- |---| | [### CSP gHM: Global Human Modification ![](https://developers.google.com/earth-engine/datasets/images/CSP/CSP_HM_GlobalHumanModification_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/CSP_HM_GlobalHumanModification.md.txt) | | The global Human Modification dataset (gHM) provides a cumulative measure of human modification of terrestrial lands globally at 1 square-kilometer resolution. The gHM values range from 0.0-1.0 and are calculated by estimating the proportion of a given location (pixel) that is modified, the estimated intensity ... | | [csp](https://developers.google.com/earth-engine/datasets/tags/csp.md.txt) [fragmentation](https://developers.google.com/earth-engine/datasets/tags/fragmentation.md.txt) [human-modification](https://developers.google.com/earth-engine/datasets/tags/human-modification.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landscape-gradient](https://developers.google.com/earth-engine/datasets/tags/landscape-gradient.md.txt) [population](https://developers.google.com/earth-engine/datasets/tags/population.md.txt) | - |---| | [### Canada AAFC Annual Crop Inventory ![](https://developers.google.com/earth-engine/datasets/images/AAFC/AAFC_ACI_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/AAFC_ACI.md.txt) | | Starting in 2009, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop type digital maps. Focusing on the Prairie Provinces in 2009 and 2010, a Decision Tree (DT) based methodology ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture.md.txt) [canada](https://developers.google.com/earth-engine/datasets/tags/canada.md.txt) [crop](https://developers.google.com/earth-engine/datasets/tags/crop.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) | - |---| | [### Copernicus CORINE Land Cover ![](https://developers.google.com/earth-engine/datasets/images/COPERNICUS/COPERNICUS_CORINE_V20_100m_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_CORINE_V20_100m.md.txt) | | The CORINE (coordination of information on the environment) Land Cover (CLC) inventory was initiated in 1985 to standardize data collection on land in Europe to support environmental policy development. The project is coordinated by the European Environment Agency (EEA) in the frame of the EU ... | | [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus.md.txt) [eea](https://developers.google.com/earth-engine/datasets/tags/eea.md.txt) [esa](https://developers.google.com/earth-engine/datasets/tags/esa.md.txt) [eu](https://developers.google.com/earth-engine/datasets/tags/eu.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### Copernicus Global Land Cover Layers: CGLS-LC100 Collection 3 ![](https://developers.google.com/earth-engine/datasets/images/COPERNICUS/COPERNICUS_Landcover_100m_Proba-V-C3_Global_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global.md.txt) | | The Copernicus Global Land Service (CGLS) is earmarked as a component of the Land service to operate a multi-purpose service component that provides a series of bio-geophysical products on the status and evolution of land surface at global scale. The Dynamic Land Cover map at ... | | [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus.md.txt) [eea](https://developers.google.com/earth-engine/datasets/tags/eea.md.txt) [esa](https://developers.google.com/earth-engine/datasets/tags/esa.md.txt) [eu](https://developers.google.com/earth-engine/datasets/tags/eu.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### Cote d'Ivoire BNETD 2020 Land Cover Map ![](https://developers.google.com/earth-engine/datasets/images/BNETD/BNETD_land_cover_v1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/BNETD_land_cover_v1.md.txt) | | The Cote d'Ivoire BNETD 2020 Land Cover Map was produced by the Ivorian Government through a national institution, the Center for Geographic Information and Digital from the National Study Office Techniques and Development (BNETD-CIGN), with technical and financial support from the European Union. The methodology ... | | [classification](https://developers.google.com/earth-engine/datasets/tags/classification.md.txt) [deforestation](https://developers.google.com/earth-engine/datasets/tags/deforestation.md.txt) [forest](https://developers.google.com/earth-engine/datasets/tags/forest.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### DESS China Terrace Map v1 ![](https://developers.google.com/earth-engine/datasets/images/Tsinghua/Tsinghua_DESS_ChinaTerraceMap_v1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/Tsinghua_DESS_ChinaTerraceMap_v1.md.txt) | | This dataset is a China terrace map at 30 m resolution in 2018. It was developed through supervised pixel-based classification using multisource and multi-temporal data based on the Google Earth Engine platform. The overall accuracy and kappa coefficient achieved 94% and 0.72, respectively. This first ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [tsinghua](https://developers.google.com/earth-engine/datasets/tags/tsinghua.md.txt) | - |---| | [### Dynamic World V1 ![](https://developers.google.com/earth-engine/datasets/images/GOOGLE/GOOGLE_DYNAMICWORLD_V1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_DYNAMICWORLD_V1.md.txt) | | Dynamic World is a 10m near-real-time (NRT) Land Use/Land Cover (LULC) dataset that includes class probabilities and label information for nine classes. Dynamic World predictions are available for the Sentinel-2 L1C collection from 2015-06-27 to present. The revisit frequency of Sentinel-2 is between 2-5 days ... | | [global](https://developers.google.com/earth-engine/datasets/tags/global.md.txt) [google](https://developers.google.com/earth-engine/datasets/tags/google.