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Publication Details

Title:
FuelMap 2020 and 2022: Imputed map of carbon stored in litter, duff, fine woody debris, and coarse woody debris for CONUS forests circa 2020 and 2022 Data publication contains GIS data
Author(s):
Zimmer, Scott N.; Riley, Karin L.; Grenfell, Isaac C.; Shaw, John D.
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.; Riley, Karin L.; Grenfell, Isaac C.; Shaw, John D. 2026. FuelMap 2020 and 2022: Imputed map of carbon stored in litter, duff, fine woody debris, and coarse woody debris for CONUS forests circa 2020 and 2022. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2026-0016
Abstract:
FuelMap 2020 and 2022 are imputed maps of litter, duff, fine woody debris, and coarse woody debris loadings for the forests of the conterminous United States (CONUS) circa 2020 and 2022. In fire science, these strata are often referred to as “fuel” for wildland fire. FuelMap 2020 and 2022 are largely derived from TreeMap 2020 and 2022, which provide a tree-level model of CONUS forests. To create TreeMap, we assigned forest plot data measured by USDA Forest Service’s Forest Inventory and Analysis (FIA) program to a 30x30 meter (m) grid. Specifically, we used a random forests machine-learning algorithm to impute the most similar forest plots to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE: https://landfire.gov) and Daymet (https://daymet.ornl.gov/). Predictor variables for both the forest plots (reference data) and rasters (target data) consisted of percent forest cover, forest height, and vegetation type, as well as topography (slope, elevation, and aspect), location (latitude and longitude), 30-year biophysical variable normals from 1981-2010 (precipitation, maximum temperature, minimum temperature, snow water equivalent, shortwave radiation, vapor pressure, and vapor pressure deficit), and disturbance history (time since disturbance and disturbance type) for the landscape circa 2020 and 2022.

FIA records downed woody material (DWM) in litter, duff, fine and coarse woody debris pools at some but not all of their forest plots. Thus, many of the FIA plots imputed (assigned) in TreeMap have DWM measurements attached to them. For pixels in TreeMap where the assigned FIA plot recorded DWM, we used the FIA plot assigned in TreeMap 2020 and 2022 in FuelMap 2020 and 2022. For pixels where FIA plots were assigned that did not have DWM measured, we ran a secondary imputation which included only FIA plots where DWM was measured to identify the most similar plot with DWM measured, and then we assigned that identified plot in the FuelMap 2020 and 2022.

The main outputs of this project are rasters at 30x30 m spatial resolution of the imputed FIA plot identifier. The plot identifier corresponds to a unique visit to a plot by an FIA field crew, and is also referred to as the plot control number (CN). Using the CN, we look up the loading in each of the carbon pools (in pounds per acre) in the DWM_COND_CALC table of the FIA DataMart and include a raster for each of the following measurements: 1) litter, 2) duff, 3) fine woody debris in the 1-hour (hr) size class (size less than 0.25 inches in diameter), 4) fine woody debris in the 10-hr size class (size from 0.25-1 inch in diameter), 5) fine woody debris in the 100-hr size class (size from 1-3 inches in diameter), 6) coarse woody debris in the 1000-hr size class (size greater than 3 inches in diameter), and 7) “total carbon” in the DWM strata produced by adding these six strata together. We present these data in GeoTIFF formats. The spatial extent is CONUS for landscape conditions circa 2020 and 2022. The carbon loadings for DWM are drawn from the FIA COND_DWM_CALC tables for the assigned plot CN for litter, duff, fine woody debris and coarse woody debris.

Keywords:
biota; environment; Climate change; Carbon; Ecology, Ecosystems, & Environment; Inventory, Monitoring, & Analysis; Natural Resource Management & Use; Conservation; Ecosystem services; Forest management; Wilderness; Forest Inventory and Analysis; imputation; LANDFIRE; random forests; fuel data; conterminous United States; CONUS
Related publications:
  • Houtman, Rachel M.; Leatherman, Lila S. T.; Zimmer, Scott N.; Housman, Ian W.; Shrestha, Abhinav; Shaw, John D.; Riley, Karin L. 2025. TreeMap 2022 CONUS: A tree-level model of the forests of the conterminous United States circa 2022. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2025-0032
  • Riley, Karin L.; Grenfell, Isaac C.; 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. 2022: 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.; Shaw, John D. 2021. TreeMap 2016: A tree-level model of the forests of the conterminous United States circa 2016. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2021-0074
  • More (8 total)
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Download count: 31
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