Workflow for estimating above ground biomass from satellite imagery with non-geolocated ground validation data
Abstract
Satellite-based aboveground biomass mapping typically relies on validation data from field-based inventory plots or other high resolution ground truthing, but acquiring validation data is challenging. In the United States, the Forest Inventory and Analysis (FIA) program is a common source of field validation data for biomass mapping, but currently the US Forest Service is not processing Material Transfer Agreements (MTA) that share exact plot coordinates due to reductions in the federal workforce. We developed a workflow that circumvents this limitation, by using individual tree-level data and stand density information from the FIA database to model “hypothetical plots” of uniform canopy structure that can be downscaled to 10 m Sentinel pixels to approximate aboveground biomass given a pixel’s canopy height and vegetation class, predicted from a separate canopy and vegetation modeling workflow. This approach is readily transferable to other regions globally where precise geolocation of validation data is not available.
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BibTeX
@misc{natijohnson2026workflow,
title = {{Workflow for estimating above ground biomass from satellite imagery with non-geolocated ground validation data}},
author = {Erik Nati-Johnson and Jodi Brandt and Trevor Caughlin and Rose A Graves and Anand Roopsind},
howpublished = {EarthArXiv},
year = {2026},
month = oct,
doi = {10.31223/x5cf9q},
url = {https://eartharxiv.org/repository/view/15442/},
note = {CC BY-NC 4.0},
}
RIS
TY - UNPB
TI - Workflow for estimating above ground biomass from satellite imagery with non-geolocated ground validation data
AU - Erik Nati-Johnson
AU - Jodi Brandt
AU - Trevor Caughlin
AU - Rose A Graves
AU - Anand Roopsind
PY - 2026
DA - 2026/10/09
PB - EarthArXiv
DO - 10.31223/x5cf9q
UR - https://eartharxiv.org/repository/view/15442/
AB - Satellite-based aboveground biomass mapping typically relies on validation data from field-based inventory plots or other high resolution ground truthing, but acquiring validation data is challenging. In the United States, the Forest Inventory and Analysis (FIA) program is a common source of field validation data for biomass mapping, but currently the US Forest Service is not processing Material Transfer Agreements (MTA) that share exact plot coordinates due to reductions in the federal workforce. We developed a workflow that circumvents this limitation, by using individual tree-level data and stand density information from the FIA database to model “hypothetical plots” of uniform canopy structure that can be downscaled to 10 m Sentinel pixels to approximate aboveground biomass given a pixel’s canopy height and vegetation class, predicted from a separate canopy and vegetation modeling workflow. This approach is readily transferable to other regions globally where precise geolocation of validation data is not available.
ER -