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [nrt](https://developers.google.com/earth-engine/datasets/tags/nrt.md.txt) | - |---| | [### ESA WorldCereal 10 m v100 ![](https://developers.google.com/earth-engine/datasets/images/ESA/ESA_WorldCereal_2021_MODELS_v100_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/ESA_WorldCereal_2021_MODELS_v100.md.txt) | | The European Space Agency (ESA) WorldCereal 10 m 2021 product suite consists of global-scale annual and seasonal crop maps and their related confidence. They were generated as part of the ESA-WorldCereal project. More information on the content of these products and the methodology used to ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture.md.txt) [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus.md.txt) [crop](https://developers.google.com/earth-engine/datasets/tags/crop.md.txt) [esa](https://developers.google.com/earth-engine/datasets/tags/esa.md.txt) [global](https://developers.google.com/earth-engine/datasets/tags/global.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) | - |---| | [### ESA WorldCereal Active Cropland 10 m v100 ![](https://developers.google.com/earth-engine/datasets/images/ESA/ESA_WorldCereal_2021_MARKERS_v100_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/ESA_WorldCereal_2021_MARKERS_v100.md.txt) | | The European Space Agency (ESA) WorldCereal Active Cropland 10 m 2021 product suite contains global-scale seasonal active cropland markers. They were generated as part of the ESA-WorldCereal project. The active cropland products indicate whether or not a pixel identified as temporary crops has been actively ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture.md.txt) [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus.md.txt) [crop](https://developers.google.com/earth-engine/datasets/tags/crop.md.txt) [esa](https://developers.google.com/earth-engine/datasets/tags/esa.md.txt) [global](https://developers.google.com/earth-engine/datasets/tags/global.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) | - |---| | [### ESA WorldCover 10m v100 ![](https://developers.google.com/earth-engine/datasets/images/ESA/ESA_WorldCover_v100_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/ESA_WorldCover_v100.md.txt) | | The European Space Agency (ESA) WorldCover 10 m 2020 product provides a global land cover map for 2020 at 10 m resolution based on Sentinel-1 and Sentinel-2 data. The WorldCover product comes with 11 land cover classes and has been generated in the framework of ... | | [esa](https://developers.google.com/earth-engine/datasets/tags/esa.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [sentinel1-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel1-derived.md.txt) [sentinel2-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel2-derived.md.txt) | - |---| | [### ESA WorldCover 10m v200 ![](https://developers.google.com/earth-engine/datasets/images/ESA/ESA_WorldCover_v200_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/ESA_WorldCover_v200.md.txt) | | The European Space Agency (ESA) WorldCover 10 m 2021 product provides a global land cover map for 2021 at 10 m resolution based on Sentinel-1 and Sentinel-2 data. The WorldCover product comes with 11 land cover classes and has been generated in the framework of ... | | [esa](https://developers.google.com/earth-engine/datasets/tags/esa.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [sentinel1-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel1-derived.md.txt) [sentinel2-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel2-derived.md.txt) | - |---| | [### FireCCI51: MODIS Fire_cci Burned Area Pixel Product, Version 5.1 ![](https://developers.google.com/earth-engine/datasets/images/ESA/ESA_CCI_FireCCI_5_1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/ESA_CCI_FireCCI_5_1.md.txt) | | The MODIS Fire_cci Burned Area pixel product version 5.1 (FireCCI51) is a monthly global \~250m spatial resolution dataset containing information on burned area as well as ancillary data. It is based on surface reflectance in the Near Infrared (NIR) band from the MODIS instrument onboard ... | | [burn](https://developers.google.com/earth-engine/datasets/tags/burn.md.txt) [cci](https://developers.google.com/earth-engine/datasets/tags/cci) [climate-change](https://developers.google.com/earth-engine/datasets/tags/climate-change.md.txt) [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus.md.txt) [esa](https://developers.google.com/earth-engine/datasets/tags/esa.md.txt) [fire](https://developers.google.com/earth-engine/datasets/tags/fire.md.txt) | - |---| | [### GFSAD1000: Cropland Extent 1km Multi-Study Crop Mask, Global Food-Support Analysis Data ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_GFSAD1000_V1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_GFSAD1000_V1.md.txt) | | The GFSAD is a NASA-funded project to provide high-resolution global cropland data and their water use that contributes towards global food security in the twenty-first century. The GFSAD products are derived through multi-sensor remote sensing data (e.g., Landsat, MODIS, AVHRR), secondary data, and field-plot data ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture.md.txt) [crop](https://developers.google.com/earth-engine/datasets/tags/crop.