 148692195 72468796 83736513 EPSG:3857:29 267624832 297384390 144937592 167473026 EPSG:3857:30 535249664 594768781 289875185 334946052 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 1 1 1 EPSG:4326:2 1 2 2 2 EPSG:4326:3 3 4 4 4 EPSG:4326:4 7 9 8 9 EPSG:4326:5 15 19 17 19 EPSG:4326:6 31 38 34 39 EPSG:4326:7 63 77 69 79 EPSG:4326:8 127 155 138 159 EPSG:4326:9 254 310 276 319 EPSG:4326:10 508 620 552 638 EPSG:4326:11 1017 1240 1105 1277 EPSG:4326:12 2035 2481 2211 2555 EPSG:4326:13 4071 4963 4423 5110 EPSG:4326:14 8142 9926 8846 10221 EPSG:4326:15 16285 19852 17692 20443 EPSG:4326:16 32570 39704 35385 40886 EPSG:4326:17 65140 79408 70770 81773 EPSG:4326:18 130280 158816 141540 163547 EPSG:4326:19 260560 317633 283081 327095 EPSG:4326:20 521121 635266 566162 654191 EPSG:4326:21 1042243 1270533 1132324 1308383 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 0 EPSG:3857:2 1 2 1 1 EPSG:3857:3 3 4 2 2 EPSG:3857:4 7 8 4 4 EPSG:3857:5 15 17 8 9 EPSG:3857:6 31 35 17 19 EPSG:3857:7 63 70 34 39 EPSG:3857:8 127 141 69 79 EPSG:3857:9 255 283 138 159 EPSG:3857:10 510 567 276 319 EPSG:3857:11 1020 1134 552 638 EPSG:3857:12 2041 2268 1105 1277 EPSG:3857:13 4083 4537 2211 2555 EPSG:3857:14 8167 9075 4423 5110 EPSG:3857:15 16334 18150 8846 10221 EPSG:3857:16 32669 36301 17692 20443 EPSG:3857:17 65338 72603 35385 40886 EPSG:3857:18 130676 145207 70770 81773 EPSG:3857:19 261352 290414 141540 163547 EPSG:3857:20 522704 580828 283081 327095 EPSG:3857:21 1045409 1161657 566162 654191 EPSG:3857:22 2090819 2323315 1132324 1308383 EPSG:3857:23 4181638 4646631 2264649 2616766 EPSG:3857:24 8363276 9293262 4529299 5233532 EPSG:3857:25 16726552 18586524 9058599 10467064 EPSG:3857:26 33453104 37173048 18117199 20934128 EPSG:3857:27 66906208 74346097 36234398 41868256 EPSG:3857:28 133812416 148692195 72468796 83736513 EPSG:3857:29 267624832 297384390 144937592 167473026 EPSG:3857:30 535249664 594768781 289875185 334946052 Historical Generalized Difference Vegetation Index of emerging Northwest Mining Region of Ghana (1990) The Generalized Normalised Difference Vegetation Index (GNDVI) is a modification of the Normalised Difference Vegetation Index (NDVI), which has been proposed by Weicheng Wu (2014) for the assessment of dryland environments due to the inadequacy of the NDVI in these areas. Indeed, this has been very appropriate and effective in mapping the vegetative cover of the Northwest region of Ghana, which is a semi-arid zone. The GNDVI of 1990 seeks to validate the land cover patterns that existed in the area with regard to biodiversity and land use. This data sets the baseline analysis of the emerging Northwest mining region of Ghana, which would enhance the monitoring of sustainable mining -2.941804951 9.626453977 -1.42736896 11.030613419 MAPX:GHA_GNDVI1990 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 7 7 15 15 EPSG:4326:5 14 14 31 31 EPSG:4326:6 28 28 62 63 EPSG:4326:7 56 57 125 126 EPSG:4326:8 112 114 251 253 EPSG:4326:9 