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).
Exotic Annual Grass
The Exotic Annual Grass (EAG) abundance dataset provides early season percent cover estimate of the exotic grass species in 30m spatial resolution for a mapped year in rangeland ecosystems of western United States. We plan to release these EAG estimates multiple times each year in early growing season. EAG is a continuous field consisting of abundance of non-native grass species whose life history is complete in one growing season. Cheatgrass (Bromus tectorum) is a dominant species but this dataset also includes Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus hordeaceus spp. Hordeaceus, Bromus japonicus, Bromus madritensis L., Bromus madritensis L. ssp. rubens (L.) Duvin, Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitch, and medusahead (Taeniatherum caput-medusae). A main objective of releasing these maps is to provide a tool for better monitoring EAG dynamics and informing conservation and management efforts at local to regional scales. (Read More)
NLCD tree canopy cover is a 30 m raster geospatial dataset that is available for the conterminous United States, coastal Alaska, Hawaii, and Puerto Rico. These data contain percent tree canopy estimates, as a continuous variable, for each pixel across all land covers and types and are generated by the United States Forest Service (USFS). The USFS derives tree canopy cover from multi-spectral Landsat imagery and other available ground and ancillary information. 2011 and 2016 Forest canopy products are available for the Continental United States, coastal 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)