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs.md.txt) | - |---| | [### GHSL: Global built-up surface 10m (P2023A) ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_GHSL_P2023A_GHS_BUILT_S_10m_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_S_10m.md.txt) | | This raster dataset depicts the distribution of built-up surfaces, expressed in square metres per 10 m grid cell, for 2018 as observed from the S2 image data. The datasets measure: a) the total built-up surface, and b) the built-up surface allocated to grid cells of ... | | [built](https://developers.google.com/earth-engine/datasets/tags/built.md.txt) [built-environment](https://developers.google.com/earth-engine/datasets/tags/built-environment.md.txt) [builtup](https://developers.google.com/earth-engine/datasets/tags/builtup.md.txt) [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus.md.txt) [ghsl](https://developers.google.com/earth-engine/datasets/tags/ghsl.md.txt) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc.md.txt) | - |---| | [### GHSL: Global built-up surface 1975-2030 (P2023A) ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_GHSL_P2023A_GHS_BUILT_S_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_S.md.txt) | | This raster dataset depicts the distribution of built-up surfaces, expressed in square metres per 100 m grid cell. The dataset measures: a) the total built-up surface, and b) the built-up surface allocated to grid cells of predominant non-residential (NRES) use. Data are spatially-temporally interpolated or ... | | [built](https://developers.google.com/earth-engine/datasets/tags/built.md.txt) [built-environment](https://developers.google.com/earth-engine/datasets/tags/built-environment.md.txt) [builtup](https://developers.google.com/earth-engine/datasets/tags/builtup.md.txt) [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus.md.txt) [ghsl](https://developers.google.com/earth-engine/datasets/tags/ghsl.md.txt) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc.md.txt) | - |---| | [### GHSL: Global settlement characteristics (10 m) 2018 (P2023A) ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_GHSL_P2023A_GHS_BUILT_C_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_C.md.txt) | | This spatial raster dataset delineates human settlements at 10 m resolution, and describes their inner characteristics in terms of the functional and height-related components of the built environment. More information about the GHSL data products can be found in the GHSL Data Package 2023 report ... | | [building](https://developers.google.com/earth-engine/datasets/tags/building.md.txt) [built](https://developers.google.com/earth-engine/datasets/tags/built.md.txt) [builtup](https://developers.google.com/earth-engine/datasets/tags/builtup.md.txt) [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus.md.txt) [ghsl](https://developers.google.com/earth-engine/datasets/tags/ghsl.md.txt) [height](https://developers.google.com/earth-engine/datasets/tags/height.md.txt) | - |---| | [### GLIMS 2023: Global Land Ice Measurements From Space ![](https://developers.google.com/earth-engine/datasets/images/GLIMS/GLIMS_20230607_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/GLIMS_20230607.md.txt) | | Global Land Ice Measurements from Space (GLIMS) is an international initiative with the goal of repeatedly surveying the world's estimated 200,000 glaciers. The project seeks to create a globally comprehensive inventory of land ice, including measurements of glacier area, geometry, surface velocity, and snow line ... | | [cryosphere](https://developers.google.com/earth-engine/datasets/tags/cryosphere.md.txt) [glacier](https://developers.google.com/earth-engine/datasets/tags/glacier.md.txt) [glims](https://developers.google.com/earth-engine/datasets/tags/glims.md.txt) [ice](https://developers.google.com/earth-engine/datasets/tags/ice.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [nasa](https://developers.google.com/earth-engine/datasets/tags/nasa.md.txt) | - |---| | [### GLIMS Current: Global Land Ice Measurements From Space ![](https://developers.google.com/earth-engine/datasets/images/GLIMS/GLIMS_current_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/GLIMS_current.md.txt) | | Global Land Ice Measurements from Space (GLIMS) is an international initiative with the goal of repeatedly surveying the world's estimated 200,000 glaciers. The project seeks to create a globally comprehensive inventory of land ice, including measurements of glacier area, geometry, surface velocity, and snow line ... | | [cryosphere](https://developers.google.com/earth-engine/datasets/tags/cryosphere.md.txt) [glacier](https://developers.google.com/earth-engine/datasets/tags/glacier.md.txt) [glims](https://developers.google.com/earth-engine/datasets/tags/glims.md.txt) [ice](https://developers.google.com/earth-engine/datasets/tags/ice.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [nasa](https://developers.google.com/earth-engine/datasets/tags/nasa.md.txt) | - |---| | [### GPW Annual Dominant Class of Grasslands v1 ![](https://developers.google.com/earth-engine/datasets/images/global-pasture-watch/projects_global-pasture-watch_assets_ggc-30m_v1_grassland_c_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_global-pasture-watch_assets_ggc-30m_v1_grassland_c.md.txt) | | This dataset provides global annual dominant class maps of grasslands (cultivated and natural/semi-natural) from 2000 to 2022 at 30-m spatial resolution. Produced by the Land \& Carbon Lab Global Pasture Watch initiative, the mapped grassland extent includes any land cover type, which contains at least ... | | [global](https://developers.google.com/earth-engine/datasets/tags/global.md.txt) [global-pasture-watch](https://developers.google.com/earth-engine/datasets/tags/global-pasture-watch.md.txt) [land](https://developers.google.com/earth-engine/datasets/tags/land.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### GPW Annual Probabilities of Cultivated Grasslands v1 ![](https://developers.google.com/earth-engine/datasets/images/global-pasture-watch/projects_global-pasture-watch_assets_ggc-30m_v1_cultiv-grassland_p_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_global-pasture-watch_assets_ggc-30m_v1_cultiv-grassland_p.md.txt) | | This dataset provides global annual probability maps of cultivated grassland from 2000 to 2022 at 30-m spatial resolution. Produced by the Land \& Carbon Lab Global Pasture Watch initiative, the mapped grassland extent includes any land cover type, which contains at least 30% of dry ... | | [global](https://developers.google.com/earth-engine/datasets/tags/global.md.txt) [global-pasture-watch](https://developers.google.com/earth-engine/datasets/tags/global-pasture-watch.md.txt) [land](https://developers.google.com/earth-engine/datasets/tags/land.