# Geospatial data layers

56 geospatial datasets ready to use beside your own project data.

## Basemaps

- **AlphaEarth Annual Satellite Embeddings**: Annual 10 m learned satellite representation shown through a fixed RGB projection. Useful for visual comparison and future derived change analysis; colors are not semantic classes. [Source](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_SATELLITE_EMBEDDING_V1_ANNUAL).
- **Harmonized Landsat Sentinel-2 True Color**: HLS true-color composite using harmonized red/green/blue channels at 30 m across Landsat and Sentinel-2 observations. [Source](https://developers.google.com/earth-engine/datasets/catalog/NASA_HLS_HLSS30_v002).
- **Landsat 8/9 False Color NIR**: False-color Landsat 8/9 composite using NIR/red/green channels to inspect vegetation structure and disturbance. [Source](https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2).
- **Landsat 8/9 False Color SWIR**: False-color Landsat 8/9 composite using SWIR1/NIR/green channels to inspect canopy moisture and disturbance. [Source](https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2).
- **Landsat 8/9**: Landsat 8 and 9 true-color surface reflectance imagery at 30 m resolution. Useful for long-running landscape context and historical comparison. [Source](https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2).
- **NAIP**: National Agriculture Imagery Program aerial imagery for the continental United States. Coverage rotates by state every 2-3 years, so the backend exposes curated supported vintages. [Source](https://naip-usdaonline.hub.arcgis.com/).
- **Sentinel-2 False Color NIR**: False-color Sentinel-2 composite using NIR/red/green channels to inspect vegetation structure and disturbance. [Source](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED).
- **Sentinel-2 False Color SWIR**: False-color Sentinel-2 composite using SWIR1/NIR/green channels to inspect canopy moisture and disturbance. [Source](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED).
- **Sentinel-2**: Sentinel-2 true-color surface reflectance mosaic at 10 m resolution. Best for recent visual checks when NAIP is too old or unavailable. [Source](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED).

