RCMAP - Future Projections - 2020s, 2050s, and 2080s | Multi-Resolution Land Characteristics (MRLC) Consortium

Preferred citation: Rigge, M., Shi, H., Postma, K. 2021. Projected change in rangeland component fractional cover across the sagebrush biome through 2085. Ecosphere. 12: e03538

Related citation: Rigge, M.B., 2022, Projections of Rangeland Fractional Component Cover Across the Sagebrush Biome for Representative Concentration Pathways (RCP) 4.5 and 8.5 Scenarios for the 2020s, 2050s, and 2080s Time-Periods (ver. 1.1, April 2022): U.S. Geological Survey data release, https://doi.org/10.5066/P9EC2094.

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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Enhanced Visualization and Analysis (EVA) Tool Now Available

Published Mar 25, 2021

The MRLC Consortium, in collaboration with NOAA and the USGS, is pleased to release version 2 of the Enhanced Visualization and Analysis (EVA) tool. This tool provides users with detailed county statistics for any two NLCD landcover dates to support quick and powerful change analyses. This tool was originally developed by NOAA and shared through the consortium with custom adaptations for NLCD.

Open EVA