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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
5 resources available
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Data Information (PNG)
PNG -
Data Information (ZIP)
ZIP -
Data Information (PDF)
PDF -
Data Information (HTML)
HTML -
Data Information (Unknown Format)
BIN
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": "Data Information (PNG)",
"format": "PNG",
"mediaType": "image/png",
"downloadURL": "https://daac.ornl.gov/CMS/guides/Maine_Forest_Biomass_Map_Fig1.png"
},
{
"@type": "dcat:Distribution",
"title": "Data Information (ZIP)",
"format": "ZIP",
"mediaType": "application/zip",
"downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/Maine_Forest_Biomass_Map_2435.zip"
},
{
"@type": "dcat:Distribution",
"title": "Data Information (PDF)",
"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",
"title": "Data Information (HTML)",
"format": "HTML",
"mediaType": "text/html",
"downloadURL": "https://doi.org/10.3334/ORNLDAAC/2435"
},
{
"@type": "dcat:Distribution",
"title": "Data Information (Unknown Format)",
"format": "BIN",
"mediaType": "application/octet-stream",
"downloadURL": "https://search.earthdata.nasa.gov/search?q=Maine_Forest_Biomass_Map_2435&ac=true"
}
]
|
| identifier | 10.3334/ORNLDAAC/2435 |
| keyword |
[
"earth-science-ecosystems-biosphere-terrestrial-ecosystems-forests",
"earth-science-vegetation-biosphere-biomass"
]
|
| landingPage | https://search.earthdata.nasa.gov/search?q=Maine_Forest_Biomass_Map_2435&ac=true |
| modified | 2026-02-17 |
| programCode |
[
"026:000"
]
|
| publisher |
{
"name": "ORNL_DAAC",
"@type": "org:Organization"
}
|
| spatial |
"[[{"WestBoundingCoordinate":-71.3389,"NorthBoundingCoordinate":47.461,"EastBoundingCoordinate":-66.6761,"SouthBoundingCoordinate":42.9074}],"CARTESIAN"]"
|
| temporal | 2023-01-01/2023-01-01 |
| theme |
[
"Earth Science"
]
|
| title | Forest Aboveground Biomass for Maine, 2023 |