## Forest & Carbon

- **Tree Cover Loss (10 Years)**: Landsat-derived pixels where tree-cover loss was detected, summarized over the configured ten-year window to show recent forest disturbance. [Source](https://developers.google.com/earth-engine/datasets/catalog/UMD_hansen_global_forest_change_2024_v1_12).
- **Non-Forest Areas (PALSAR)**: Global 25 m radar-based classification of dense forest, non-dense forest, non-forest, and water from ALOS PALSAR imagery. [Source](https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_FNF4).
- **USDA Landscape Change Monitoring**: Annual USDA Forest Service maps of landscape change, land cover, and land use, derived consistently from the Landsat time series. [Source](https://docs.cecil.earth/datasets/446d2f29-0d7a-48a3-8407-e84d43df909b).
- **NAIP Tree Cover (2014)**: Tree-canopy cover percentage derived from high-resolution aerial imagery, providing a 2014 baseline for vegetation cover in the United States. [Source](https://www.mrlc.gov/data/nlcd-2016-usfs-tree-canopy-cover-conus).
- **Meta/WRI Global Canopy Height v2**: Estimated top-of-canopy height from 2017–2020 imagery at about 1.2 m resolution for canopy structure and forest screening. [Source](https://www.wri.org/data/global-canopy-height-maps).
- **Nature Trace Forest Typology 2020**: Global 10 m 2020 forest typology shown as the most likely class: primary, naturally regenerating, planted, plantation, tree crops and agroforestry, or other land. [Source](https://developers.google.com/earth-engine/datasets/catalog/projects_nature-trace_assets_forest_typology_forest_typology_2020_v1_0_collection).
- **LANDFIRE Vegetation Cover**: Existing Vegetation Cover: percent live canopy cover by life form within each 30 m LANDFIRE cell. [Source](https://landfire.gov/vegetation/evc).
- **LANDFIRE Vegetation Height**: Existing Vegetation Height: height classes for the dominant tree, shrub, and herbaceous vegetation within each 30 m LANDFIRE cell. [Source](https://landfire.gov/vegetation/evh).
- **LANDFIRE Vegetation Type**: Existing Vegetation Type: mapped plant communities and land-cover types based on LANDFIRE’s ecological vegetation classification. [Source](https://landfire.gov/vegetation/evt).
- **Drivers of Forest Loss (WRI / Google DeepMind)**: Dominant cause of tree cover loss in each 1 km cell, 2001-2025, such as agriculture, logging or wildfire. Context for loss nearby; too coarse to attribute loss inside one small site. [Source](https://developers.google.com/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_3_2001_2025).
- **Above-Ground Biomass (ESA CCI v6)**: Above-ground woody biomass (Mg/ha) at ~100 m for 2007, 2010 and 2015-2022. An independent cross-check, not a stock estimate; per-pixel uncertainty is large. [Source](https://developers.google.com/earth-engine/datasets/catalog/ESA_CCI_Above_Ground_Biomass_V6_0).
- **Forest Loss Due to Fire**: Annual 30 m forest loss attributed to fire. Use it to distinguish fire disturbance from other tree-cover loss and to screen restoration permanence risk. [Source](https://glad.umd.edu/dataset/Fire_GFL/).
- **Harmonized Landsat Sentinel-2 NDVI**: Normalized Difference Vegetation Index, a harmonized vegetation greenness proxy across Landsat and Sentinel-2 observations. [Source](https://developers.google.com/earth-engine/datasets/catalog/NASA_HLS_HLSS30_v002).
- **Disturbance Alerts**: Near-real-time vegetation loss alerts from four satellite systems. Covers all vegetation, including young plantings; planned clearing and harvest also alert. [Source](https://globalnaturewatch.org/blog/data-and-tools/integrated-deforestation-alerts/).
- **JRC Global Forest Cover 2020**: Global 2020 forest/non-forest baseline aligned with the EUDR forest definition. Useful for restoration eligibility and forest-presence context; not a change-detection layer. [Source](https://docs.cecil.earth/datasets/9cfbe1d5-040d-4c13-8151-87ebdce8e0c2).
- **JRC Global Forest Type 2020**: Global 2020 forest-type baseline distinguishing naturally regenerating, primary, and planted forests. Useful for forest-restoration context and EUDR-oriented degradation screening. [Source](https://docs.cecil.earth/datasets/c17fcd5f-02bc-42e4-b069-779b17d2655a).
- **JRC Tropical Moist Forest Annual Changes**: Annual 30 m tropical moist forest classes, 1990–2025: undisturbed forest, degradation, deforestation, regrowth, water, and other areas. Exact-year JRC Tropical Moist Forest data. [Source](https://forobs.jrc.ec.europa.eu/TMF/resources/tutorial/gee).
- **Carbon Offset Project Boundaries (Africa)**: Boundaries of 72 nature-based carbon offset projects in Africa, with accounting areas and reference regions where published. Use it to check overlap with existing crediting projects. [Source](https://zenodo.org/records/11459391).
- **Landsat 8/9 NBR**: Normalized Burn Ratio, a vegetation disturbance signal from Landsat 8/9 surface reflectance; not a standalone burned-area classification. [Source](https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2).
- **Landsat 8/9 NDVI**: Normalized Difference Vegetation Index, a vegetation greenness proxy from Landsat 8/9 surface reflectance. [Source](https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2).
- **Fire History (MODIS Burned Area)**: Years each ~21 ha MODIS pixel burned, 2001-2025, to screen fire regime and permanence risk. Small or patchy early-dry-season burns are often missed. [Source](https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD64A1).
- **Sentinel-2 EVI**: Enhanced Vegetation Index, a canopy greenness proxy with blue-band correction from Sentinel-2 surface reflectance. [Source](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED).
- **Sentinel-2 NBR**: Normalized Burn Ratio, a vegetation disturbance signal from Sentinel-2 surface reflectance; not a standalone burned-area classification. [Source](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED).
- **Sentinel-2 NDVI**: Normalized Difference Vegetation Index, a vegetation greenness proxy from Sentinel-2 surface reflectance. [Source](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED).
- **WRI SBTN Natural Lands 2020**: Global 2020 baseline of natural and non-natural land. Useful for restoration eligibility and conversion-risk screening; it is not a current annual surface. [Source](https://docs.cecil.earth/datasets/bf249342-557a-4028-922c-c67fc4ad6a64).

## Water & Climate

- **Precipitation**: Median CHIRPS pentad rainfall over the configured five-year window, combining satellite rainfall estimates with station observations. [Source](https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD).
- **Rivers & Streams**: Rivers, streams, and canals from the Mapbox Streets waterway layer, showing the drainage network around a site. [Source](https://docs.mapbox.com/data/tilesets/reference/mapbox-streets-v8/).
- **Landsat 8/9 NDWI**: McFeeters Normalized Difference Water Index, a surface-water signal from Landsat 8/9 surface reflectance; not a categorical water delineation. [Source](https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2).
- **Sentinel-2 NDMI**: Normalized Difference Moisture Index, a canopy moisture proxy from Sentinel-2 surface reflectance. [Source](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED).
- **Sentinel-2 NDWI**: McFeeters Normalized Difference Water Index, a surface-water signal from Sentinel-2 surface reflectance; not a categorical water delineation. [Source](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED).

