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Forest Aboveground Biomass for Maine, 2023

Overview

DOIhttps://doi.org/10.3334/ORNLDAAC/2435
Version1
Project
Published2025-06-10
Usage1 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

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DOI citation formatter
Ayrey, E., D.J. Hayes, X. Wei, G. Shao, A. Weiskittel, S. Fei, J. Zhao, and B. Zhang. 2025. Forest Aboveground Biomass for Maine, 2023. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2435

This dataset is openly shared, without restriction, in accordance with the NASA Earthdata Data Use Guidance.

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Companion Files

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Dataset has 1 companion files.

  • Maine_Forest_Biomass_Map.pdf