- |---| | [### Brazil Forest Imagery Dataset 2008: Analytic Basemap ![](https://developers.google.com/earth-engine/datasets/images/GOOGLE/GOOGLE_BRAZIL_FOREST_2008_V1_ANALYTIC_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_BRAZIL_FOREST_2008_V1_ANALYTIC) | | This dataset provides up to a 10-meter resolution multispectral (green, red, and near-infrared) basemap of Brazil, primarily captured in 2008, to support implementation of the Brazil Forest Code. The mosaic is synthesized from SPOT 2, 4, and 5 satellite data. It serves as a higher-resolution ... | | [brazil](https://developers.google.com/earth-engine/datasets/tags/brazil) [forest-code](https://developers.google.com/earth-engine/datasets/tags/forest-code) [google](https://developers.google.com/earth-engine/datasets/tags/google) [imagery](https://developers.google.com/earth-engine/datasets/tags/imagery) [multispectral](https://developers.google.com/earth-engine/datasets/tags/multispectral) [satellite-imagery](https://developers.google.com/earth-engine/datasets/tags/satellite-imagery) | - |---| | [### Brazil Forest Imagery Dataset 2008: Visual Basemap ![](https://developers.google.com/earth-engine/datasets/images/GOOGLE/GOOGLE_BRAZIL_FOREST_2008_V1_VISUAL_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_BRAZIL_FOREST_2008_V1_VISUAL) | | This dataset provides a visual imagery basemap of Brazil with up to 5-meter resolution, primarily captured in 2008, to support implementation of the Brazil Forest Code. The mosaic is synthesized from SPOT 2, 4, and 5 satellite data. It serves as a high-resolution alternative to ... | | [brazil](https://developers.google.com/earth-engine/datasets/tags/brazil) [deforestation](https://developers.google.com/earth-engine/datasets/tags/deforestation) [forest-code](https://developers.google.com/earth-engine/datasets/tags/forest-code) [google](https://developers.google.com/earth-engine/datasets/tags/google) [rgb](https://developers.google.com/earth-engine/datasets/tags/rgb) [satellite-imagery](https://developers.google.com/earth-engine/datasets/tags/satellite-imagery) | - |---| | [### Cloud Score+ S2_HARMONIZED V1 ![](https://developers.google.com/earth-engine/datasets/images/GOOGLE/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED) | | Cloud Score+ is a quality assessment (QA) processor for medium-to-high resolution optical satellite imagery. The Cloud Score+ S2_HARMONIZED dataset is being operationally produced from the harmonized Sentinel-2 L1C collection, and Cloud Score+ outputs can be used to identify relatively clear pixels and effectively remove clouds ... | | [cloud](https://developers.google.com/earth-engine/datasets/tags/cloud) [google](https://developers.google.com/earth-engine/datasets/tags/google) [satellite-imagery](https://developers.google.com/earth-engine/datasets/tags/satellite-imagery) [sentinel2-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel2-derived) | - |---| | [### 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) | - |---| | [### Earth Timelapse v0 ![](https://developers.google.com/earth-engine/datasets/images/ee-earth-timelapse/projects_ee-earth-timelapse_assets_annual_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_ee-earth-timelapse_assets_annual) | | The Earth Timelapse dataset provides a four-decade visual record of planetary change spanning from 1984 to 2022. Synthesized by Google from petabytes of spaceborne observations acquired by NASA/USGS Landsat missions (Landsat 4, 5, 7, 8, and 9) and ESA's Copernicus Sentinel-2 constellation, the dataset is ... | | [copernicus](https://developers.google.com/earth-engine/datasets/tags/copernicus) [global](https://developers.google.com/earth-engine/datasets/tags/global) [google](https://developers.google.com/earth-engine/datasets/tags/google) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [publisher-dataset](https://developers.google.com/earth-engine/datasets/tags/publisher-dataset) [satellite-imagery](https://developers.google.com/earth-engine/datasets/tags/satellite-imagery) | - |---| | [### GEM-15: Near-Global Surface and Terrain Elevation Models (15m) (Experimental) ![](https://developers.google.com/earth-engine/datasets/images/climate-and-sustainability/projects_climate-and-sustainability_assets_gem-15_v1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_climate-and-sustainability_assets_gem-15_v1) | | Google's Near-Global