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).
NLCD imperviousness products represent urban impervious surfaces as a percentage of developed surface over every 30-meter pixel in the United States. NLCD 2019 updates all previously released versions of impervious products for CONUS and provides integrated analysis for all Land Cover dates. It also includes a matching impervious surface descriptor layer. This descriptor layer identifies types of roads, wind tower sites, building locations, and energy production sites to allow a deeper analysis of developed features. No new imperviousness products for Alaska, Hawaii and Puerto Rico are available from NLCD 2019. (Read More)
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 Fisch. & C.A. Mey. Bromus catharticus Vahl, Bromus commutatus Schrad, Bromus diandrus Roth, Bromus hordeaceus L., Bromus hordeaceus spp. Hordeaceus, Bromus japonicus Thunb, Bromus madritensis L., Bromus madritensis L. ssp. rubens (L.) Duvin, Bromus racemosus L., Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc, and medusahead (Taeniatherum caput-medusae (L.) Nevski). 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)
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). Please note that some suspect increases in sagebrush cover are projected in the Southern Great Basin and Southern Colorado Plateau, which we interpret as model error. We have developed a mask (see below) to apply to the future sagebrush cover layers. Masked areas meet three criteria: 1) they are within the sagebrush biome (Jeffries and Finn 2019), 2) within the following EPA level 3 ecoregions: Arizona/New Mexico Mountains, Arizona/New Mexico Plateau (excluding the San Luis Valley from the mask), Colorado Plateaus (excluding the Uinta Basin from the mask), Mojave Basin and Range, and Sonoran Basin and Range, and 3) have a maximum of 0% sagebrush cover observed over the 1985-2020 RCMAP time-series. (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)