WFShttps://datacore.unepgrid.ch/geoserver/unep_storymap:Barcelona_ua2012_wgs_WarsawBarcelona UA2012 - Warsawfeatures, Barcelona_ua2012_wgsEPSG:4326grid_data_core:city1k_gisCities with more than 1'000 inhabitantsfeatures, city1k_gisEPSG:4326grid_data_core:city15k_gisCities with more than 15'000 inhabitantsfeatures, city15k_gisEPSG:4326grid_data_core:city5k_gisCities with more than 5'000 inhabitantsfeatures, city5k_gisEPSG:4326UN_Sahel:USAID_CMM_exp_0-001_vClimate ExposureThe 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.features, USAID_CMM_bivariate_exp_frag_0-001_vEPSG:4326wesr_cca:CobVeg_180615CobVeg_180615Layer 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.features, CobVeg_180615EPSG:32718UN_Sahel:USAID_CMM_frag_0-001_vFragilityThe 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.features, USAID_CMM_bivariate_exp_frag_0-001_vEPSG:4326ECO-DRR:GLO_ecodrrGLO_ecodrrfeatures, GLO_ecodrrEPSG:4326sand:Dredging_points-2012-2024vfGlobal Dredging Activity 2012 to 2024This 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.features, Dredging_points-2012-2024vfEPSG:4326unep_storymap:HELSINKI_UA2012_WGS84_WarsawHelsinki UA2012 - Warsafeatures, HELSKINKI_UA2012_WGS84EPSG:4326cc_and_health:vNaturalPolygonsHydrography - Natural Polygonsfeatures, vNaturalPolygonsEPSG:32634cc_and_health:vWaterLines_river_onlyHydrography - Water Lines river onlyfeatures, vWaterLines_river_onlyEPSG:32634grid_data_core_pro:_2012_ungiwg_cst_ln_01International Boundaries Coastalines Level 0 - UNGIWGInternational 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.features, _2012_ungiwg_cst_ln_01, boundary, coastEPSG:4326grid_data_core_pro:ungiwg_cst_ln_01mInternational Boundaries Coastalines Level 0 - UNmapUNmap 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.ungiwg_cst_ln_01m, featuresEPSG:4326grid_data_core_pro:_2012_ungiwg_lks_ply_01International Boundaries Lakes - UNGIWG_2012_ungiwg_lks_ply_01, features, lake, water body, ungiwgEPSG:4326grid_data_core_pro:_2012_ungiwg_bnd_ln_01International Boundaries Lines Level 0 - UNGIWGInternational 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.features, _2012_ungiwg_bnd_ln_01, ungiwg, boundaryEPSG:4326grid_data_core_pro:ungiwg_bnd_ln_01mInternational Boundaries Lines Level 0 - UNmapUNmap 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.features, ungiwg_bnd_ln_01mEPSG:4326grid_data_core:esri_boundaries2015International Boundaries Polygons Level 0 - ESRIfeatures, esri_boundaries2015EPSG:4326grid_data_core_pro:g2015_2014_0International Boundaries Polygons Level 0 - GAULfeatures, g2015_2014_0EPSG:4326grid_data_core:ne_10m_admin_0_countriesInternational Boundaries Polygons Level 0 - Natural Earthne_10m_admin_0_countries, featuresEPSG:4326grid_data_core_pro:_2012_ungiwg_cnt_ply_01International Boundaries Polygons Level 0 - UNGIWGInternational 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._2012_ungiwg_cnt_ply_01, features, boundary, ungiwgEPSG:4326grid_data_core_pro:ungiwg_bnd_ply_01mInternational Boundaries Polygons Level 0 - UNmapUNmap 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.ungiwg_bnd_ply_01m, featuresEPSG:4326grid_data_core_pro:g2015_2014_1International Boundaries Polygons Level 1 - GAULg2015_2014_1, featuresEPSG:4326grid_data_core_pro:g2015_2014_2International Boundaries Polygons Level 2 - GAULfeatures, g2015_2014_2EPSG:4326grid_data_core_pro:gadm36_1_0.001_shpInternational boundaries Level 1 subdivision - GADM 3.6- Edited by GRID - simplified DP 0.001 on QGIS using Simplifyfeatures, gadm36_1_0-001EPSG:4326MAPX_nd:gadm36_2International boundaries Level 2 subdivision - GADM 3.6Source: https://gadm.org/data.htmlfeatures, gadm36_2EPSG:4326wesr_risk:lakes_glwdLakesfeatures, glwd_1EPSG:4326UN_Sahel:FEWS_NET_LH_WorldLivelihood 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>.features, FEWS_NET_LH_WorldEPSG:4326wesr_cca:MAPA_NACIONAL_DE_ECOSISTEMASMAPA_NACIONAL_DE_ECOSISTEMASLayer 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.pdffeatures, MAPA_NACIONAL_DE_ECOSISTEMASEPSG:32718MAPX:nasa_firms_fires_nrtNASA - FIRMS active fires Near Real TimeNASA's Fire Information for Resource Management System (FIRMS) distributes Near Real-Time (NRT) active fire data within 3 hours of satellite overpass from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and NASA's Visible Infrared Imaging Radiometer Suite (VIIRS).