Elevation Models at 15m (GEM-15) is an experimental (under review) near-global elevation dataset at 15m grid spacing derived from sub-meter optical stereo satellite imagery. The dataset is built from optical stereo imagery acquired through 2024 (primarily 2022--2024 30cm Pléiades Neo imagery, supplemented by ... | | [climate-and-sustainability](https://developers.google.com/earth-engine/datasets/tags/climate-and-sustainability) [dem](https://developers.google.com/earth-engine/datasets/tags/dem) [elevation](https://developers.google.com/earth-engine/datasets/tags/elevation) [elevation-topography](https://developers.google.com/earth-engine/datasets/tags/elevation-topography) [google](https://developers.google.com/earth-engine/datasets/tags/google) [height](https://developers.google.com/earth-engine/datasets/tags/height) | - |---| | [### 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) | - |---| | [### JRC Global Surface Water Mapping Layers, v1.2 \[deprecated\] ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_GSW1_2_GlobalSurfaceWater_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_GSW1_2_GlobalSurfaceWater) | | This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2019 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its ... | | [geophysical](https://developers.google.com/earth-engine/datasets/tags/geophysical) [google](https://developers.google.com/earth-engine/datasets/tags/google) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [surface](https://developers.google.com/earth-engine/datasets/tags/surface) [surface-ground-water](https://developers.google.com/earth-engine/datasets/tags/surface-ground-water) | - |---| | [### JRC Global Surface Water Mapping Layers, v1.4 ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_GSW1_4_GlobalSurfaceWater_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_GSW1_4_GlobalSurfaceWater) | | This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its ... | | [change-detection](https://developers.google.com/earth-engine/datasets/tags/change-detection) [geophysical](https://developers.google.com/earth-engine/datasets/tags/geophysical) [google](https://developers.google.com/earth-engine/datasets/tags/google) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [surface](https://developers.google.com/earth-engine/datasets/tags/surface) | - |---| | [### JRC Global Surface Water Metadata, v1.4 ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_GSW1_4_Metadata_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_GSW1_4_Metadata) | | This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its ... | | [geophysical](https://developers.google.com/earth-engine/datasets/tags/geophysical) [google](https://developers.google.com/earth-engine/datasets/tags/google) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [surface](https://developers.google.com/earth-engine/datasets/tags/surface) [surface-ground-water](https://developers.google.com/earth-engine/datasets/tags/surface-ground-water) | - |---| | [### JRC Monthly Water History, v1.4 ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_GSW1_4_MonthlyHistory_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_GSW1_4_MonthlyHistory) | | This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its ... | | [geophysical](https://developers.google.com/earth-engine/datasets/tags/geophysical) [google](https://developers.google.com/earth-engine/datasets/tags/google) [history](https://developers.google.com/earth-engine/datasets/tags/history) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [monthly](https://developers.google.com/earth-engine/datasets/tags/monthly) | - |---| | [### JRC Monthly Water Recurrence, v1.4 ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_GSW1_4_MonthlyRecurrence_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_GSW1_4_MonthlyRecurrence) | | This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its ... | | [geophysical](https://developers.google.com/earth-engine/datasets/tags/geophysical) [google](https://developers.google.com/earth-engine/datasets/tags/google) [history](https://developers.google.com/earth-engine/datasets/tags/history) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [monthly](https://developers.google.com/earth-engine/datasets/tags/monthly) | - |---| | [### JRC Yearly Water Classification History, v1.4 ![](https://developers.google.com/earth-engine/datasets/images/JRC/JRC_GSW1_4_YearlyHistory_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/JRC_GSW1_4_YearlyHistory) | | This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its ... | | [annual](https://developers.google.com/earth-engine/datasets/tags/annual) [geophysical](https://developers.google.com/earth-engine/datasets/tags/geophysical) [google](https://developers.google.com/earth-engine/datasets/tags/google) [history](https://developers.google.com/earth-engine/datasets/tags/history) [jrc](https://developers.google.com/earth-engine/datasets/tags/jrc) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) | - |---| | [### Murray Global Intertidal Change Classification ![](https://developers.google.com/earth-engine/datasets/images/UQ/UQ_murray_Intertidal_v1_1_global_intertidal_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/UQ_murray_Intertidal_v1_1_global_intertidal) | | The Murray Global Intertidal Change Dataset contains global maps of tidal flat ecosystems produced via a supervised classification of 707,528 Landsat Archive images. Each pixel was classified into tidal flat, permanent water or other with reference to a globally distributed set of training data. The ... | | [coastal](https://developers.google.com/earth-engine/datasets/tags/coastal) [google](https://developers.google.com/earth-engine/datasets/tags/google) [intertidal](https://developers.google.com/earth-engine/datasets/tags/intertidal) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [murray](https://developers.google.com/earth-engine/datasets/tags/murray) [surface-ground-water](https://developers.google.com/earth-engine/datasets/tags/surface-ground-water) | - |---| | [### Murray Global Intertidal Change Data Mask ![](https://developers.google.com/earth-engine/datasets/images/UQ/UQ_murray_Intertidal_v1_1_data_mask_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/UQ_murray_Intertidal_v1_1_data_mask) | | The Murray Global Intertidal Change Dataset contains global maps of tidal flat ecosystems produced via a supervised classification of 707,528 Landsat Archive images. Each pixel was classified into tidal flat, permanent water or other with reference to a globally distributed set of training data. The ... | | [coastal](https://developers.google.com/earth-engine/datasets/tags/coastal) [google](https://developers.google.com/earth-engine/datasets/tags/google) [intertidal](https://developers.google.com/earth-engine/datasets/tags/intertidal) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [murray](https://developers.google.com/earth-engine/datasets/tags/murray) [surface-ground-water](https://developers.google.com/earth-engine/datasets/tags/surface-ground-water) | - |---| | [### Murray Global Intertidal Change QA Pixel Count ![](https://developers.google.com/earth-engine/datasets/images/UQ/UQ_murray_Intertidal_v1_1_qa_pixel_count_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/UQ_murray_Intertidal_v1_1_qa_pixel_count) | | The Murray Global Intertidal Change Dataset contains global maps of tidal flat ecosystems produced via a supervised classification of 707,528 Landsat Archive images. Each pixel was classified into tidal flat, permanent water or other with reference to a globally distributed set of training data. The ... | | [coastal](https://developers.google.com/earth-engine/datasets/tags/coastal) [google](https://developers.google.com/earth-engine/datasets/tags/google) [intertidal](https://developers.google.com/earth-engine/datasets/tags/intertidal) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [murray](https://developers.google.com/earth-engine/datasets/tags/murray) [surface-ground-water](https://developers.google.com/earth-engine/datasets/tags/surface-ground-water) | - |---| | [### SPOT Multispectral Imagery 10-20m, Brazil ![](https://developers.google.com/earth-engine/datasets/images/AIRBUS/AIRBUS_SPOT_2_4_5_BRAZIL_2007_2009_MS_V1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/AIRBUS_SPOT_2_4_5_BRAZIL_2007_2009_MS_V1) | | This collection provides 2008-era raw multispectral imagery from the SPOT 2, 4, and 5 satellites over the country of Brazil. These missions, operated by CNES, were designed to provide high-resolution, wide-area optical imagery for managing Earth's resources. SPOT 2 and 4 utilized HRV and HRVIR ... | | [brazil](https://developers.google.com/earth-engine/datasets/tags/brazil) [forest-code](https://developers.google.com/earth-engine/datasets/tags/forest-code) [google](https://developers.google.com/earth-engine/datasets/tags/google) [multispectral](https://developers.google.com/earth-engine/datasets/tags/multispectral) [satellite-imagery](https://developers.google.com/earth-engine/datasets/tags/satellite-imagery) [spot](https://developers.google.com/earth-engine/datasets/tags/spot) | - |---| | [### SPOT Multispectral Pseudo Natural Color Imagery 10-20m, Brazil ![](https://developers.google.com/earth-engine/datasets/images/AIRBUS/AIRBUS_SPOT_2_4_5_BRAZIL_2007_2009_MS_NC_V1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/AIRBUS_SPOT_2_4_5_BRAZIL_2007_2009_MS_NC_V1) | | This collection contains 2008-era "pseudo natural color" RGB images derived from the native multispectral bands of SPOT 2, 4, and 5 for Brazil. Because the HRV and HRG sensors did not include a native blue band, this product synthesizes an RGB representation to approximate a ... | | [brazil](https://developers.google.com/earth-engine/datasets/tags/brazil) [forest-code](https://developers.google.com/earth-engine/datasets/tags/forest-code) [google](https://developers.google.com/earth-engine/datasets/tags/google) [rgb](https://developers.google.com/earth-engine/datasets/tags/rgb) [satellite-imagery](https://developers.google.com/earth-engine/datasets/tags/satellite-imagery) [spot](https://developers.google.com/earth-engine/datasets/tags/spot) | - |---| | [### SPOT Panchromatic Imagery 5-10m, Brazil ![](https://developers.google.com/earth-engine/datasets/images/AIRBUS/AIRBUS_SPOT_2_4_5_BRAZIL_2007_2009_PAN_V1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/AIRBUS_SPOT_2_4_5_BRAZIL_2007_2009_PAN_V1) | | This collection contains the raw panchromatic (PAN) bands from the SPOT 2, 4, and 5 satellites for Brazil circa 2008. The panchromatic sensor provides the highest native spatial resolution of the missions, capturing light across a broad visible spectrum (0.51-0.73 µm for SPOT 2, 0.61-0.68 ... | | [brazil](https://developers.google.com/earth-engine/datasets/tags/brazil) [forest-code](https://developers.google.com/earth-engine/datasets/tags/forest-code) [google](https://developers.google.com/earth-engine/datasets/tags/google) [imagery](https://developers.google.com/earth-engine/datasets/tags/imagery) [satellite-imagery](https://developers.google.com/earth-engine/datasets/tags/satellite-imagery) [spot](https://developers.google.com/earth-engine/datasets/tags/spot) | - |---| | [### SPOT Pansharpened Pseudo Natural Color Imagery 5-10m, Brazil ![](https://developers.google.com/earth-engine/datasets/images/AIRBUS/AIRBUS_SPOT_2_4_5_BRAZIL_2007_2009_PMS_NC_V1_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/AIRBUS_SPOT_2_4_5_BRAZIL_2007_2009_PMS_NC_V1) | | This collection provides high-resolution pansharpened pseudo-natural color SPOT imagery satellites 2, 4, and 5 for Brazil circa 2008. Where a corresponding high-resolution panchromatic image was available, it was fused with multispectral data to achieve enhanced spatial detail (up to 5m for SPOT 5 or 10m ... | | [brazil](https://developers.google.com/earth-engine/datasets/tags/brazil) [forest-code](https://developers.google.com/earth-engine/datasets/tags/forest-code) [google](https://developers.google.com/earth-engine/datasets/tags/google) [rgb](https://developers.google.com/earth-engine/datasets/tags/rgb) [satellite-imagery](https://developers.google.com/earth-engine/datasets/tags/satellite-imagery) [spot](https://developers.google.com/earth-engine/datasets/tags/spot) | - |---| | [### Satellite Embedding V1 ![](https://developers.google.com/earth-engine/datasets/images/GOOGLE/GOOGLE_SATELLITE_EMBEDDING_V1_ANNUAL_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_SATELLITE_EMBEDDING_V1_ANNUAL) | | The Google Satellite Embedding dataset is a global, analysis-ready collection of learned geospatial embeddings. Each 10-meter pixel in this dataset is a 64-dimensional representation, or "embedding vector," that encodes temporal trajectories of surface conditions at and around that pixel as measured by various Earth observation ... | | [annual](https://developers.google.com/earth-engine/datasets/tags/annual) [global](https://developers.google.com/earth-engine/datasets/tags/global) [google](https://developers.google.com/earth-engine/datasets/tags/google) [landsat-derived](https://developers.google.com/earth-engine/datasets/tags/landsat-derived) [satellite-imagery](https://developers.google.com/earth-engine/datasets/tags/satellite-imagery) [sentinel1-derived](https://developers.google.com/earth-engine/datasets/tags/sentinel1-derived) | - |---| | [### WRI/Google