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### GPW Annual Probabilities of Natural/Semi-natural Grasslands v1 ![](https://developers.google.com/earth-engine/datasets/images/global-pasture-watch/projects_global-pasture-watch_assets_ggc-30m_v1_nat-semi-grassland_p_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_global-pasture-watch_assets_ggc-30m_v1_nat-semi-grassland_p.md.txt) | | This dataset provides global annual probability maps of natural/semi-natural grassland from 2000 to 2022 at 30-m spatial resolution. Produced by the Land \& Carbon Lab Global Pasture Watch initiative, the mapped grassland extent includes any land cover type, which contains at least 30% of dry ... | | [global](https://developers.google.com/earth-engine/datasets/tags/global.md.txt) [global-pasture-watch](https://developers.google.com/earth-engine/datasets/tags/global-pasture-watch.md.txt) [land](https://developers.google.com/earth-engine/datasets/tags/land.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### GPW Annual short vegetation height v1 ![](https://developers.google.com/earth-engine/datasets/images/global-pasture-watch/projects_global-pasture-watch_assets_gsvh-30m_v1_short-veg-height_m_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_global-pasture-watch_assets_gsvh-30m_v1_short-veg-height_m.md.txt) | | This dataset provides global median vegetation height from 2000 at 30-m spatial resolution. Produced by the Land \& Carbon Lab's Global Pasture Watch initiative, this dataset provides median vegetation height values (50th percentile) globally at 30-m spatial resolution from 2000 onwards. The dataset is based ... | | [canopy](https://developers.google.com/earth-engine/datasets/tags/canopy.md.txt) [global](https://developers.google.com/earth-engine/datasets/tags/global.md.txt) [global-pasture-watch](https://developers.google.com/earth-engine/datasets/tags/global-pasture-watch.md.txt) [land](https://developers.google.com/earth-engine/datasets/tags/land.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [plant-productivity](https://developers.google.com/earth-engine/datasets/tags/plant-productivity.md.txt) | - |---| | [### GPW Annual uncalibrated Gross Primary Productivity (uGPP) v1 ![](https://developers.google.com/earth-engine/datasets/images/global-pasture-watch/projects_global-pasture-watch_assets_ggpp-30m_v1_ugpp_m_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_global-pasture-watch_assets_ggpp-30m_v1_ugpp_m.md.txt) | | This dataset provides global uncalibrated EO-based Gross Primary Productivity from 2000 at 30-m spatial resolution. Produced by the Land \& Carbon Lab Global Pasture Watch initiative, the current dataset provides Gross Primary Productivity (GPP) values globally at 30-m spatial resolution from 2000 onwards. GPP values ... | | [global](https://developers.google.com/earth-engine/datasets/tags/global.md.txt) [global-pasture-watch](https://developers.google.com/earth-engine/datasets/tags/global-pasture-watch.md.txt) [land](https://developers.google.com/earth-engine/datasets/tags/land.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [plant-productivity](https://developers.google.com/earth-engine/datasets/tags/plant-productivity.md.txt) | - |---| | [### GlobCover: Global Land Cover Map ![](https://developers.google.com/earth-engine/datasets/images/ESA/ESA_GLOBCOVER_L4_200901_200912_V2_3_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/ESA_GLOBCOVER_L4_200901_200912_V2_3.md.txt) | | GlobCover 2009 is a global land cover map based on ENVISAT's Medium Resolution Imaging Spectrometer (MERIS) Level 1B data acquired in full resolution mode with a spatial resolution of approximately 300 meters. | | [esa](https://developers.google.com/earth-engine/datasets/tags/esa.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### Global 3-class PALSAR-2/PALSAR Forest/Non-Forest Map ![](https://developers.google.com/earth-engine/datasets/images/JAXA/JAXA_ALOS_PALSAR_YEARLY_FNF_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_FNF.md.txt) | | A newer version of this dataset with 4 classes for 2017-2020 can be found in JAXA/ALOS/PALSAR/YEARLY/FNF4 The global forest/non-forest map (FNF) is generated by classifying the SAR image (backscattering coefficient) in the global 25m resolution PALSAR-2/PALSAR SAR mosaic so that strong and low backscatter pixels ... | | [alos](https://developers.google.com/earth-engine/datasets/tags/alos.md.txt) [alos2](https://developers.google.com/earth-engine/datasets/tags/alos2.md.txt) [classification](https://developers.google.com/earth-engine/datasets/tags/classification.md.txt) [eroc](https://developers.google.com/earth-engine/datasets/tags/eroc.md.txt) [forest](https://developers.google.com/earth-engine/datasets/tags/forest.md.txt) [forest-biomass](https://developers.google.com/earth-engine/datasets/tags/forest-biomass.md.txt) | - |---| | [### Global 4-class PALSAR-2/PALSAR Forest/Non-Forest Map ![](https://developers.google.com/earth-engine/datasets/images/JAXA/JAXA_ALOS_PALSAR_YEARLY_FNF4_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_FNF4.md.txt) | | The global forest/non-forest map (FNF) is generated by classifying the SAR image (backscattering coefficient) in the global 25m resolution PALSAR-2/PALSAR SAR mosaic so that strong and low backscatter pixels are assigned as "forest" and "non-forest", respectively. Here, "forest" is defined as the natural forest with ... | | [alos](https://developers.google.com/earth-engine/datasets/tags/alos.md.txt) [alos2](https://developers.google.com/earth-engine/datasets/tags/alos2.md.txt) [classification](https://developers.google.com/earth-engine/datasets/tags/classification.md.txt) [eroc](https://developers.google.com/earth-engine/datasets/tags/eroc.md.txt) [forest](https://developers.google.com/earth-engine/datasets/tags/forest.md.txt) [forest-biomass](https://developers.google.com/earth-engine/datasets/tags/forest-biomass.md.txt) | - |---| | [### Global Oil Palm Extent and Planting Year (1990-2021) v1.2 ![](https://developers.google.com/earth-engine/datasets/images/BIOPAMA/BIOPAMA_GlobalOilPalm_v1_2_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/BIOPAMA_GlobalOilPalm_v1_2.md.txt) | | Global oil palm extent for 2016-2021 at 10 m resolution and oil palm planting year from 1990 to 2021 at 30 m resolution. The dataset consists of 609 100x100 km grid tiles covering tropical and subtropical oil-palm-growing regions worldwide, mapping 23.98 Mha of closed-canopy oil ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture.md.txt) [biodiversity](https://developers.google.com/earth-engine/datasets/tags/biodiversity.md.txt) [conservation](https://developers.google.com/earth-engine/datasets/tags/conservation.md.txt) [crop](https://developers.google.com/earth-engine/datasets/tags/crop.md.txt) [global](https://developers.google.com/earth-engine/datasets/tags/global.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) | - |---| | [### Global map of Local Climate Zones, latest version ![](https://developers.google.com/earth-engine/datasets/images/RUB/RUB_RUBCLIM_LCZ_global_lcz_map_latest_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/RUB_RUBCLIM_LCZ_global_lcz_map_latest.md.txt) | | Since their introduction in 2012, Local Climate Zones (LCZs) emerged as a new standard for characterizing urban landscapes, providing a holistic classification approach that takes into account micro-scale land-cover and associated physical properties. This global map of Local Climate Zones, at 100m pixel size and ... | | [climate](https://developers.google.com/earth-engine/datasets/tags/climate.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [urban](https://developers.google.com/earth-engine/datasets/tags/urban.md.txt) | - |---| | [### Google Global Landsat-based CCDC Segments (1999-2019) ![](https://developers.google.com/earth-engine/datasets/images/GOOGLE/GOOGLE_GLOBAL_CCDC_V1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_GLOBAL_CCDC_V1.md.txt) | | This collection contains precomputed results from running the Continuous Change Detection and Classification (CCDC) algorithm on 20 years of Landsat surface reflectance data. CCDC is a break-point finding algorithm that uses harmonic fitting with a dynamic RMSE threshold to detect breakpoints in time-series data. The ... | | [change-detection](https://developers.google.com/earth-engine/datasets/tags/change-detection.md.txt) [google](https://developers.google.com/earth-engine/datasets/tags/google.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### Iran Land Cover Map v1 13-class (2017) ![](https://developers.google.com/earth-engine/datasets/images/KNTU/KNTU_LiDARLab_IranLandCover_V1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/KNTU_LiDARLab_IranLandCover_V1.md.txt) | | The Iran-wide land cover map was generated by processing Sentinel imagery within the Google Earth Engine Cloud platform. For this purpose, over 2,500 Sentinel-1 and over 11,000 Sentinel-2 images were processed to produce a single mosaic dataset for the year 2017. Then, an object-based Random ... | | [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### LUCAS Copernicus (Polygons with attributes, 2018) V1 ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_LUCAS_HARMO_COPERNICUS_POLYGONS_V1_2018_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_LUCAS_HARMO_COPERNICUS_POLYGONS_V1_2018.md.txt) | | The Land Use/Cover Area frame Survey (LUCAS) in the European Union (EU) was set up to provide statistical information. It represents a triennial in-situ landcover and land-use data-collection exercise that extends over the whole of the EU's territory. LUCAS collects information on land cover and ... | | [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus.md.txt) [eu](https://developers.google.com/earth-engine/datasets/tags/eu.md.txt) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) | - |---| | [### LUCAS Harmonized (Theoretical Location, 2006-2018) V1 ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_LUCAS_HARMO_THLOC_V1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_LUCAS_HARMO_THLOC_V1.md.txt) | | The Land Use/Cover Area frame Survey (LUCAS) in the European Union (EU) was set up to provide statistical information. It represents a triennial in-situ landcover and land-use data-collection exercise that extends over the whole of the EU's territory. LUCAS collects information on land cover and ... | | [eu](https://developers.google.com/earth-engine/datasets/tags/eu.md.txt) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [lucas](https://developers.google.com/earth-engine/datasets/tags/lucas.md.txt) | - |---| | [### LUCAS THLOC (Points with attributes, 2022) V1 ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_LUCAS_THLOC_V1_2022_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_LUCAS_THLOC_V1_2022.md.txt) | | The Land Use/Cover Area frame Survey (LUCAS) in the European Union (EU) was set up to provide statistical information. It represents a triennial in-situ landcover and land-use data-collection exercise that extends over the whole of the EU's territory. LUCAS collects information on land cover and ... | | [eu](https://developers.google.com/earth-engine/datasets/tags/eu.md.txt) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [lucas](https://developers.google.com/earth-engine/datasets/tags/lucas.md.txt) | - |---| | [### Land Cover of North America at 30 meters, 2020 ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_NLCD_RELEASES_2020_REL_NALCMS_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2020_REL_NALCMS.md.txt) | | The 2020 North American Land Cover 30-meter dataset was produced as part of the North American Land Change Monitoring System (NALCMS), a trilateral effort between Natural Resources Canada, the United States Geological Survey, and three Mexican organizations including the National Institute of Statistics and Geography ... | | [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landsat](https://developers.google.com/earth-engine/datasets/tags/landsat.