- |---| | [### 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) | | 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) [eea](https://developers.google.com/earth-engine/datasets/tags/eea) [esa](https://developers.google.com/earth-engine/datasets/tags/esa) [eu](https://developers.google.com/earth-engine/datasets/tags/eu) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [eea](https://developers.google.com/earth-engine/datasets/tags/eea) [esa](https://developers.google.com/earth-engine/datasets/tags/esa) [eu](https://developers.google.com/earth-engine/datasets/tags/eu) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [deforestation](https://developers.google.com/earth-engine/datasets/tags/deforestation) [forest](https://developers.google.com/earth-engine/datasets/tags/forest) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [tsinghua](https://developers.google.com/earth-engine/datasets/tags/tsinghua) | - |---| | [### 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) | | 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) [google](https://developers.google.com/earth-engine/datasets/tags/google) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [nrt](https://developers.google.com/earth-engine/datasets/tags/nrt) | - |---| | [### 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) | | 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) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [sentinel1-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel1-derived) [sentinel2-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel2-derived) | - |---| | [### 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) | | 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) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [sentinel1-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel1-derived) [sentinel2-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel2-derived) | - |---| | [### Farmscapes 2020 ![](https://developers.google.com/earth-engine/datasets/images/nature-trace/projects_nature-trace_assets_farmscapes_england_v1_0_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_nature-trace_assets_farmscapes_england_v1_0) | | The Farmscapes 2020 dataset provides high-resolution (25cm) probability maps for three key semi-natural features within England's agricultural landscapes: hedgerows, woodland, and stone walls. This dataset was developed in collaboration with the Leverhulme Centre for Nature Recovery at Oxford to serve as a baseline for applications ... | | [biodiversity](https://developers.google.com/earth-engine/datasets/tags/biodiversity) [climate](https://developers.google.com/earth-engine/datasets/tags/climate) [conservation](https://developers.google.com/earth-engine/datasets/tags/conservation) [ecological-connectivity](https://developers.google.com/earth-engine/datasets/tags/ecological-connectivity) [forest](https://developers.google.com/earth-engine/datasets/tags/forest) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### Farmscapes 2020 Vectorised ![](https://developers.google.com/earth-engine/datasets/images/nature-trace/projects_nature-trace_assets_farmscapes_england_v1_0_vectorised_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_nature-trace_assets_farmscapes_england_v1_0_vectorised) | | This is the vectorised version of the Farmscapes 2020 raster dataset. It provides polygon geometries representing fine-scale semi-natural landscape features (specifically hedgerows, woodland, and stone walls) across England's agricultural landscapes. This dataset was developed in collaboration with the Oxford Leverhulme Centre for Nature Recovery to ... | | [biodiversity](https://developers.google.com/earth-engine/datasets/tags/biodiversity) [climate](https://developers.google.com/earth-engine/datasets/tags/climate) [conservation](https://developers.google.com/earth-engine/datasets/tags/conservation) [ecological-connectivity](https://developers.google.com/earth-engine/datasets/tags/ecological-connectivity) [forest](https://developers.google.com/earth-engine/datasets/tags/forest) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [global-pasture-watch](https://developers.google.com/earth-engine/datasets/tags/global-pasture-watch) [land](https://developers.google.com/earth-engine/datasets/tags/land) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [global-pasture-watch](https://developers.google.com/earth-engine/datasets/tags/global-pasture-watch) [land](https://developers.google.com/earth-engine/datasets/tags/land) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [global-pasture-watch](https://developers.google.com/earth-engine/datasets/tags/global-pasture-watch) [land](https://developers.google.com/earth-engine/datasets/tags/land) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### Global Annual Mangrove Extent (1984-2023) ![](https://developers.google.com/earth-engine/datasets/images/mangrovedatahub2/projects_mangrovedatahub2_assets_CGMD-Extent30_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_mangrovedatahub2_assets_CGMD-Extent30) | | The CGMD-Extent30 (Continuous Global Mangrove Dynamics-Annual Mangrove Extent at 30-m resolution) dataset provides global annual mangrove extent from 1984 to 2023. The dataset is distributed as a single Earth Engine FeatureCollection, with each feature representing a mapped mangrove polygon for a specific year. The dataset ... | | [annual](https://developers.google.com/earth-engine/datasets/tags/annual) [coastal](https://developers.google.com/earth-engine/datasets/tags/coastal) [forest-biomass](https://developers.google.com/earth-engine/datasets/tags/forest-biomass) [global](https://developers.google.com/earth-engine/datasets/tags/global) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [biodiversity](https://developers.google.com/earth-engine/datasets/tags/biodiversity) [conservation](https://developers.google.com/earth-engine/datasets/tags/conservation) [crop](https://developers.google.com/earth-engine/datasets/tags/crop) [global](https://developers.google.com/earth-engine/datasets/tags/global) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) | - |---| | [### 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) | | 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) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [urban](https://developers.google.com/earth-engine/datasets/tags/urban) | - |---| | [### 