MODIS NRT active fire products (MCD14DL) are processed using the standard MOD14/MYD14 Fire and Thermal Anomalies product. Each MODIS active fire location represents the center of a 1km pixel that is flagged by the algorithm as containing one or more fires within the pixel.
VIIRS NRT 375 m active fire products (VNP14IMGTDL_NRT, VJ114IMGTDL_NRT, VJ214IMGTDL_NRT) complements MODIS fire detections but the improved spatial resolution of the 375 m data provides a greater response of fires over relatively small areas. The 375 m data also has improved nighttime performance.
MODIS Collection 6 NRT Hotspot/Active Fire Detections MCD14DL. Available on-line. doi: 10.5067/FIRMS/MODIS/MCD14DL.NRT.006
VIIRS (S-NPP) I Band 375 m Active Fire Product NRT VNP14IMGT. Available on-line. doi: 10.5067/FIRMS/VIIRS/VNP14IMGT.NRT.001.
VIIRS (NOAA-20/JPSS-1) I Band 375 m Active Fire Product NRT VJ114IMGTDL_NRT. Available on-line. doi: 10.5067/FIRMS/VIIRS/VJ114IMGT_NRT.002.
VIIRS (NOAA-21/JPSS-2) I Band 375 m Active Fire Product NRT VJ214IMGTDL_NRT. Available on-line. doi: 10.5067/VIIRS/VJ214IMG_NRT.002.features, nasa_firms_fires_nrtEPSG:4326wesr_risk:nparksNational Parksfeatures, nparksEPSG:4326unep_storymap:NATURA_UA2012_WGS84_WarsawNatura UA2012 - Warsawfeatures, NATURA_UA2012_WGS84EPSG:4326wesr_mountains:RGI_GlobalRGI_GlobalThis 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.features, RGI_GlobalEPSG:4326wesr_risk:riversRiversfeatures, riverEPSG:4326grid_data_core_pro:UN0_administrative_boundaries_2018UN Country Administrative Boundaries 2018United 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 Resourcesfeatures, BNDLEPSG:4326grid_data_core_pro:UN0_administrative_boundaries_2020UN Country Administrative Boundaries 2020United 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 Resourcesfeatures, BNDLEPSG:4326grid_data_core_pro:UN0_administrative_boundaries_polygons_2018UN Country Polygons 2018United 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 Resourcesfeatures, BNDA_CTYEPSG:4326wesr_risk:urban_assetsUrban Assetsfeatures, v0_urbanEPSG:4326sand:WDPA_2024_MPAWDPA Marine Protected Areas Global Ocean Units 2024This 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.features, WDPA_2024_MPAEPSG:4326grid_data_core:city_esriWorld Cities (Esri)features, city_esriEPSG:4326grid_data_core:roads_esriWorld Roads - Esrifeatures, roads_esriEPSG:4326grid_data_core:esri_urban_areasWorld Urban Areas - Esriesri_urban_areas, featuresEPSG:4326grid_data_core:ne_10m_urban_areasWorld Urban Areas - Natural Earthfeatures, ne_10m_urban_areasEPSG:4326sand:dredging_points20122024vf_pgdredging_points20122024vf_pgfeatures, dredging_points20122024vfEPSG:4326MAPX_nd:ecuador_ecosistemas_clean_ecosistemaecuador_ecosistemas_clean_ecosistemaecd_ecosistemas_ecuador_84_a, featuresEPSG:4326MAPX_nd:ecuador_ecosistemas_clean_fragmentationecuador_ecosistemas_clean_fragmentationecd_ecosistemas_ecuador_84_a, featuresEPSG:4326mapx_chemobs:eth_natural_hazards_exposureeth_natural_hazards_exposureeth_natural_hazards_exposure_4326, featuresEPSG:4326mapx_chemobs:eth_wb_buffer_100meth_wb_buffer_100mfeatures, eth_wb_buffer_100m_4326EPSG:4326grid_data_core:roads_groadsgROADS v1 - CIESINroads_groads, featuresEPSG:4326mapx_chemobs:gab_natural_hazards_exposuregab_natural_hazards_exposurefeatures, gba_natural_hazards_4326EPSG:4326mapx_chemobs:gab_wb_buffer_100mgab_wb_buffer_100mfeatures, gab_wb_buffer_100m_4326EPSG:4326wesr_mountains:glims_polygonsglims_polygonsfeatures, glims_polygonsEPSG:4326sdc_test:greg_no2greg_no2features, NO2_tomEPSG:2056sdc_test:greg_zonalstat_s5greg_zonalstat_s5zonalstat_s5, featuresEPSG:2056mapx_chemobs:ken_natural_hazards_exposureken_natural_hazards_exposurefeatures, ken_natural_hazards_exposure_fixed_buffer_10cmEPSG:32737mapx_chemobs:ken_wb_buffer_100mken_wb_buffer_100mfeatures, ken_wb_buffer_100mEPSG:4326mapx_chemobs:sen_natural_hazards_exposuresen_natural_hazards_exposurefeatures, sen_natural_hazards_exposure_fixed_buffer_10cmEPSG:32628mapx_chemobs:sen_wb_buffer_100msen_wb_buffer_100mfeatures, sen_wb_buffer_100mEPSG:4326mapx_chemobs:tza_natural_hazards_exposuretza_natural_hazards_exposurefeatures, tza_natural_hazards_exposure_fixed_buffer_10cmEPSG:32737mapx_chemobs:tza_wb_buffer_100mtza_wb_buffer_100mfeatures, tza_wb_buffer_100mEPSG:4326absabs_2abs_3abs_4acosAddCoveragesAffineAggregateAndAreaarea2AreaGridarrayasinatanatan2attributeCountBandMergebandsBandSelectBarnesSurfacebetweenboundaryboundaryDimensionboundedByBoundsbufferBufferFeatureCollectionbufferWithSegmentsCategorizeceilcenterLinecentroidclassifyClassifyByRangeClipCollectGeometriesCollection_AverageCollection_BoundsCollection_CountCollection_MaxCollection_MedianCollection_MinCollection_NearestCollection_SumCollection_UniqueConcatenatecontainsContourcontrastconvertconvexHullConvolveCoveragecosCountCoverageClassStatsCropCoveragecrossesdarkendateDifferencedateFormatdateParsedensifydesaturatedifferencedimensiondisjointdisjoint3Ddistancedistance3Ddivdouble2boolendAngleendPointenvenvelopeEqualAreaEqualIntervalequalsExactequalsExactToleranceequalToexpexteriorRingFeatureFeatureClassStatsfloorfootprintsgeometrygeometryTypegeomFromWKTgeomLengthgetGeometryNgetXgetYgetzgrayscalegreaterEqualThangreaterThanGridGroupCandidateSelectionHeatmaphslidIEEEremainderif_then_elseinin10in2in3in4in5in6in7in8in9inArrayInclusionFeatureCollectionint2bboolint2ddoubleinteriorPointinteriorRingNInterpolateintersectionIntersectionFeatureCollectionintersectsintersects3DisCachedisClosedisCoverageisEmptyisInstanceOfisLikeisNullisometricisRingisSimpleisValidisWithinDistanceisWithinDistance3DJenksJifflejsonArrayContainsjsonPointerlabelPointlanguagelapplylengthlessEqualThanlessThanlightenlinlistlistMultiplylitemliteratelogLRSGeocodeLRSMeasureLRSSegmentmapGetmaxmax_2max_3max_4midAnglemidPointminmin_2min_3min_4mincircleminimumdiameterminrectanglemixmoduloMultiplyCoveragesNearestNormalizeCoveragenorthFixnotnotEqualTonownumberFormatnumberFormat2numGeometriesnumInteriorRingnumPointsoctagonalenvelopeoffsetOroverlapsparameterparseBooleanparseDoubleparseIntparseLongparseTimepgNearestpiPointBufferspointNpointOnLinePointStackerPolygonExtractionpolygonizePolyLabellerpowpropertyPropertyExistsQuantileQueryrandomRangeLookupRasterAsPointCollectionRasterZonalStatisticsRasterZonalStatistics2RecodeRectangularCliprelaterelatePatternreprojectrescaleToPixelsrintroundround_2roundDoublesaturateScaleCoveragesetCRSshadesimplifysinsizeSnapspinsplitPolygonsqrtStandardDeviationstartAnglestartPointstrAbbreviatestrCapitalizestrConcatstrDefaultIfBlankstrEndsWithstrEqualsIgnoreCasestrIndexOfstringTemplatestrLastIndexOfstrLengthstrMatchesstrPositionstrReplacestrStartsWithstrStripAccentsstrSubstringstrSubstringStartstrToLowerCasestrToUpperCasestrTrimstrTrim2strURLEncodeStyleCoveragesymDifferencetantinttoDegreestoRadianstouchestoWKTTransformTransparencyFillunionUnionFeatureCollectionUniqueUniqueIntervalVectorToRasterVectorZonalStatisticsverticeswithin