Overview
DOI | https://doi.org/10.3334/ORNLDAAC/1719 |
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Version | 1 |
Project | |
Published | 2019-11-14 |
Usage | 240 downloads |
Description
This dataset provides annual maps of aboveground biomass (AGB, Mg/ha) for forests in Washington, Oregon, Idaho, and western Montana, USA, for the years 2000-2016, at a spatial resolution of 30 meters. Tree measurements were summarized with the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS) to estimate AGB in field plots contributed by stakeholders, then lidar was used to predict plot-level AGB using the Random Forests machine learning algorithm. The machine learning outputs were used to predict AGB from Landsat time series imagery processed through LandTrendr, climate metrics generated from 30-year climate normals, and topographic metrics generated from a 30-m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM). The non-forested pixels were masked using the PALSAR 2009 forest/nonforest mask.
Science Keywords
- BIOSPHERE
- VEGETATION
- BIOMASS
- BIOSPHERE
- VEGETATION
- CARBON
- BIOSPHERE
- ECOSYSTEMS
- TERRESTRIAL ECOSYSTEMS
- FORESTS
Data Use and Citation
This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use Policy. See our Data Use and Citation Policy for more information.
Data Files
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Companion Files
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Dataset Companion Files
Dataset has 1 companion files.
- CMS_AGB_NW_USA.pdf