Data

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).

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 – Future Projections 2050s – rcp 8.5

Western U.S. | 2050s

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Rangeland – Future Projections 2050s – rcp 4.5

Western U.S. | 2050s

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Sagebrush Mask for Future Projections

Western U.S. | 2020s, 2050s, 2080s

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NLCD 2021 Now Available

Published Jul 20, 2023

The U.S. Geological Survey (USGS), in association with the Multi-Resolution Land Characteristics (MRLC) Consortium, is pleased to announce the completion and release of the latest epoch of the National Land Cover Database (NLCD) for the conterminous U.S.—NLCD 2021. The MRLC, a consortium of federal agencies who coordinate and generate consistent and relevant land cover information at the national scale for a wide variety of environmental, land management, and modeling applications, have been providing the scientific community with detailed land cover products for more than 30 years. Over that time, NLCD has been one of the most widely used geospatial datasets in the U.S., serving as a basis for understanding the Nation’s landscapes in thousands of studies and applications, trusted by scientists, land managers, students, city planners, and many more as a definitive source of U.S. land cover.

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RCMAP 1985-2021 Fractional Component Time-Series Now Available

Published Dec 01, 2022

The U.S. Geological Survey (USGS), in collaboration with the MRLC consortium and Bureau of Land Management (BLM), is pleased to announce the availability of a new generation of Rangeland, Condition, Monitoring, Assessment, and Projection (RCMAP) fractional component data spanning a 1985-2021 time-series. The new time-series includes yearly cover predictions for 9 components: shrub, sagebrush, non-sagebrush shrub, herbaceous, annual herbaceous, perennial herbaceous, litter, bare ground, and new to this version, tree cover. Trends statistics of the new time-series will be available by Jan 2023. Data are available for download and on the rangelands viewer. The new generation of data update previously released 1985-2020 RCMAP data and are not designed to be backwards compatible (1985-2020 cover predictions are different between versions). While users are encouraged to use the newest generation of data, the previous versions of the time-series data are archived.

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Release of RCMAP Time-Series Trends Statistics

Published Aug 02, 2021

RCMAP has released temporal trends for the 1985-2020 fractional component cover time-series. Temporal patterns in each RCMAP component were evaluated with two approaches, 1) linear trends and 2) a structural change method using a temporal moving window to detect “breaks” and “stable states” in pixel values. The structural change method partitions the time-series into segments of similar slope values, with statistically significant break-points indicating perturbations to the prior trajectory. We provide the following statistics: 1) for each component, each year, the presence/absence of breaks, 2) the slope, p-value, and standard error of the segment occurring in each year, 3) the overall model R2 (quality of model fit to the temporal profile), and 4) an index, Total Change Intensity, reflecting the total amount of change occurring across components in that pixel.

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Dataset Type

Region

Time Period

RCMAP - Future Projections - 2020s, 2050s, and 2080s

Rangeland – Future Projections 2050s – rcp 8.5

Western U.S. | 2050s

Rangeland – Future Projections 2050s – rcp 4.5

Western U.S. | 2050s

Sagebrush Mask for Future Projections

Western U.S. | 2020s, 2050s, 2080s

RCMAP - Time-Series - Cover

RCMAP Shrub Cover

Western U.S. | 1985-1996

RCMAP Sagebrush Cover

Western U.S. | 1985-1996

RCMAP Litter Cover

Western U.S. | 1985-1996

RCMAP Herbaceous Cover

Western U.S. | 1985-1996

RCMAP Bare Ground Cover

Western U.S. | 1985-1996

RCMAP Perennial Herbaceous Cover

Western U.S. | 1985-1996

RCMAP Non-sagebrush Shrub Cover

Western U.S. | 1985-1996

RCMAP Annual Herbaceous Cover

Western U.S. | 1985-1996

RCMAP Tree Cover

Western U.S. | 1985-1996

NLCD 2021 Now Available

RCMAP 1985-2021 Fractional Component Time-Series Now Available

Release of RCMAP Time-Series Trends Statistics