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    • Digital Elevation Models for the Global Change Research Wetland, Maryland, USA, 2016

    Metadata Updated: December 6, 2023

    This dataset contains four alternative digital elevation models (DEMs) at 1 m resolution and model performance statistical metrics for the Global Change Research Wetland (GCReW) site on the Rhode River, a tributary of the Chesapeake Bay in Maryland, USA, for the year 2016. Three DEMs were created by using different strategies for correcting positive biases in Light Detection and Ranging (LiDAR)-based DEMs that are common in tidal wetlands. These included (1) applying a single average offset based on a literature review, (2) using the LiDAR Elevation Correction with NDVI (LEAN)-method, and (3) applying plant community-specific offsets using a local vegetation cover map. Existing LiDAR data at 1 m resolution collected in 2011 was the basis for these DEMs. The fourth DEM was created by using Empirical Bayesian Kriging to extrapolate between measured ground points. The elevation is provided in meters relative to the North American Vertical Datum of 1988 (NAVD 88). To calibrate the four approaches, the elevation of the entire marsh complex was surveyed at 20 m x 20 m resolution to document the distribution of elevation relative to tidal datums from a single year. Two Trimble R8 real-time kinematic (RTK) GPS receivers were used to survey 525 points over the complex from July 26, 2016, to August 15, 2016. Relative plant cover was also documented. Tidal datums were calculated from the nearby Annapolis, MD tidal gauge located 13 km from GCReW.

    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

    DEM of the Global Change Research Wetland (GCReW) site generated using the LiDAR Elevation Correction with NDVI (LEAN) method with existing LiDAR data and bias-corrected the LEAN algorithm. Source: GCReW_Elevation_2016_LEAN.tif

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date December 1, 2022
    Metadata Updated Date December 6, 2023
    Publisher ORNL_DAAC
    Maintainer
    Identifier C2408633818-ORNL_CLOUD
    Data First Published 2021-04-01
    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 Holmquist, J.R., J. Riera, J.P. Megonigal, L. Schile-beers, K.J. Buffington, and D.E. Weller. 2021. Digital Elevation Models for the Global Change Research Wetland, Maryland, USA, 2016. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1793
    Graphic Preview Description DEM of the Global Change Research Wetland (GCReW) site generated using the LiDAR Elevation Correction with NDVI (LEAN) method with existing LiDAR data and bias-corrected the LEAN algorithm. Source: GCReW_Elevation_2016_LEAN.tif
    Graphic Preview File https://daac.ornl.gov/CMS/guides/GCRW_DEM_2016_Fig1.png
    Harvest Object Id 1dff549e-5ddd-4f49-b20f-70b0ef575bbe
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://doi.org/10.3334/ORNLDAAC/1793
    Metadata Type geospatial
    Old Spatial -76.55 38.87 -76.54 38.88
    Program Code 026:001
    Source Datajson Identifier True
    Source Hash 39e28e7a0841df6c8a3876c219950376ab080e141838f5dab9eede0a61a88deb
    Source Schema Version 1.1
    Spatial
    Temporal 2016-06-22T00:00:00Z/2016-08-15T23:59:59Z

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