MURAL - Maynooth University Research Archive Library



    The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery


    McCarthy, Timothy (2019) The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery. Irish Journal of Agricultural and Food Research, 58 (44). pp. 1-22. ISSN 2009-9029

    [img]
    Preview
    Download (9MB) | Preview


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    Abstract

    The capability of Sentinel 1 C-band (5 cm wavelength) synthetic aperture radio detection and ranging (RADAR) (abbreviated as SAR) for flood mapping is demonstrated, and this approach is used to map the extent of the extensive floods that occurred throughout the Republic of Ireland in the winter of 2015–2016. Thirty-three Sentinel 1 images were used to map the area and duration of floods over a 6-mo period from November 2015 to April 2016. Flood maps for 11 separate dates charted the development and persistence of floods nationally. The maximum flood extent during this period was estimated to be ~24,356 ha. The depth of rainfall influenced the magnitude of flood in the preceding 5 d and over more extended periods to a lesser degree. Reduced photosynthetic activity on farms affected by flooding was observed in Landsat 8 vegetation index difference images compared to the previous spring. The accuracy of the flood map was assessed against reports of flooding from affected farms, as well as other satellite-derived maps from Copernicus Emergency Management Service and Sentinel 2. Monte Carlo simulated elevation data (20 m resolution, 2.5 m root mean square error [RMSE]) were used to estimate the flood’s depth and volume. Although the modelled flood height showed a strong correlation with the measured river heights, differences of several metres were observed. Future mapping strategies are discussed, which include high–temporal-resolution soil moisture data, as part of an integrated multisensor approach to flood response over a range of spatial scales.

    Item Type: Article
    Keywords: Agriculture; flooding; Landsat; mitigation; remote sensing; Sentinel;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Item ID: 11396
    Identification Number: https://doi.org/10.2478/ijafr-2019-0006
    Depositing User: Tim McCarthy
    Date Deposited: 21 Oct 2019 13:01
    Journal or Publication Title: Irish Journal of Agricultural and Food Research
    Publisher: TEAGASC-Agriculture and Food Development Authority
    Refereed: Yes
    URI:

    Repository Staff Only(login required)

    View Item Item control page

    Downloads

    Downloads per month over past year