Forest Aboveground Biomass for Maine, 2023

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.

Data and Resources

Additional Info

Field Value
Maintainer Earthdata Forum
Last Updated September 15, 2026, 03:29 (UTC)
Created June 18, 2025, 21:28 (UTC)
accessLevel public
bureauCode {026:00}
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
harvest_object_id d84db813-0ead-42d0-9e95-f05c7b83de97
harvest_source_id b99e41c6-fe79-4c19-bbc3-9b6c8111bfac
harvest_source_title Science Discovery Engine
identifier 10.3334/ORNLDAAC/2435
license https://www.usa.gov/government-works
modified 2026-09-07T22:16:02Z
programCode {026:000}
publisher ORNL_DAAC
resource-type Dataset
source_datajson_identifier true
source_hash 8d62e6cef9eefcd9f8d26c31ba8adeeb6138bc32a303ce0168c606a239f411cc
source_schema_version 1.1
spatial ["CARTESIAN", [{"WestBoundingCoordinate": -71.3389, "NorthBoundingCoordinate": 47.461, "EastBoundingCoordinate": -66.6761, "SouthBoundingCoordinate": 42.9074}]]
temporal 2023-01-01/2023-12-31
theme {"Earth Science"}