DeepMind Global Drivers of Forest Loss 2001-2022 v1.0 ![](https://developers.google.com/earth-engine/datasets/images/landandcarbon/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_2001_2022_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_2001_2022) | | This dataset maps the dominant driver of tree cover loss from 2001-2022 globally at 1 km resolution. Produced by the World Resources Institute (WRI) and Google DeepMind, the data were developed using a global neural network model (ResNet) trained on a set of samples collected ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture) [deforestation](https://developers.google.com/earth-engine/datasets/tags/deforestation) [forest](https://developers.google.com/earth-engine/datasets/tags/forest) [forest-biomass](https://developers.google.com/earth-engine/datasets/tags/forest-biomass) [google](https://developers.google.com/earth-engine/datasets/tags/google) [landandcarbon](https://developers.google.com/earth-engine/datasets/tags/landandcarbon) | - |---| | [### WRI/Google DeepMind Global Drivers of Forest Loss 2001-2023 v1.1 ![](https://developers.google.com/earth-engine/datasets/images/landandcarbon/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_1_2001_2023_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_1_2001_2023) | | This dataset maps the dominant driver of tree cover loss from 2001-2023 globally at 1 km resolution. Produced by the World Resources Institute (WRI) and Google DeepMind, the data were developed using a global neural network model (ResNet) trained on a set of samples collected ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture) [deforestation](https://developers.google.com/earth-engine/datasets/tags/deforestation) [forest](https://developers.google.com/earth-engine/datasets/tags/forest) [forest-biomass](https://developers.google.com/earth-engine/datasets/tags/forest-biomass) [google](https://developers.google.com/earth-engine/datasets/tags/google) [landandcarbon](https://developers.google.com/earth-engine/datasets/tags/landandcarbon) | - |---| | [### WRI/Google DeepMind Global Drivers of Forest Loss 2001-2024 v1.2 ![](https://developers.google.com/earth-engine/datasets/images/landandcarbon/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_2_2001_2024_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_2_2001_2024) | | This dataset maps the dominant driver of tree cover loss from 2001-2024 globally at 1 km resolution. Produced by the World Resources Institute (WRI) and Google DeepMind, the data were developed using a global neural network model (ResNet) trained on a set of samples collected ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture) [deforestation](https://developers.google.com/earth-engine/datasets/tags/deforestation) [forest](https://developers.google.com/earth-engine/datasets/tags/forest) [forest-biomass](https://developers.google.com/earth-engine/datasets/tags/forest-biomass) [google](https://developers.google.com/earth-engine/datasets/tags/google) [landandcarbon](https://developers.google.com/earth-engine/datasets/tags/landandcarbon) | - |---| | [### WRI/Google DeepMind Global Drivers of Forest Loss 2001-2025 v1.3 ![](https://developers.google.com/earth-engine/datasets/images/landandcarbon/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_3_2001_2025_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_3_2001_2025) | | This dataset maps the dominant driver of tree cover loss from 2001-2025 globally at 1 km resolution. Produced by the World Resources Institute (WRI) and Google DeepMind, the data were developed using a global neural network model (ResNet) trained on a set of samples collected ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture) [deforestation](https://developers.google.com/earth-engine/datasets/tags/deforestation) [forest](https://developers.google.com/earth-engine/datasets/tags/forest) [forest-biomass](https://developers.google.com/earth-engine/datasets/tags/forest-biomass) [google](https://developers.google.com/earth-engine/datasets/tags/google) [landandcarbon](https://developers.google.com/earth-engine/datasets/tags/landandcarbon) |