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    • LiDAR Derived Biomass, Canopy Height, and Cover for New England Region, USA, 2015

    Metadata Updated: December 6, 2023

    This dataset provides 30 m gridded estimates of aboveground biomass density (AGBD), forest canopy height, and tree canopy coverage for the New England Region of the U.S., including the state of Maine, Vermont, New Hampshire, Massachusetts, Connecticut, and Rhode Island, for the nominal year 2015. It is based on inputs from 1 m resolution Leaf-off LiDAR data collected from 2010 through 2015, high-resolution leaf-on agricultural imagery, and FIA plot-level measurements. Canopy height and tree cover were derived directly from LiDAR data while AGBD was estimated by statistical models that link remote sensing data and FIA plots at the pixel level. Error in AGBD was calculated at the 90% confidence interval. This approach can directly contribute to the formation of a cohesive forest carbon accounting system at national and even international levels, especially via future integrations with NASA's spaceborne LiDAR missions.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

    Downloads & Resources

    Dates

    Metadata Created Date December 1, 2022
    Metadata Updated Date December 6, 2023

    Metadata Source

    Harvested from NASA Data.json

    Other Data Resources

    Graphic Preview

    30 m resolution maps of aboveground biomass density (AGBD) over the New England region in 2015. a) The mean of the posterior distribution sampled from a Markov chain Monte Carlo (MCMC) model. b) The AGBD estimate over an entire pixel adjusted by canopy cover (i.e., AGBD multiplied by canopy cover percentage). Despite similar forest carbon density values between forests and suburban areas, their total carbon stock per unit area can differ by one order of magnitude, highlighting the requirement for high-resolution mapping of both forest density and extent in a carbon accounting framework. Source: Tang et al., 2021

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date December 1, 2022
    Metadata Updated Date December 6, 2023
    Publisher ORNL_DAAC
    Maintainer
    Identifier C2345879771-ORNL_CLOUD
    Data First Published 2022-11-28
    Language en-US
    Data Last Modified 2023-06-12
    Category CMS, geospatial
    Public Access Level public
    Bureau Code 026:00
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Metadata Catalog ID https://data.nasa.gov/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Citation Tang, H., L. Ma, A.J. Lister, J. ONeil-Dunne, J. Lu, R. Lamb, R.O. Dubayah, and G.C. Hurtt. 2021. LiDAR Derived Biomass, Canopy Height, and Cover for New England Region, USA, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1854
    Graphic Preview Description 30 m resolution maps of aboveground biomass density (AGBD) over the New England region in 2015. a) The mean of the posterior distribution sampled from a Markov chain Monte Carlo (MCMC) model. b) The AGBD estimate over an entire pixel adjusted by canopy cover (i.e., AGBD multiplied by canopy cover percentage). Despite similar forest carbon density values between forests and suburban areas, their total carbon stock per unit area can differ by one order of magnitude, highlighting the requirement for high-resolution mapping of both forest density and extent in a carbon accounting framework. Source: Tang et al., 2021
    Graphic Preview File https://daac.ornl.gov/CMS/guides/AGB_CanopyHt_Cover_NewEngland_Fig1.png
    Harvest Object Id ca58bf83-077a-42e0-acc1-e708cd8785e3
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://doi.org/10.3334/ORNLDAAC/1854
    Metadata Type geospatial
    Old Spatial -74.8 39.96 -66.36 46.76
    Program Code 026:001
    Source Datajson Identifier True
    Source Hash 9806357c5e6116f9bd9ab3010b6f61bbe0b11cb52ee7dbdb483cc02783180019
    Source Schema Version 1.1
    Spatial
    Temporal 2010-01-01T00:00:00Z/2015-12-31T23:59:59Z

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