Return to search results
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.
Resources
6 resources available
-
Original Metadata
ISO -
Resource 2
PNG -
Resource 3
ZIP -
Resource 4
PDF -
Resource 5
HTML -
Resource 6
BIN
Find Related Datasets
Search by Tags
Click any tag below to search for similar datasets
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "026:00" ] |
| contactPoint |
{ "fn": "Earthdata Forum", "@type": "vcard:Contact", "hasEmail": "mailto:earthdata-support@nasa.gov" } |
| 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. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "Original Metadata", "format": "ISO", "mediaType": "text/xml", "conformsTo": "http://www.isotc211.org/2005/gmi", "description": "The metadata's original source.", "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C3566308239-ORNL_CLOUD.iso19115" }, { "@type": "dcat:Distribution", "format": "PNG", "mediaType": "image/png", "downloadURL": "https://daac.ornl.gov/CMS/guides/Maine_Forest_Biomass_Map_Fig1.png" }, { "@type": "dcat:Distribution", "format": "ZIP", "mediaType": "application/zip", "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/Maine_Forest_Biomass_Map_2435.zip" }, { "@type": "dcat:Distribution", "format": "PDF", "mediaType": "application/pdf", "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/cms/Maine_Forest_Biomass_Map/comp/Maine_Forest_Biomass_Map.pdf" }, { "@type": "dcat:Distribution", "format": "HTML", "mediaType": "text/html", "downloadURL": "https://doi.org/10.3334/ORNLDAAC/2435" }, { "@type": "dcat:Distribution", "format": "BIN", "mediaType": "application/octet-stream", "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C3566308239-ORNL_CLOUD" } ] |
| identifier | 10.3334/ORNLDAAC/2435 |
| keyword |
[ "earth-science-ecosystems-biosphere-terrestrial-ecosystems", "earth-science-vegetation-biosphere-biomass" ] |
| license | https://www.usa.gov/government-works |
| modified | 2026-08-10 |
| programCode |
[ "026:000" ] |
| publisher |
{ "name": "ORNL_DAAC", "@type": "org:Organization" } |
| spatial |
"["CARTESIAN", [{"WestBoundingCoordinate": -71.3389, "NorthBoundingCoordinate": 47.461, "EastBoundingCoordinate": -66.6761, "SouthBoundingCoordinate": 42.9074}]]"
|
| temporal | 2023-01-01/2023-12-31 |
| theme |
[ "Earth Science" ] |
| title | Forest Aboveground Biomass for Maine, 2023 |