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [nlcd](https://developers.google.com/earth-engine/datasets/tags/nlcd.md.txt) [reflectance](https://developers.google.com/earth-engine/datasets/tags/reflectance.md.txt) | - |---| | [### MCD12C1.061 MODIS Land Cover Type Yearly Global 0.05 Deg CMG ![](https://developers.google.com/earth-engine/datasets/images/MODIS/MODIS_061_MCD12C1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD12C1.md.txt) | | The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) (MCD12C1) Version 6.1 data product provides a spatially aggregated and reprojected version of the tiled MCD12Q1 Version 6.1 data product. Maps of the International Geosphere-Biosphere Programme (IGBP), University of ... | | [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [modis](https://developers.google.com/earth-engine/datasets/tags/modis.md.txt) [nasa](https://developers.google.com/earth-engine/datasets/tags/nasa.md.txt) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs.md.txt) [yearly](https://developers.google.com/earth-engine/datasets/tags/yearly.md.txt) | - |---| | [### MCD12Q1.061 MODIS Land Cover Type Yearly Global 500m ![](https://developers.google.com/earth-engine/datasets/images/MODIS/MODIS_061_MCD12Q1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD12Q1.md.txt) | | The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) Version 6.1 data product provides global land cover types at yearly intervals. The MCD12Q1 Version 6.1 data product is derived using supervised classifications of MODIS Terra and Aqua reflectance data. Land ... | | [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [modis](https://developers.google.com/earth-engine/datasets/tags/modis.md.txt) [nasa](https://developers.google.com/earth-engine/datasets/tags/nasa.md.txt) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs.md.txt) [yearly](https://developers.google.com/earth-engine/datasets/tags/yearly.md.txt) | - |---| | [### Monitoring Trends in Burn Severity (MTBS) Burn Severity Images ![](https://developers.google.com/earth-engine/datasets/images/USFS/USFS_GTAC_MTBS_annual_burn_severity_mosaics_v1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USFS_GTAC_MTBS_annual_burn_severity_mosaics_v1.md.txt) | | The burn severity mosaics consist of thematic raster images of MTBS burn severity classes for all currently completed MTBS fires for the continental United States, Alaska, Hawaii and Puerto Rico. Mosaicked burn severity images are compiled annually for each year by US State and the ... | | [eros](https://developers.google.com/earth-engine/datasets/tags/eros.md.txt) [fire](https://developers.google.com/earth-engine/datasets/tags/fire.md.txt) [forest](https://developers.google.com/earth-engine/datasets/tags/forest.md.txt) [gtac](https://developers.google.com/earth-engine/datasets/tags/gtac.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived.md.txt) | - |---| | [### NLCD 2019: USGS National Land Cover Database, 2019 release ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_NLCD_RELEASES_2019_REL_NLCD_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2019_REL_NLCD.md.txt) | | NLCD (the National Land Cover Database) is a 30-m Landsat-based land cover database spanning 8 epochs (2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019). A ninth epoch for 2021 is also available here. The images rely on the imperviousness data layer for the urban ... | | [blm](https://developers.google.com/earth-engine/datasets/tags/blm.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [mrlc](https://developers.google.com/earth-engine/datasets/tags/mrlc.md.txt) [nlcd](https://developers.google.com/earth-engine/datasets/tags/nlcd.md.txt) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs.md.txt) | - |---| | [### NLCD 2021: USGS National Land Cover Database, 2021 release ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_NLCD_RELEASES_2021_REL_NLCD_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2021_REL_NLCD.md.txt) | | The U.S. Geological Survey (USGS), in partnership with several federal agencies, has now developed and released seven National Land Cover Database (NLCD) products: NLCD 1992, 2001, 2006, 2011, 2016, 2019, and 2021. Beginning with the 2016 release, land cover products were created for two-to-three-year intervals ... | | [blm](https://developers.google.com/earth-engine/datasets/tags/blm.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [mrlc](https://developers.google.com/earth-engine/datasets/tags/mrlc.md.txt) [nlcd](https://developers.google.com/earth-engine/datasets/tags/nlcd.md.txt) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs.md.txt) | - |---| | [### Oxford MAP: Malaria Atlas Project Fractional International Geosphere-Biosphere Programme Landcover ![](https://developers.google.com/earth-engine/datasets/images/Oxford/Oxford_MAP_IGBP_Fractional_Landcover_5km_Annual_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/Oxford_MAP_IGBP_Fractional_Landcover_5km_Annual.md.txt) | | The underlying dataset for this landcover product is the IGBP layer found within the MODIS annual landcover product (MCD12Q1). This data was converted from its categorical format, which has a ≈500 meter resolution, to a fractional product indicating the integer percentage (0-100) of the output ... | | [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [map](https://developers.google.com/earth-engine/datasets/tags/map.md.txt) | - |---| | [### SBTN Natural Lands Map v1 ![](https://developers.google.com/earth-engine/datasets/images/WRI/WRI_SBTN_naturalLands_v1_2020_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/WRI_SBTN_naturalLands_v1_2020.md.txt) | | The SBTN Natural Lands Map v1 is a 2020 baseline map of natural and non-natural land covers intended for use by companies setting science-based targets for nature, specifically the SBTN Land target #1: no conversion of natural ecosystems. "Natural" and "non-natural" definitions were adapted from ... | | [ecosystems](https://developers.google.com/earth-engine/datasets/tags/ecosystems.