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) | | 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) [google](https://developers.google.com/earth-engine/datasets/tags/google) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [eu](https://developers.google.com/earth-engine/datasets/tags/eu) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) | - |---| | [### 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) | | 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) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [lucas](https://developers.google.com/earth-engine/datasets/tags/lucas) | - |---| | [### 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) | | 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) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse](https://developers.google.com/earth-engine/datasets/tags/landuse) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [lucas](https://developers.google.com/earth-engine/datasets/tags/lucas) | - |---| | [### 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) | | 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) [landsat](https://developers.google.com/earth-engine/datasets/tags/landsat) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [nlcd](https://developers.google.com/earth-engine/datasets/tags/nlcd) [reflectance](https://developers.google.com/earth-engine/datasets/tags/reflectance) | - |---| | [### 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) | | 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) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [modis](https://developers.google.com/earth-engine/datasets/tags/modis) [nasa](https://developers.google.com/earth-engine/datasets/tags/nasa) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs) [yearly](https://developers.google.com/earth-engine/datasets/tags/yearly) | - |---| | [### 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) | | 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) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [modis](https://developers.google.com/earth-engine/datasets/tags/modis) [nasa](https://developers.google.com/earth-engine/datasets/tags/nasa) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs) [yearly](https://developers.google.com/earth-engine/datasets/tags/yearly) | - |---| | [### MCD12Q2.006 Land Cover Dynamics Yearly Global 500m ![](https://developers.google.com/earth-engine/datasets/images/MODIS/MODIS_061_MCD12Q2_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD12Q2) | | The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Dynamics (MCD12Q2) Version 6.1 data product provides global land surface phenology metrics at yearly intervals. The MCD12Q2 Version 6.1 data product is derived from time series of the 2-band Enhanced Vegetation Index (EVI2) ... | | [evi](https://developers.google.com/earth-engine/datasets/tags/evi) [global](https://developers.google.com/earth-engine/datasets/tags/global) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [modis](https://developers.google.com/earth-engine/datasets/tags/modis) [onset-greenness](https://developers.google.com/earth-engine/datasets/tags/onset-greenness) [phenology](https://developers.google.com/earth-engine/datasets/tags/phenology) | - |---| | [### MOD44B.061 Terra Vegetation Continuous Fields Yearly Global 250m ![](https://developers.google.com/earth-engine/datasets/images/MODIS/MODIS_061_MOD44B_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD44B) | | The Terra MODIS Vegetation Continuous Fields (VCF) product is a sub-pixel-level representation of surface vegetation cover estimates globally. Designed to continuously represent Earth's terrestrial surface as a proportion of basic vegetation traits, it provides a gradation of three surface cover components: percent tree cover, percent ... | | [annual](https://developers.google.com/earth-engine/datasets/tags/annual) [geophysical](https://developers.google.com/earth-engine/datasets/tags/geophysical) [global](https://developers.google.com/earth-engine/datasets/tags/global) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [modis](https://developers.google.com/earth-engine/datasets/tags/modis) [nasa](https://developers.google.com/earth-engine/datasets/tags/nasa) | - |---| | [### MapBiomas Land Use and Land Cover - Bolivia V1.0 ![](https://developers.google.com/earth-engine/datasets/images/mapbiomas-public/projects_mapbiomas-public_assets_bolivia_lulc_v1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_mapbiomas-public_assets_bolivia_lulc_v1) | | MapBiomas Land Use and Land Cover (LULC) dataset for Bolivia is produced annually by the MapBiomas Project using Landsat satellite imagery and machine learning classification techniques. The dataset provides consistent annual land cover maps at 30-meter resolution covering the period from 1985 to 2024. Bolivia's ... | | [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [mapbiomas-public](https://developers.google.com/earth-engine/datasets/tags/mapbiomas-public) [publisher-dataset](https://developers.google.com/earth-engine/datasets/tags/publisher-dataset) | - |---| | [### MapBiomas Land Use and Land Cover - Brazil V1.0 ![](https://developers.google.com/earth-engine/datasets/images/mapbiomas-public/projects_mapbiomas-public_assets_brazil_lulc_v1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_mapbiomas-public_assets_brazil_lulc_v1) | | MapBiomas Land Use and Land Cover (LULC) dataset for Brazil is produced annually by the MapBiomas Project using Landsat satellite imagery and machine learning classification techniques. The dataset provides consistent, thematically detailed maps at 30-meter resolution, covering multiple decades and updated each year. Each image ... | | [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [mapbiomas-public](https://developers.google.com/earth-engine/datasets/tags/mapbiomas-public) [publisher-dataset](https://developers.google.com/earth-engine/datasets/tags/publisher-dataset) | - |---| | [### MapBiomas Land Use and Land Cover - Ecuador V1.0 ![](https://developers.google.com/earth-engine/datasets/images/mapbiomas-public/projects_mapbiomas-public_assets_ecuador_lulc_v1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_mapbiomas-public_assets_ecuador_lulc_v1) | | MapBiomas Land Use and Land Cover (LULC) dataset for Ecuador is produced annually by the MapBiomas Project using Landsat satellite imagery and machine learning