Geospatial Estimation of Forest Relative Density for Carbon Stewardship Decision Support across the Continental US

The US Forest Services (USFS) under the Forest Inventory and Analysis (FIA) program estimates resource characteristics and statistics regarding forest attributes and ecosystem processes at various strategic scales with different levels of precision and refinement. A vital forest resource attribute is tree size-density, which informs regional and national policies and project-scale management. To enhance the development and distribution of key forest tree-size density metrics, a 30 × 30 m wall to wall spatial dataset for stand density index (SDI), maximum SDI (SDI<sub>MAX</sub>) and relative density (RD), was developed using 54,925 FIA plots to produce estimates for ≈2,668,162,817 forested pixels across the continental US (CONUS) using a previously developed TREEMAP2016 raster. Summaries of SDI, SDI<sub>MAX</sub>, and RD revealed key differences between FIA plot-based and TREEMAP raster estimates, attributed to spatial resolution, methodological assumptions, and spatio-temporal misalignments. The nationally consistent medium-resolution forest size-density raster and underlying data provide important and unique opportunities for quantification of tree competition levels, ecosystem vulnerability, carbon sequestration opportunities, and stand dynamics at different spatio-temporal scales.

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Publication Details

Journal
Scientific Data
Published
2025-10-31
DOI
https://doi.org/10.1038/s41597-025-06012-6
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Geospatial Estimation of Forest Relative Density for Carbon Stewardship Decision Support across the Continental US

Aaron R. Weiskittel, Emmerson Chivhenge, Adam Daigneault, Christopher W. Woodall et al.
Scientific Data
Remote Sensing and LiDAR Applications
article

Geospatial Estimation of Forest Relative Density for Carbon Stewardship Decision Support across the Continental US

Aaron R. Weiskittel, Emmerson Chivhenge, Adam Daigneault, Christopher W. Woodall, Anthony W. D’Amato
article en

Abstract

The US Forest Services (USFS) under the Forest Inventory and Analysis (FIA) program estimates resource characteristics and statistics regarding forest attributes and ecosystem processes at various strategic scales with different levels of precision and refinement. A vital forest resource attribute is tree size-density, which informs regional and national policies and project-scale management. To enhance the development and distribution of key forest tree-size density metrics, a 30 × 30 m wall to wall spatial dataset for stand density index (SDI), maximum SDI (SDI<sub>MAX</sub>) and relative density (RD), was developed using 54,925 FIA plots to produce estimates for ≈2,668,162,817 forested pixels across the continental US (CONUS) using a previously developed TREEMAP2016 raster. Summaries of SDI, SDI<sub>MAX</sub>, and RD revealed key differences between FIA plot-based and TREEMAP raster estimates, attributed to spatial resolution, methodological assumptions, and spatio-temporal misalignments. The nationally consistent medium-resolution forest size-density raster and underlying data provide important and unique opportunities for quantification of tree competition levels, ecosystem vulnerability, carbon sequestration opportunities, and stand dynamics at different spatio-temporal scales.

Scientific DataVol. 12(1)
University of Vermont (US), US Forest Service (US), University of Maine (US)
National Science Foundation, U.S. Department of Agriculture, U.S. Forest Service, Office of Experimental Program to Stimulate Competitive Research
Openalex Percentile: Top 71%
Remote Sensing and LiDAR Applications
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