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [wri](https://developers.google.com/earth-engine/datasets/tags/wri.md.txt) | - |---| | [### SBTN Natural Lands Map v1.1 ![](https://developers.google.com/earth-engine/datasets/images/WRI/WRI_SBTN_naturalLands_v1_1_2020_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/WRI_SBTN_naturalLands_v1_1_2020.md.txt) | | The SBTN Natural Lands Map v1.1 is a 2020 baseline map of natural and non-natural land covers intended for use by companies setting science-based targets for nature, specifically the SBTN Land target #1: no conversion of natural ecosystems. "Natural" and "non-natural" definitions were adapted from ... | | [ecosystems](https://developers.google.com/earth-engine/datasets/tags/ecosystems.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover.md.txt) [wri](https://developers.google.com/earth-engine/datasets/tags/wri.md.txt) | - |---| | [### TNC Global Human Modification v3 (Change-Consistent 300m) ![](https://developers.google.com/earth-engine/datasets/images/TNC/TNC_HM_v3_300m_c_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/TNC_HM_v3_300m_c.md.txt) | | The Global Human Modification v3 dataset measures cumulative human pressures on global terrestrial ecosystems (excluding Antarctica). It tracks data from 1990 to 2022 and is intended to help quantify human impact for conservation planning, policy-making, and research. This dataset is the "Change-Consistent" Series ("c" series) ... | | [fragmentation](https://developers.google.com/earth-engine/datasets/tags/fragmentation.md.txt) [human-modification](https://developers.google.com/earth-engine/datasets/tags/human-modification.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landscape-gradient](https://developers.google.com/earth-engine/datasets/tags/landscape-gradient.md.txt) [population](https://developers.google.com/earth-engine/datasets/tags/population.md.txt) [stressors](https://developers.google.com/earth-engine/datasets/tags/stressors.md.txt) | - |---| | [### TNC Global Human Modification v3 (Static Snapshot 90m) ![](https://developers.google.com/earth-engine/datasets/images/TNC/TNC_HM_v3_90m_s_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/TNC_HM_v3_90m_s.md.txt) | | The Global Human Modification v3 dataset measures cumulative human pressures on global terrestrial ecosystems (excluding Antarctica). It tracks data from 1990 to 2022 and is intended to help quantify human impact for conservation planning, policy-making, and research. This is the 2022 static snapshot ("s" series) ... | | [fragmentation](https://developers.google.com/earth-engine/datasets/tags/fragmentation.md.txt) [human-modification](https://developers.google.com/earth-engine/datasets/tags/human-modification.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landscape-gradient](https://developers.google.com/earth-engine/datasets/tags/landscape-gradient.md.txt) [population](https://developers.google.com/earth-engine/datasets/tags/population.md.txt) [stressors](https://developers.google.com/earth-engine/datasets/tags/stressors.md.txt) | - |---| | [### USDA NASS Cropland Data Layers ![](https://developers.google.com/earth-engine/datasets/images/USDA/USDA_NASS_CDL_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USDA_NASS_CDL.md.txt) | | The Cropland Data Layer (CDL) is a crop-specific land cover data layer created annually for the continental United States using moderate resolution satellite imagery and extensive agricultural ground truth. The CDL is created by the USDA, National Agricultural Statistics Service (NASS), Research and Development Division, ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture.md.txt) [crop](https://developers.google.com/earth-engine/datasets/tags/crop.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [usda](https://developers.google.com/earth-engine/datasets/tags/usda.md.txt) | - |---| | [### USFS Landscape Change Monitoring System v2025-11 (CONUS and OCONUS) ![](https://developers.google.com/earth-engine/datasets/images/gtac-data-publish/projects_gtac-data-publish_assets_LCMS_Product_Version_2025-11_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_gtac-data-publish_assets_LCMS_Product_Version_2025-11.md.txt) | | This product is part of the Landscape Change Monitoring System (LCMS) data suite. It shows LCMS-modeled change, land cover, and/or land use classes for each year and covers the Conterminous United States (CONUS) as well as areas outside the CONUS (OCONUS) including Alaska (AK), Puerto ... | | [change-detection](https://developers.google.com/earth-engine/datasets/tags/change-detection.md.txt) [forest](https://developers.google.com/earth-engine/datasets/tags/forest.md.txt) [fsic-go](https://developers.google.com/earth-engine/datasets/tags/fsic-go.md.txt) [gtac](https://developers.google.com/earth-engine/datasets/tags/gtac.md.txt) [gtac-data-publish](https://developers.google.com/earth-engine/datasets/tags/gtac-data-publish.