224 228 503 507 EPSG:4326:10 449 457 1007 1015 EPSG:4326:11 898 914 2014 2031 EPSG:4326:12 1796 1828 4029 4063 EPSG:4326:13 3593 3657 8058 8127 EPSG:4326:14 7187 7315 16116 16254 EPSG:4326:15 14375 14631 32232 32508 EPSG:4326:16 28751 29263 64464 65016 EPSG:4326:17 57503 58526 128929 130032 EPSG:4326:18 115007 117052 257859 260065 EPSG:4326:19 230015 234104 515719 520130 EPSG:4326:20 460030 468209 1031438 1040260 EPSG:4326:21 920060 936419 2062877 2080521 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 15 15 15 15 EPSG:3857:6 30 30 31 31 EPSG:3857:7 60 60 62 63 EPSG:3857:8 120 121 125 126 EPSG:3857:9 240 242 251 253 EPSG:3857:10 480 484 503 507 EPSG:3857:11 960 968 1007 1015 EPSG:3857:12 1921 1937 2014 2031 EPSG:3857:13 3843 3875 4029 4063 EPSG:3857:14 7686 7751 8058 8127 EPSG:3857:15 15373 15503 16116 16254 EPSG:3857:16 30747 31007 32232 32508 EPSG:3857:17 61494 62014 64464 65016 EPSG:3857:18 122989 124029 128929 130032 EPSG:3857:19 245979 248058 257859 260065 EPSG:3857:20 491958 496116 515719 520130 EPSG:3857:21 983917 992232 1031438 1040260 EPSG:3857:22 1967834 1984464 2062877 2080521 EPSG:3857:23 3935669 3968928 4125754 4161043 EPSG:3857:24 7871338 7937857 8251509 8322087 EPSG:3857:25 15742677 15875714 16503019 16644175 EPSG:3857:26 31485355 31751428 33006039 33288351 EPSG:3857:27 62970710 63502856 66012079 66576702 EPSG:3857:28 125941421 127005712 132024159 133153404 EPSG:3857:29 251882843 254011425 264048318 266306809 EPSG:3857:30 503765686 508022850 528096636 532613618 Spatial distribution of forest fire risk This risk related to forest fires is defined by the interaction between the inherent danger posed by fires and the vulnerability of ecosystems and local populations. On the one hand, global warming, characterized by rising temperatures and decreasing precipitation, promotes the drying out of vegetation and the accumulation of dry biomass, thus creating an ideal fuel for the outbreak and spread of fires (Mbow, 2003). On the other hand, human practices, such as burning land for field preparation and charcoal production, reinforced by increasing population pressure, increase the probability of uncontrolled fire outbreaks (Benoit, 1998). -13.239460488881921 12.307817707721565 -11.342398271878317 13.461074869474206 risk_southeast_senegal:burn_risk image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242357 244079 242862 245625 EPSG:3857:20 484714 488159 485725 491250 EPSG:3857:21 969428 976319 971450 982501 EPSG:3857:22 1938856 1952639 1942901 1965003 EPSG:3857:23 3877712 3905279 3885802 3930006 EPSG:3857:24 7755424 7810559 7771604 7860013 EPSG:3857:25 15510848 15621118 15543208 15720027 EPSG:3857:26 31021697 31242237 31086417 31440055 EPSG:3857:27 62043395 62484474 62172835 62880111 EPSG:3857:28 124086790 124968948 124345670 125760222 EPSG:3857:29 248173580 249937896 248691341 251520445 EPSG:3857:30 496347160 499875793 497382682 503040891 EPSG:4326 EPSG:4326:0 0 0 0 0 EPSG:4326:1 0 0 1 1 EPSG:4326:2 