National Land Cover Database (NLCD)

The National Land Cover Database (NLCD) is a reliable and comprehensive source of land cover information for the United States. Developed by the U.S. Geological Survey (USGS), it offers detailed and consistent data on land cover types across the nation. For more information visit National Land Cover Database.

Tree Canopy

NLCD tree canopy cover is a 30 m raster geospatial dataset that is available for the conterminous United States. They are generated by the USDA Forest Service. These data contain percent tree canopy estimates, as a continuous variable, for each pixel across all land covers and types. Tree canopy cover is derived from multi-spectral satellite imagery and other available ground and ancillary information. 2011 through 2021 Forest canopy products are available for the conterminous United States, and will be available for coastal Alaska, Hawaii, Puerto Rico, and American Virgin Islands in the summer of 2023.

Land Cover

The National Land Cover Database (NLCD) provides nationwide data on land cover and land cover change at a 30m resolution with a 16-class legend based on a modified Anderson Level II classification system. NLCD 2019 represents the latest evolution of NLCD land cover products focused on providing innovative land cover and land cover change data for the Nation. NLCD 2019 offers 8 integrated epochs of land cover for years 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019. Developed classes in these years are directly derived from percent developed impervious surface and include a descriptor label that identifies the type of each impervious surface pixel. The NLCD Land Cover change index combines information from all years of land cover change and provides a simple and comprehensive way to visualize change from all 8 dates of land cover in a single layer. The change index was designed to assist NLCD users to understand complex land cover change with a single product. NLCD 2019 does not yet contain updated products for Alaska, Hawaii and Puerto Rico.

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Rangeland Analysis Platform (RAP)

Combines satellite imagery with thousands of on-the-ground vegetation measurements collected by BLM, NPS, and NRCS. For more information visit the Rangeland Analysis Platform. All raw data are available here.

Rangeland Cover

These data represent rangeland cover estimates determined by Jones et al. (2018) and as accessible on the Rangeland Analysis Platform (https://rangelands.app). Values are percent aerial cover of the following rangeland functional groups:

• Band 1 - annual forbs and grasses
• Band 2 - bare ground
• Band 3 - litter
• Band 4 - perennial forbs and grasses
• Band 5 - shrubs
• No Data value = 255
• No Data value = 255

Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Cover estimates may not be suitable in other ecosystems, e.g., forests, agricultural lands.

Rangeland Biomass

These data represent estimates of annual aboveground biomass (lbs/acre) partitioned into the following plant functional types:

• Band 1 - annual forb and grass
• Band 2 - perennial forb and grass
• No Data value = 65535

Estimates represent annually accumulated new biomass throughout the year. Estimates do not account for biomass accumulation in previous years. Biomass was calculated by separating partitioned net primary production (Robinson et al. 2019; Allred et al. 2020) to aboveground and converting carbon to biomass (Jones et al. 2020). Estimates are provided in United States customary units (lbs/acre) to facilitate use. Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Biomass estimates may not be suitable in other ecosystems, e.g., forests. Estimates in agricultural lands are not to be used. No masking was performed and is therefore the responsibility of the user.

Cropland Data Layer (CDL)

The USDA NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2022 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from Landsat 8 and 9 OLI/TIRS, ISRO ResourceSat-2 LISS-3, and ESA SENTINEL-2A and -2B collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED) and the imperviousness data layer from the USGS National Land Cover Database 2019 (NLCD 2019) and the tree canopy data layer from the NLCD 2016. For more information on metadata visit Cropland Data Layer.