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) | - |---| | [### USFS TreeMap 2023-1 ![](https://developers.google.com/earth-engine/datasets/images/gtac-data-publish/projects_gtac-data-publish_assets_TreeMap_Product_Version_2023-1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_gtac-data-publish_assets_TreeMap_Product_Version_2023-1.md.txt) | | TreeMap datasets provide detailed spatial information on forest characteristics across the entire forested extent of the Conterminous United States (CONUS) for the years 2016, 2020, 2022, and 2023. TreeMap 2014 is also available for CONUS but not included in this data archive. TreeMap 2024 is ... | | [aboveground](https://developers.google.com/earth-engine/datasets/tags/aboveground.md.txt) [biomass](https://developers.google.com/earth-engine/datasets/tags/biomass.md.txt) [carbon](https://developers.google.com/earth-engine/datasets/tags/carbon.md.txt) [climate-change](https://developers.google.com/earth-engine/datasets/tags/climate-change.md.txt) [conus](https://developers.google.com/earth-engine/datasets/tags/conus.md.txt) [forest](https://developers.google.com/earth-engine/datasets/tags/forest.md.txt) | - |---| | [### USGS GAP Alaska 2001 ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_GAP_AK_2001_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_GAP_AK_2001.md.txt) | | The GAP/LANDFIRE National Terrestrial Ecosystems data represents a detailed vegetation and land cover classification for the Conterminous U.S., Alaska, Hawaii, and Puerto Rico.GAP/LF 2011 Ecosystems for the Conterminous U.S. is an update of the National Gap Analysis Program Land Cover Data - Version 2.2. Alaska ... | | [ecosystems](https://developers.google.com/earth-engine/datasets/tags/ecosystems.md.txt) [gap](https://developers.google.com/earth-engine/datasets/tags/gap.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landfire](https://developers.google.com/earth-engine/datasets/tags/landfire.md.txt) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs.md.txt) [vegetation](https://developers.google.com/earth-engine/datasets/tags/vegetation.md.txt) | - |---| | [### USGS GAP CONUS 2011 ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_GAP_CONUS_2011_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_GAP_CONUS_2011.md.txt) | | The GAP/LANDFIRE National Terrestrial Ecosystems data represents a detailed vegetation and land cover classification for the Conterminous U.S., Alaska, Hawaii, and Puerto Rico.GAP/LF 2011 Ecosystems for the Conterminous U.S. is an update of the National Gap Analysis Program Land Cover Data - Version 2.2. Alaska ... | | [ecosystems](https://developers.google.com/earth-engine/datasets/tags/ecosystems.md.txt) [gap](https://developers.google.com/earth-engine/datasets/tags/gap.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landfire](https://developers.google.com/earth-engine/datasets/tags/landfire.md.txt) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs.md.txt) [vegetation](https://developers.google.com/earth-engine/datasets/tags/vegetation.md.txt) | - |---| | [### USGS GAP Hawaii 2001 ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_GAP_HI_2001_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_GAP_HI_2001.md.txt) | | The GAP/LANDFIRE National Terrestrial Ecosystems data represents a detailed vegetation and land cover classification for the Conterminous U.S., Alaska, Hawaii, and Puerto Rico.GAP/LF 2011 Ecosystems for the Conterminous U.S. is an update of the National Gap Analysis Program Land Cover Data - Version 2.2. Alaska ... | | [ecosystems](https://developers.google.com/earth-engine/datasets/tags/ecosystems.md.txt) [gap](https://developers.google.com/earth-engine/datasets/tags/gap.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landfire](https://developers.google.com/earth-engine/datasets/tags/landfire.md.txt) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs.md.txt) [vegetation](https://developers.google.com/earth-engine/datasets/tags/vegetation.md.txt) | - |---| | [### USGS GAP Puerto Rico 2001 ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_GAP_PR_2001_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_GAP_PR_2001.md.txt) | | The GAP/LANDFIRE National Terrestrial Ecosystems data represents a detailed vegetation and land cover classification for the Conterminous U.S., Alaska, Hawaii, and Puerto Rico.GAP/LF 2011 Ecosystems for the Conterminous U.S. is an update of the National Gap Analysis Program Land Cover Data - Version 2.2. Alaska ... | | [ecosystems](https://developers.google.com/earth-engine/datasets/tags/ecosystems.md.txt) [gap](https://developers.google.com/earth-engine/datasets/tags/gap.md.txt) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landfire](https://developers.google.com/earth-engine/datasets/tags/landfire.md.txt) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs.md.txt) [vegetation](https://developers.google.com/earth-engine/datasets/tags/vegetation.md.txt) | - |---| | [### World Settlement Footprint 2015 ![](https://developers.google.com/earth-engine/datasets/images/DLR/DLR_WSF_WSF2015_v1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/DLR_WSF_WSF2015_v1.md.txt) | | The World Settlement Footprint (WSF) 2015 is a 10m resolution binary mask outlining the extent of human settlements globally derived by means of 2014-2015 multitemporal Landsat-8 and Sentinel-1 imagery (of which \~217,000 and \~107,000 scenes have been processed, respectively). The temporal dynamics of human settlements ... | | [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover.md.txt) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived.md.txt) [population](https://developers.google.com/earth-engine/datasets/tags/population.md.txt) [sentinel1-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel1-derived.md.txt) [settlement](https://developers.google.com/earth-engine/datasets/tags/settlement.md.txt) [urban](https://developers.google.com/earth-engine/datasets/tags/urban.md.txt) |