IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v4y2019i1p46-d217244.html
   My bibliography  Save this article

Removal of Positive Elevation Bias of Digital Elevation Models for Sea-Level Rise Planning

Author

Listed:
  • Elizabeth Burke Watson

    (Department of Biodiversity, Earth & Environmental Sciences and the Academy of Natural Sciences, Drexel University, Philadelphia, PA 19103, USA)

  • LeeAnn Haaf

    (Partnership for the Delaware Estuary, Wilmington, DE 19801, USA)

  • Kirk Raper

    (Academy of Natural Sciences, Drexel University, Philadelphia, PA 19103, USA)

  • Erin Reilly

    (The Barnegat Bay Partnership, Toms River, NJ 08754, USA
    University of Maryland Center for Environmental Science, MD 20688, USA)

Abstract

Digital elevation models (DEMs) based on LiDAR surveys provide critical information for predicting the vulnerability of coastal areas to sea-level rises. Due to the poor penetration of LiDAR pulses in marsh vegetation, bare-earth DEMs for coastal wetlands are often subject to positive elevation bias, and thus underestimate vulnerability. This data publication includes comprehensive elevation surveys from seven coastal wetlands in coastal New Jersey, and an evaluation of the accuracy and positive elevation bias of each publically available DEM. Resampling the DEMs at a coarser resolution, replacing cell values using the minimum value in a wider search window (4 m), removed this positive elevation bias with no loss of accuracy.

Suggested Citation

  • Elizabeth Burke Watson & LeeAnn Haaf & Kirk Raper & Erin Reilly, 2019. "Removal of Positive Elevation Bias of Digital Elevation Models for Sea-Level Rise Planning," Data, MDPI, vol. 4(1), pages 1-6, March.
    • Handle: RePEc:gam:jdataj:v:4:y:2019:i:1:p:46-:d:217244
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/4/1/46/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/4/1/46/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:4:y:2019:i:1:p:46-:d:217244. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.