1 1 3 3 EPSG:4326:3 3 3 7 7 EPSG:4326:4 6 6 14 14 EPSG:4326:5 13 13 29 29 EPSG:4326:6 27 27 59 59 EPSG:4326:7 54 55 118 119 EPSG:4326:8 108 110 237 239 EPSG:4326:9 217 220 474 479 EPSG:4326:10 435 441 948 959 EPSG:4326:11 870 883 1897 1918 EPSG:4326:12 1741 1767 3794 3837 EPSG:4326:13 3483 3535 7589 7675 EPSG:4326:14 6966 7071 15178 15351 EPSG:4326:15 13933 14143 30357 30703 EPSG:4326:16 27866 28286 60715 61406 EPSG:4326:17 55733 56573 121431 122812 EPSG:4326:18 111467 113147 242862 245625 EPSG:4326:19 222935 226294 485725 491250 EPSG:4326:20 445871 452589 971450 982501 EPSG:4326:21 891743 905179 1942901 1965003 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 0 EPSG:3857:2 1 1 1 1 EPSG:3857:3 3 3 3 3 EPSG:3857:4 7 7 7 7 EPSG:3857:5 14 14 14 14 EPSG:3857:6 29 29 29 29 EPSG:3857:7 59 59 59 59 EPSG:3857:8 118 119 118 119 EPSG:3857:9 236 238 237 239 EPSG:3857:10 473 476 474 479 EPSG:3857:11 946 953 948 959 EPSG:3857:12 1893 1906 1897 1918 EPSG:3857:13 3786 3813 3794 3837 EPSG:3857:14 7573 7627 7589 7675 EPSG:3857:15 15147 15254 15178 15351 EPSG:3857:16 30294 30509 30357 30703 EPSG:3857:17 60589 61019 60715 61406 EPSG:3857:18 121178 122039 121431 122812 EPSG:3857:19 242357 244079 242862 245625 EPSG:3857:20 484714 488159 485725 491250 EPSG:3857:21 969428 976319 971450 982501 EPSG:3857:22 1938856 1952639 1942901 1965003 EPSG:3857:23 3877712 3905279 3885802 3930006 EPSG:3857:24 7755424 7810559 7771604 7860013 EPSG:3857:25 15510848 15621118 15543208 15720027 EPSG:3857:26 31021697 31242237 31086417 31440055 EPSG:3857:27 62043395 62484474 62172835 62880111 EPSG:3857:28 124086790 124968948 124345670 125760222 EPSG:3857:29 248173580 249937896 248691341 251520445 EPSG:3857:30 496347160 499875793 497382682 503040891 Self-calibrating Palmer Drought Severity Index (scPDSI) 2011 (CRU) This layer shows the average values for 2011 of the Self-calibrating Palmer Drought Severity Index (scPDSI), based on the scPDSI dataset provided by the Climatic Research Unit (CRU) that cover the time interval from 1901. Original data were subset and processed using R at UNEP/GRID-Geneva.<br><br> The scPSDI indicates the degree of drought severity (negative values means higher severity) based on climatic and environmental parameters. The scPDSI metric was introduced by Wells et al. (2004), who give detailed information about its calculation. The scPDSI is a variant on the original PDSI of Palmer (1965), with the aim to make results from different climate regimes more comparable. As with the PDSI, the scPDSI is calculated from time series of precipitation and temperature, together with fixed parameters related to the soil/surface characteristics at each location. <br><br> Version: preliminary CRU TS 4.07, 0.5° lat-lon resolution <br><br> (Dataset method) van der Schrier G, Barichivich J, Briffa KR and Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901-2009. J. Geophys. Res. Atmos. 118, 4025-4048 (10.1002/jgrd.50355).