Overview
DOI | https://doi.org/10.3334/ORNLDAAC/2435 |
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Version | 1 |
Project | |
Published | 2025-06-10 |
Usage | 1 download |
Description
This dataset holds estimates of forest aboveground biomass (AGB) for Maine, USA, in 2023. AGB was estimated using airborne LiDAR data from the USGS 3DEP project and a deep learning convolutional neural network (CNN) model. The airborne LiDAR datasets used in this mapping were collected in different years. The CNN model was calibrated using plot-level forest inventory data with precise location measurements and spectral indices derived from multiple remote sensing products. Stand-level biomass succession models, developed from the USDA Forest Service Forest Inventory and Analysis (FIA) data, were applied to project biomass estimates to the year 2023 with 10-m spatial resolution. The data are provided in GeoTIFF format.
Science Keywords
- BIOSPHERE
- ECOSYSTEMS
- TERRESTRIAL ECOSYSTEMS
- FORESTS
- BIOSPHERE
- VEGETATION
- BIOMASS
Data Use and Citation
This dataset is openly shared, without restriction, in accordance with the NASA Earthdata Data Use Guidance.
Data Files
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Companion Files
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Dataset Companion Files
Dataset has 1 companion files.
- Maine_Forest_Biomass_Map.pdf