Skip to main content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

USDA Logo U.S. Department of Agriculture

Publication Details

Title:
RangeMap: Landscape-scale imputation of rangeland plot vegetation cover, height, and species composition across the western United States Data publication contains GIS data
Author(s):
Zimmer, Scott N.; Reeves, Matthew C.; Riley, Karin L.; Inglis, Nicole C.
Publication Year:
2026
How to Cite:
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:
Zimmer, Scott N.; Reeves, Matthew C.; Riley, Karin L.; Inglis, Nicole C. 2026. RangeMap: Landscape-scale imputation of rangeland plot vegetation cover, height, and species composition across the western United States. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2026-0058
Abstract:
RangeMap is a novel spatial dataset that imputes field-collected plot indicators across western United States rangelands. Modeling of plot indicators such as fractional vegetation cover provides valuable data for inventory and monitoring at large spatial and temporal scales, expanding the degree of inference of discrete field plots. Existing models have provided raster predictions of several key measures of rangeland vegetation, including fractional cover of bare ground, shrubs, perennial forbs and grasses, cheatgrass, trees, and canopy gaps, each modeled separately. While it is possible to model several individual variables as such, it is impractical to individually model the dozens of plot-level attributes which could be useful for analysis, and the predictions from individual models may not be representative of a true inventory plot.

RangeMap addresses these drawbacks by instead imputing a unique plot identifier, from which any relevant field-collected plot metric can be derived. Since all resulting data are drawn from a single plot, they are internally consistent and correspond to a real plot measured in the field. We provide more than 100 plot indicators, including many categories of data which have not been addressed by prior models. Where prior models have addressed only “first-hit” cover representing top canopy vegetation, we provide both “first-hit” and “any-hit” metrics, allowing cover of understory vegetation to be addressed in a novel way. Other new metrics include heights of relevant plant functional groups, species compositions, soil stability, and fire behavior fuel models. RangeMap utilizes a random forest nearest neighbor model and incorporates 90,404 plots collected by the following programs in training and validation: 1) Bureau of Land Management Assessment, Inventory, and Monitoring (AIM); 2) Natural Resources Conservation Service Landscape Monitoring Framework (LMF); and 3) Natural Resources Conservation Service National Resources Inventory (NRI). RangeMap is run at 30-meter resolution and is produced annually throughout the western United States, with Landsat imagery and climate anomalies as the primary inputs. This data publication includes a georeferenced TIF file for each of these annual model outputs, from 2006-2025, along with the associated attribute tables providing plot-level attributes. Also included is a tabular file containing the plot-level attributes of all inventory plots utilized in modeling and validation.

Keywords:
biota; environment; Carbon; Ecology, Ecosystems, & Environment; Fire; Natural Resource Management & Use; rangelands; vegetation; carbon; fire; wildfire risk; western United States
Related publications:
  • Riley, Karin L.; Grenfell, Isaac C.; Shaw, John D.; Finney, Mark A. 2022. TreeMap 2016 dataset generates CONUS-wide maps of forest characteristics including live basal area, aboveground carbon, and number of trees per acre. Journal of Forestry. 120(6): 607-632. https://doi.org/10.1093/jofore/fvac022 https://research.fs.usda.gov/treesearch/65597
  • Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A.; Wiener, Jason M. 2021. TreeMap, a tree-level model of conterminous US forests circa 2014 produced by imputation of FIA plot data. Scientific Data. 8: 11. https://doi.org/10.1038/s41597-020-00782-x https://research.fs.usda.gov/treesearch/61840
  • Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A.; Wiener, Jason M.; Houtman, Rachel M. 2019. Fire Lab tree list: A tree-level model of the conterminous United States landscape circa 2014. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2019-0026
  • Zimmer, Scott N.; Houtman, Rachel M.; Leatherman, Lila S. T.; Shaw, John D.; Housman, Ian W.; Shrestha, Abhinav; Borja Arboleda, Maria O.; Grenfell, Isaac C.; Finney, Mark A.; Riley, Karin L. 2026. TreeMap 2023 CONUS: A tree-level model of the forests of the conterminous United States circa 2023. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2026-0038
Metrics:
Visit count : 37
Download count: 26
More details
Data Access:

Need information about Using our Formats?