<br> (1901-2021 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2022) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in “State of the Climate in 2021“]. Bull. Amer. Meteor. Soc., 103 (8), S31–S33, (https://doi.org/10.1175/BAMS-D-22-0092.1).<br> (1901-2020 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2021) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2020" eds. Dunn RJH, Aldred F, Gobron N, Miller JB & Willett KM]. Bulletin of the American Meteorological Society 102, S68-S70. (https://doi.org/10.1175/BAMS-D-21-0098.1)<br> (1901-2019 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2020) Drought [in "State of the Climate in 2019"]. Bulletin of the American Meteorological Society 101, S1-S429. (doi:10.1175/2020BAMSStateoftheClimate.1)<br> (1901-2018 update) Barichivich J, Osborn TJ, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society under review.<br> (1901-2017 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2018) Drought [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society 99, S36-S37. (doi:10.1175/2018BAMSStateoftheClimate.1)<br> (1901-2016 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2017) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society 98, S32-S33 (doi:10.1175/2017BAMSStateoftheClimate.1) (available here).<br> (1901-2015 update) Osborn TJ, Barichivich J, Harris I, van der Schrier G and Jones PD (2016) Monitoring global drought using the self-calibrating Palmer Drought Severity Index [in "State of the Climate in 2015"]. Bulletin of the American Meteorological Society 97, S32-S36 (available here). <br><br> Data were downloaded from <a href="https://crudata.uea.ac.uk/cru/data/drought/"target=_blank>CRUDATA/Drought</a> -180.0 -90.0 180.0 90.0 wesr_climat:cru_scpdsi_11_mean image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:4326 EPSG:900913 EPSG:3857_512 med_00_ogs_nut_an-fc-m-avrg_year_2020 -5.5625 30.16667 36.3125 46.0 Medicip:med_00_ogs_nut_an-fc-m-avrg_year_2020 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 31 38 EPSG:3857:7 45 52 62 76 EPSG:3857:8 91 105 124 153 EPSG:3857:9 182 210 248 307 EPSG:3857:10 364 421 496 615 EPSG:3857:11 728 843 992 1230 EPSG:3857:12 1457 1687 1984 2461 EPSG:3857:13 2914 3375 3969 4922 EPSG:3857:14 5828 6750 7938 9844 EPSG:3857:15 11657 13501 15877 19689 EPSG:3857:16 23315 27003 31755 39378 EPSG:3857:17 46630 54006 63510 78756 EPSG:3857:18 93260 108013 127021 157513 EPSG:3857:19 186521 216027 254043 315027 EPSG:3857:20 373043 432055 508086 630055 EPSG:3857:21 746086 864110 1016172 1260111 EPSG:3857:22 1492173 1728221 2032344 2520223 EPSG:3857:23 2984346 3456443 4064688 5040446 EPSG:3857:24 5968692 6912886 8129376 10080893 EPSG:3857:25 11937384 13825773 16258753 20161786 EPSG:3857:26 23874768 27651547 32517506 40323572 EPSG:3857:27 47749537 55303095 65035013 80647145 EPSG:3857:28 95499074 110606190 130070027 161294290 EPSG:3857:29 190998149 221212380 260140054 322588580 EPSG:3857:30 381996298 442424760 520280109 645177161 