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 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)
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)