MURAL - Maynooth University Research Archive Library



    Dual-scale validation of a medium-resolution coastal DEM with terrestrial LiDAR DSM and GPS


    Coveney, Seamus and Fotheringham, Stewart and Charlton, Martin and McCarthy, Tim (2010) Dual-scale validation of a medium-resolution coastal DEM with terrestrial LiDAR DSM and GPS. Computers and Geosciences, 36 (4). pp. 489-499. ISSN 0098-3004

    [img]
    Preview
    Download (4MB) | Preview


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    Abstract

    The use of medium-resolution photogrammetric-derived Digital Elevation Models (DEMs) to model coastal inundation risk is commonplace in the geosciences. However, these datasets are often characterised by relatively large and loosely defined elevation errors, which can seriously limit their reliability. Post-processed and static RTK dual-frequency GPS data and very high-resolution Terrestrial Laser Scanning DSM data are used here to quantify the magnitude and spatial distribution of elevation error on a 10 km coastal section of a medium-resolution photogrammetric DEM. The validation data are captured at two scales and spatial-resolutions to minimise the risk of spatial bias in the validation results. The strengths and shortcomings of each validation dataset are assessed, and the complimentary value of GPS and Terrestrial Laser Scanning for external validation is demonstrated. Elevation errors highlighted in the photogrammetric DEM are found to be significantly larger than suggested by the data suppliers, with a tendency for the larger errors to occur with increasing proximity to the coastline. The results confirm the unsuitability of the DEM tested for the local spatial modelling of coastal inundation risk, highlighting difficulties that may be prone to occur when similar DEM datasets are used in coastal studies elsewhere.

    Item Type: Article
    Keywords: DEM error; Terrestrial LiDAR DSM; GPS; Coastal flooding;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Item ID: 5762
    Identification Number: https://doi.org/10.1016/j.cageo.2009.10.003
    Depositing User: Martin Charlton
    Date Deposited: 03 Feb 2015 12:09
    Journal or Publication Title: Computers and Geosciences
    Publisher: Elsevier
    Refereed: Yes
    URI:

    Repository Staff Only(login required)

    View Item Item control page

    Downloads

    Downloads per month over past year