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 0 1 2 EPSG:4326:2 0 1 3 4 EPSG:4326:3 1 2 7 9 EPSG:4326:4 3 5 15 19 EPSG:4326:5 7 10 31 38 EPSG:4326:6 15 21 62 76 EPSG:4326:7 31 42 124 153 EPSG:4326:8 62 85 248 307 EPSG:4326:9 125 170 496 615 EPSG:4326:10 250 340 992 1230 EPSG:4326:11 500 680 1984 2461 EPSG:4326:12 1001 1361 3969 4922 EPSG:4326:13 2002 2723 7938 9844 EPSG:4326:14 4004 5446 15877 19689 EPSG:4326:15 8009 10892 31755 39378 EPSG:4326:16 16019 21784 63510 78756 EPSG:4326:17 32039 43569 127021 157513 EPSG:4326:18 64079 87138 254043 315027 EPSG:4326:19 128159 174277 508086 630055 EPSG:4326:20 256318 348554 1016172 1260111 EPSG:4326:21 512637 697108 2032344 2520223 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 11 13 15 19 EPSG:3857:6 22 26 31 38 EPSG:3857:7 45 52 62 76 EPSG:3857:8 91 105 124 153 EPSG:3857:9 182 210 248 307 EPSG:3857:10 364 421 496 615 EPSG:3857:11 728 843 992 1230 EPSG:3857:12 1457 1687 1984 2461 EPSG:3857:13 2914 3375 3969 4922 EPSG:3857:14 5828 6750 7938 9844 EPSG:3857:15 11657 13501 15877 19689 EPSG:3857:16 23315 27003 31755 39378 EPSG:3857:17 46630 54006 63510 78756 EPSG:3857:18 93260 108013 127021 157513 EPSG:3857:19 186521 216027 254043 315027 EPSG:3857:20 373043 432055 508086 630055 EPSG:3857:21 746086 864110 1016172 1260111 EPSG:3857:22 1492173 1728221 2032344 2520223 EPSG:3857:23 2984346 3456443 4064688 5040446 EPSG:3857:24 5968692 6912886 8129376 10080893 EPSG:3857:25 11937384 13825773 16258753 20161786 EPSG:3857:26 23874768 27651547 32517506 40323572 EPSG:3857:27 47749537 55303095 65035013 80647145 EPSG:3857:28 95499074 110606190 130070027 161294290 EPSG:3857:29 190998149 221212380 260140054 322588580 EPSG:3857:30 381996298 442424760 520280109 645177161 Human Footprint difference 1993-2009 (Terrestrial) -179.99999995447251 -65.25013301721049 179.99661098079287 89.89762321520959 MapX_UNDP:hfp_difference_93-09 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 1 0 1 EPSG:3857:2 0 2 0 3 EPSG:3857:3 0 5 0 7 EPSG:3857:4 0 11 0 15 EPSG:3857:5 0 23 0 31 EPSG:3857:6 0 47 0 63 EPSG:3857:7 0 94 0 127 EPSG:3857:8 0 189 0 255 EPSG:3857:9 0 379 0 511 EPSG:3857:10 0 759 0 1023 EPSG:3857:11 0 1518 0 2047 EPSG:3857:12 0 3036 0 4095 EPSG:3857:13 0 6073 0 8191 EPSG:3857:14 0 12147 0 16383 EPSG:3857:15 0 24294 0 32767 EPSG:3857:16 0 48589 0 65535 EPSG:3857:17 0 97178 0 131070 EPSG:3857:18 0 194356 0 262141 EPSG:3857:19 0 388713 0 524283 EPSG:3857:20 0 777426 0 1048566 EPSG:3857:21 0 1554852 0 2097132 EPSG:3857:22 -1 3109705 0 4194264 EPSG:3857:23 -1 6219410 0 8388529 EPSG:3857:24 0 12438820 0 16777058 EPSG:3857:25 0 24877640 0 33554116 EPSG:3857:26 0 49755280 0 67108232 EPSG:3857:27 0 99510561 0 134216464 EPSG:3857:28 -1 199021122 0 268432928 EPSG:3857:29 0 398042245 0 536865857 EPSG:3857:30 0 796084491 0 1073731715 EPSG:4326 EPSG:4326:0 0 0 0 1 EPSG:4326:1 0 1 0 3 EPSG:4326:2 0 3 0 7 EPSG:4326:3 0 6 0 15 EPSG:4326:4 0 13 0 31 EPSG:4326:5 0 27 0 63 EPSG:4326:6 0 55 0 127 EPSG:4326:7 0 110 0 255 EPSG:4326:8 