## Land Cover

- **Dynamic World - LULC**: Near-real-time 10 m land-cover labels from Sentinel-2 imagery, distinguishing water, trees, grass, crops, built area, bare ground, and other classes. [Source](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_DYNAMICWORLD_V1).
- **ESA WorldCover**: ESA’s 2021 global 10 m land-cover map, classifying tree cover, shrubland, grassland, cropland, built-up areas, wetlands, water, and other surfaces. [Source](https://developers.google.com/earth-engine/datasets/catalog/ESA_WorldCover_v200).
- **ESRI Land Cover**: Annual global 10 m land-cover classes derived from Sentinel-2 imagery, including water, trees, crops, built area, bare ground, and rangeland. [Source](https://docs.cecil.earth/datasets/a4bb9aea-b6df-4d19-9083-38357f8fa76c).
- **USGS NLCD Land Cover**: USGS annual 30 m land-cover classes for the United States, including forest, shrubland, grassland, cropland, wetlands, water, and developed areas. [Source](https://docs.cecil.earth/datasets/2ce9cb24-dba0-4f5e-89e1-d8fa5f5db7dc).
- **Fields of The World (Global)**: Global agricultural field predictions from Fields of The World. Useful as cropland and field-structure context for restoration screening. [Source](https://source.coop/ftw/global-data).
- **MapBiomas Brazil**: Annual 30 m land cover and land use for Brazil, 1985–2025. Collection 11, coverage v3; official regional classes and colours. [Source](https://brasil.mapbiomas.org/iniciativas-e-produtos/cobertura-e-uso-da-terra/cobertura-30m/cobertura/).
- **MapBiomas Chaco**: Annual 30 m land cover and land use for Gran Chaco (Argentina, Bolivia and Paraguay), 1985–2023. Collection 5, integration v2; official regional classes and colours. [Source](https://chaco.mapbiomas.org/en/collection-maps/).
- **USDA Cropland Data Layer 30 m**: Annual crop-specific land cover for the conterminous United States. Useful for historical crop and land-use screening; it is not a global restoration baseline. [Source](https://docs.cecil.earth/datasets/86bb24b3-c6c8-4a6c-8641-ae899852e3e3).

## Terrain

- **Global Slope**: Terrain steepness in degrees derived from NASADEM elevation, highlighting gentle, moderate, and steep ground worldwide. [Source](https://developers.google.com/earth-engine/datasets/catalog/NASA_NASADEM_HGT_001).
- **Slope - USGS 3DEP**: Terrain steepness in degrees derived from the USGS 3DEP elevation model, providing finer topographic detail across the United States. [Source](https://developers.google.com/earth-engine/datasets/catalog/USGS_3DEP_10m_collection).
- **Contour Lines**: Elevation contour lines from Mapbox Terrain, joining points of equal elevation in meters with intervals that become finer as the map zooms in. [Source](https://docs.mapbox.com/data/tilesets/reference/mapbox-terrain-v2/).
- **Relief**: Global elevation relief from Mapterhorn's approximately 30 m baseline. Colours adapt to the visible terrain while fixed hillshade adds shape. [Source](https://mapterhorn.com/attribution/).

## Infrastructure

- **Mapbox - Roads**: Road lines from Mapbox Streets, including highways and local streets, for understanding access and regional connectivity. [Source](https://docs.mapbox.com/data/tilesets/reference/mapbox-streets-v8/).
- **Mapbox - Settlements**: Named populated places from Mapbox Streets, showing cities, towns, villages, and smaller settlements near a site. [Source](https://docs.mapbox.com/data/tilesets/reference/mapbox-streets-v8/).

## Biodiversity

- **Birdlife Key Biodiversity Areas**: BirdLife Important Bird and Biodiversity Areas and related Key Biodiversity Areas: sites identified by standardized criteria as globally important for birds and other biodiversity. [Source](https://www.birdlife.org/focus-areas/sites/).
- **WDPA Protected Areas**: Protected Planet’s global inventory of terrestrial and marine protected-area boundaries reported by governments and other authoritative data providers. [Source](https://www.protectedplanet.net/en/thematic-areas/wdpa).
- **WWF Ecoregions**: World Wildlife Fund terrestrial ecoregions with names, boundaries, and 14 biome colors. Generalized regional ecological context for restoration planning; not current land cover or parcel boundaries. [Source](https://data-gis.unep-wcmc.org/server/rest/services/Hosted/Terrestrial_Ecoregions_of_the_World/FeatureServer).

## Put these layers to work.

Build the processing and analysis workflows your team needs. [Explore geospatial workflows](https://restorationscope.com/platform/geospatial).