classification techniques. The dataset provides consistent annual land cover maps at 30-meter resolution covering the period from 1985 to 2024. Ecuador's ... | | [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [mapbiomas-public](https://developers.google.com/earth-engine/datasets/tags/mapbiomas-public) [publisher-dataset](https://developers.google.com/earth-engine/datasets/tags/publisher-dataset) | - |---| | [### 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) | | 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) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [mrlc](https://developers.google.com/earth-engine/datasets/tags/mrlc) [nlcd](https://developers.google.com/earth-engine/datasets/tags/nlcd) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs) | - |---| | [### 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) | | 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) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [mrlc](https://developers.google.com/earth-engine/datasets/tags/mrlc) [nlcd](https://developers.google.com/earth-engine/datasets/tags/nlcd) [usgs](https://developers.google.com/earth-engine/datasets/tags/usgs) | - |---| | [### 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) | | 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) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [map](https://developers.google.com/earth-engine/datasets/tags/map) | - |---| | [### RCMAP Rangeland Component Timeseries (1985-2023), v06 ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_COVER_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_COVER) | | 'The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, ... | | [climate-change](https://developers.google.com/earth-engine/datasets/tags/climate-change) [disturbance](https://developers.google.com/earth-engine/datasets/tags/disturbance) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [nlcd](https://developers.google.com/earth-engine/datasets/tags/nlcd) [rangeland](https://developers.google.com/earth-engine/datasets/tags/rangeland) | - |---| | [### RCMAP Rangeland Trends Year for Component Timeseries (1985-2023), v06 ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_TRENDS_YEAR_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_TRENDS_YEAR) | | This collection includes RCMAP yearly products from 1985 through 2023. The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual ... | | [climate-change](https://developers.google.com/earth-engine/datasets/tags/climate-change) [disturbance](https://developers.google.com/earth-engine/datasets/tags/disturbance) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [nlcd](https://developers.google.com/earth-engine/datasets/tags/nlcd) [rangeland](https://developers.google.com/earth-engine/datasets/tags/rangeland) | - |---| | [### RCMAP Rangeland Trends for Component Timeseries (1985-2023), v06 ![](https://developers.google.com/earth-engine/datasets/images/USGS/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_TRENDS_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_TRENDS) | | The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, ... | | [climate-change](https://developers.google.com/earth-engine/datasets/tags/climate-change) [disturbance](https://developers.google.com/earth-engine/datasets/tags/disturbance) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [nlcd](https://developers.google.com/earth-engine/datasets/tags/nlcd) [rangeland](https://developers.google.com/earth-engine/datasets/tags/rangeland) | - |---| | [### 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) | | 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) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [wri](https://developers.google.com/earth-engine/datasets/tags/wri) | - |---| | [### 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) | | 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) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [wri](https://developers.google.com/earth-engine/datasets/tags/wri) | - |---| | [### TUBerlin/BigEarthNet/v1 ![](https://developers.google.com/earth-engine/datasets/images/TUBerlin/TUBerlin_BigEarthNet_v1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/TUBerlin_BigEarthNet_v1) | | BigEarthNet is a new large-scale Sentinel-2 benchmark archive, consisting of 590,326 Sentinel-2 image patches. To construct BigEarthNet, 125 Sentinel-2 tiles were acquired between June 2017 and May 2018 over the 10 countries (Austria, Belgium, Finland, Ireland, Kosovo, Lithuania, Luxembourg, Portugal, Serbia, Switzerland) of Europe. All ... | | [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [ml](https://developers.google.com/earth-engine/datasets/tags/ml) [sentinel](https://developers.google.com/earth-engine/datasets/tags/sentinel) | - |---| | [### 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) | | 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) [forest](https://developers.google.com/earth-engine/datasets/tags/forest) [fsic-go](https://developers.google.com/earth-engine/datasets/tags/fsic-go) [gtac](https://developers.google.com/earth-engine/datasets/tags/gtac) [gtac-data-publish](https://developers.google.com/earth-engine/datasets/tags/gtac-data-publish) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) | - |---| | [### USFS Tree Canopy Cover v2025-6 (CONUS and OCONUS) ![](https://developers.google.com/earth-engine/datasets/images/gtac-data-publish/projects_gtac-data-publish_assets_TCC_Product_Version_2025-6_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_gtac-data-publish_assets_TCC_Product_Version_2025-6) | | The Tree Canopy Cover (TCC) data suite, produced by the United States Department of Agriculture, Forest Service (USFS), are annual remote sensing-based map outputs spanning from 1985-2025. These data support the National Land Cover Database (NLCD) project, which is managed by the US Geological Survey ... | | [forest](https://developers.google.com/earth-engine/datasets/tags/forest) [fsic-go](https://developers.google.com/earth-engine/datasets/tags/fsic-go) [gtac](https://developers.google.com/earth-engine/datasets/tags/gtac) [gtac-data-publish](https://developers.google.com/earth-engine/datasets/tags/gtac-data-publish) [landuse-landcover](https://developers.google.com/earth-engine/datasets/tags/landuse-landcover) [publisher-dataset](https://developers.google.com/earth-engine/datasets/tags/publisher-dataset) |