0 220 0 511 EPSG:4326:9 0 441 0 1023 EPSG:4326:10 0 883 0 2047 EPSG:4326:11 1 1766 0 4095 EPSG:4326:12 2 3532 0 8191 EPSG:4326:13 4 7065 0 16383 EPSG:4326:14 9 14131 0 32767 EPSG:4326:15 18 28262 0 65535 EPSG:4326:16 37 56524 0 131070 EPSG:4326:17 74 113049 0 262141 EPSG:4326:18 149 226099 0 524283 EPSG:4326:19 298 452198 0 1048566 EPSG:4326:20 596 904397 0 2097132 EPSG:4326:21 1192 1808795 0 4194264 EPSG:900913 Mean temperatures 2011 - Central African Republic Mean observed temperatures in 2011 in the Central African Republic. 14.373044545912343 2.1559566818868507 27.488447694057356 11.049277994670113 cc_and_health:mean_temp_2011_caf image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 4 4 EPSG:4326:3 3 3 8 9 EPSG:4326:4 7 7 17 18 EPSG:4326:5 14 15 34 36 EPSG:4326:6 28 31 69 73 EPSG:4326:7 56 62 138 147 EPSG:4326:8 112 124 276 295 EPSG:4326:9 224 249 552 590 EPSG:4326:10 449 499 1105 1180 EPSG:4326:11 898 999 2211 2360 EPSG:4326:12 1796 1998 4423 4721 EPSG:4326:13 3593 3997 8846 9443 EPSG:4326:14 7186 7995 17692 18886 EPSG:4326:15 14372 15991 35384 37772 EPSG:4326:16 28745 31983 70769 75544 EPSG:4326:17 57490 63966 141538 151088 EPSG:4326:18 114980 127932 283076 302176 EPSG:4326:19 229960 255864 566152 604353 EPSG:4326:20 459921 511728 1132305 1208707 EPSG:4326:21 919842 1023457 2264610 2417415 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 4 4 EPSG:3857:4 7 7 8 9 EPSG:3857:5 15 15 17 18 EPSG:3857:6 30 31 34 36 EPSG:3857:7 60 63 69 73 EPSG:3857:8 120 126 138 147 EPSG:3857:9 240 252 276 295 EPSG:3857:10 480 505 552 590 EPSG:3857:11 960 1011 1105 1180 EPSG:3857:12 1921 2023 2211 2360 EPSG:3857:13 3842 4046 4423 4721 EPSG:3857:14 7685 8093 8846 9443 EPSG:3857:15 15371 16187 17692 18886 EPSG:3857:16 30743 32375 35384 37772 EPSG:3857:17 61487 64750 70769 75544 EPSG:3857:18 122975 129501 141538 151088 EPSG:3857:19 245951 259003 283076 302176 EPSG:3857:20 491903 518006 566152 604353 EPSG:3857:21 983806 1036013 1132305 1208707 EPSG:3857:22 1967613 2072027 2264610 2417415 EPSG:3857:23 3935226 4144054 4529220 4834831 EPSG:3857:24 7870452 8288109 9058440 9669662 EPSG:3857:25 15740905 16576218 18116880 19339325 EPSG:3857:26 31481810 33152437 36233761 38678650 EPSG:3857:27 62963620 66304875 72467523 77357300 EPSG:3857:28 125927241 132609750 144935046 154714600 EPSG:3857:29 251854483 265219501 289870093 309429200 EPSG:3857:30 503708967 530439002 579740187 618858400 namibia_remote_site_screening_res50 11.715630531000063 -28.969192951999922 25.262630531000063 -16.963192951999922 mapx_chemobs:namibia_remote_site_screening_res50 image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 9 8 9 EPSG:3857:5 17 18 17 18 EPSG:3857:6 35 37 34 36 EPSG:3857:7 70 74 68 72 EPSG:3857:8 140 149 136 145 EPSG:3857:9 280 299 272 291 EPSG:3857:10 560 598 545 583 EPSG:3857:11 1121 1196 1090 1167 EPSG:3857:12 2243 2392 2181 2335 EPSG:3857:13 4487 4785 4362 4670 EPSG:3857:14 8975 9570 8725 9341 EPSG:3857:15 17951 19140 17450 18683 EPSG:3857:16 