Use the interface below to filter and download available NLCD products. Click (here) for NLCD Science Research Products which offer more comprehensive delineation of shrub and grass classes and information about change disturbance. For access to dynamic MRLC viewer applications and tools, click (here).
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. (Read More)
RCMAP – Basemap (2016)
RCMAP base component products characterize the percentage of each 30-meter pixel in the Western United States covered by shrub, herbaceous, bare ground, litter, sagebrush, big sagebrush and annual herbaceous, along with estimating shrub height and sagebrush height. These products have been produced by USGS in collaboration with the Bureau of Land Management. Component products are designed to be used individually or combined to support a broad variety of applications. Please note these new Revised (071520) rangeland products will differ from the first generation of circa 2016 fractional cover maps, a more aggressive masking of tree canopy cover was applied to each rangeland component. Specifically, we have lowered the tree canopy cover threshold for exclusion from 40 to 25%. For pixels with 1-25% tree canopy cover we ensured that our primary components (shrub, herbaceous, litter, and bare ground) cover summed to 100% when added with the tree canopy. And, for the secondary components (sagebrush, big sagebrush, sagebrush height and shrub height) we reconciled to the primary component (shrub), excluding any pinyon-juniper woodlands. (Read More)
RCMAP - Future Projections - 2020s, 2050s, and 2080s
RCMAP projected cover products characterize the fractional (i.e. percentage) cover of shrub, herbaceous, bare ground, litter, sagebrush, and annual herbaceous in each 30-meter pixel in the Western United States. Projected data include three time periods (2020s, 2050s, and 2080s) and two climate scenarios (Representative Concentration Pathways [RCP] 4.5 and 8.5). Component cover were harmonized so that the sum of bare ground, shrub, herbaceous, and litter cover adds to ~100% and secondary components sagebrush and annual herbaceous cover were harmonized to their respective primary components of shrub and herbaceous cover, (so their cover could not be greater than their primary component). These products have been produced by USGS in collaboration with the Bureau of Land Management. Component products are designed to be used individually or combined to support a broad variety of applications. Data are packaged by time-period and climate scenarios (six). (Read More)
Rangeland Ecological Potential - Component Cover, Cover Departure, and Vegetation States. Ecological Potential rangeland fractional cover data products represent the potential cover given the most productive, least disturbed, portion of the 1985-2020 Landsat archive. Models used to predict Ecological Potential cover were trained on ecologically intact sites where annual herbaceous cover is low, no known disturbance or land treatment has occurred over the study period, and bare ground cover is relatively lower than expectations (Read More)