35902 38281 34900 37366 EPSG:3857:17 71804 76563 69801 74733 EPSG:3857:18 143608 153127 139603 149467 EPSG:3857:19 287217 306255 279206 298935 EPSG:3857:20 574434 612510 558412 597870 EPSG:3857:21 1148869 1225020 1116824 1195741 EPSG:3857:22 2297739 2450041 2233648 2391482 EPSG:3857:23 4595479 4900082 4467297 4782965 EPSG:3857:24 9190958 9800164 8934595 9565931 EPSG:3857:25 18381917 19600329 17869191 19131863 EPSG:3857:26 36763835 39200659 35738383 38263727 EPSG:3857:27 73527670 78401319 71476767 76527455 EPSG:3857:28 147055340 156802639 142953535 153054910 EPSG:3857:29 294110680 313605278 285907070 306109821 EPSG:3857:30 588221361 627210556 571814141 612219642 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 1 1 2 2 EPSG:4326:2 2 2 4 4 EPSG:4326:3 4 5 8 9 EPSG:4326:4 9 10 17 18 EPSG:4326:5 19 21 34 36 EPSG:4326:6 38 42 68 72 EPSG:4326:7 76 84 136 145 EPSG:4326:8 152 169 272 291 EPSG:4326:9 304 338 545 583 EPSG:4326:10 608 676 1090 1167 EPSG:4326:11 1217 1353 2181 2335 EPSG:4326:12 2434 2707 4362 4670 EPSG:4326:13 4868 5414 8725 9341 EPSG:4326:14 9736 10828 17450 18683 EPSG:4326:15 19472 21657 34900 37366 EPSG:4326:16 38944 43315 69801 74733 EPSG:4326:17 77888 86630 139603 149467 EPSG:4326:18 155776 173261 279206 298935 EPSG:4326:19 311552 346522 558412 597870 EPSG:4326:20 623105 693045 1116824 1195741 EPSG:4326:21 1246211 1386091 2233648 2391482 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 1 1 1 1 EPSG:3857:2 2 2 2 2 EPSG:3857:3 4 4 4 4 EPSG:3857:4 8 9 8 9 EPSG:3857:5 17 18 17 18 EPSG:3857:6 35 37 34 36 EPSG:3857:7 70 74 68 72 EPSG:3857:8 140 149 136 145 EPSG:3857:9 280 299 272 291 EPSG:3857:10 560 598 545 583 EPSG:3857:11 1121 1196 1090 1167 EPSG:3857:12 2243 2392 2181 2335 EPSG:3857:13 4487 4785 4362 4670 EPSG:3857:14 8975 9570 8725 9341 EPSG:3857:15 17951 19140 17450 18683 EPSG:3857:16 35902 38281 34900 37366 EPSG:3857:17 71804 76563 69801 74733 EPSG:3857:18 143608 153127 139603 149467 EPSG:3857:19 287217 306255 279206 298935 EPSG:3857:20 574434 612510 558412 597870 EPSG:3857:21 1148869 1225020 1116824 1195741 EPSG:3857:22 2297739 2450041 2233648 2391482 EPSG:3857:23 4595479 4900082 4467297 4782965 EPSG:3857:24 9190958 9800164 8934595 9565931 EPSG:3857:25 18381917 19600329 17869191 19131863 EPSG:3857:26 36763835 39200659 35738383 38263727 EPSG:3857:27 73527670 78401319 71476767 76527455 EPSG:3857:28 147055340 156802639 142953535 153054910 EPSG:3857:29 294110680 313605278 285907070 306109821 EPSG:3857:30 588221361 627210556 571814141 612219642 Kerala Flood 50 Years RP - Historical Kerala State flood hazard map - Historical. Maximum expected flood event water height in a 50 years return period, expressed in cm. 74.85875 8.25375 77.49291666666667 12.842916666666673 ECO-DRR:Kerala_Flood_50_Yrs_Historical image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 EPSG:4326 EPSG:4326:0 0 0 1 1 EPSG:4326:1 0 0 2 2 EPSG:4326:2 1 1 5 5 EPSG:4326:3 3 3 11 11 EPSG:4326:4 6 7 22 22 EPSG:4326:5 13 14 45 45 EPSG:4326:6 27 29 90 91 EPSG:4326:7 54 58 181 183 EPSG:4326:8 109 116 362 366 EPSG:4326:9 219 232 724 732 EPSG:4326:10 438 465 1449 1464 EPSG:4326:11 877 930 2899 2929 EPSG:4326:12 1755 1860 5799 5859 EPSG:4326:13 3511 3720 11598 11718 EPSG:4326:14 7023 7440 23197 23437 EPSG:4326:15 14046 14881 46395 46875 EPSG:4326:16 28092 29762 92791 93750 EPSG:4326:17 56184 59525 185582 187500 EPSG:4326:18 112368 119051 371164 375001 EPSG:4326:19 224736 238103 742329 750002 EPSG:4326:20 449472 476206 1484659 1500004 EPSG:4326:21 898945 952412 2969319 3000009 EPSG:900913 EPSG:3857_512 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 1 1 EPSG:3857:2 1 1 2 2 EPSG:3857:3 3 3 5 5 EPSG:3857:4 7 7 11 11 EPSG:3857:5 14 15 22 22 EPSG:3857:6 29 30 45 45 EPSG:3857:7 59 61 90 91 EPSG:3857:8 118 122 181 183 EPSG:3857:9 237 244 362 366 EPSG:3857:10 475 488 724 732 EPSG:3857:11 950 976 1449 1464 EPSG:3857:12 1900 1953 2899 2929 EPSG:3857:13 3801 3907 5799 5859 EPSG:3857:14 7602 7815 11598 11718 EPSG:3857:15 15205 15630 23197 23437 EPSG:3857:16 30410 31260 46395 46875 EPSG:3857:17 60820 62520 92791 93750 EPSG:3857:18 121640 125040 185582 187500 EPSG:3857:19 243281 250081 371164 375001 EPSG:3857:20 486563 500163 742329 750002 EPSG:3857:21 973126 1000327 1484659 1500004 EPSG:3857:22 1946252 2000654 2969319 3000009 EPSG:3857:23 3892504 4001309 5938639 6000019 EPSG:3857:24 7785008 8002618 11877278 12000039 EPSG:3857:25 15570017 16005236 23754557 24000079 EPSG:3857:26 31140035 32010472 47509114 48000158 EPSG:3857:27 62280070 64020944 95018228 96000317 EPSG:3857:28 124560140 128041888 190036457 192000634 EPSG:3857:29 249120281 256083777 380072915 384001269 EPSG:3857:30 498240563 512167555 760145830 768002538 Spring precipitations change (%) for the period 2040 - 2059 under the RCP 2.6 scenario Projected change of precipitations for the specified season and reference period, under the specified scenario with respect to the reference period (1980-1999). Data provided by MedECC Atlas. -12.0 27.5 37.0 49.0 Medicip:pr_mam_MIDREF_rcp26_opt image/png image/vnd.jpeg-png image/jpeg image/png8 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml text/html application/json EPSG:3857 EPSG:3857:0 0 0 0 0 EPSG:3857:1 0 0 0 1 EPSG:3857:2 1 1 1 2 EPSG:3857:3 2 3 3 4 EPSG:3857:4 5 6 7 9 EPSG:3857:5 10 13 14 19 EPSG:3857:6 21 26 29 38 EPSG:3857:7 43 53 59 77 EPSG:3857:8 87 107 119 154 EPSG:3857:9 175 215 238 308 EPSG:3857:10 351 430 477 617 EPSG:3857:11 703 861 955 1234 EPSG:3857:12 1406 1722 1911 2468 EPSG:3857:13 2813 3444 3822 4937 EPSG:3857:14 5626 6889 7645 9875 EPSG:3857:15 11253 13778 15291 19751 EPSG:3857:16 22506 27557 30583 39503 EPSG:3857:17 45013 55115 61166 79007 EPSG:3857:18 90026 110230 122333 158014 EPSG:3857:19 180052 220461 244667 316029 EPSG:3857:20 360104 440923 489335 632058 EPSG:3857:21 720208 881846 978670 1264116 EPSG:3857:22 1440416 1763692 1957341 2528233 EPSG:3857:23 2880833 3527385 3914683 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