• DocumentCode
    1288614
  • Title

    Amundsen Sea Bathymetry: The Benefits of Using Gravity Data for Bathymetric Prediction

  • Author

    McMillan, Malcolm ; Shepherd, Andrew ; Vaughan, David G. ; Laxon, Seymour ; McAdoo, David

  • Author_Institution
    Centre for Polar Obs. & Modelling, Univ. of Edinburgh, Edinburgh, UK
  • Volume
    47
  • Issue
    12
  • fYear
    2009
  • Firstpage
    4223
  • Lastpage
    4228
  • Abstract
    Bathymetric charts are essential for modeling oceanic processes, yet, in remote areas, direct measurements of seafloor depth are often scarce. It is possible to augment sparse depth soundings with dense satellite-derived gravity data to provide additional bathymetric detail in regions devoid of sounding data. We demonstrate this method by using marine gravity derived from the European Remote Sensing (ERS-1) satellite altimeter, combined with depth soundings, to form a bathymetric prediction of the Amundsen Sea, West Antarctica. We estimate the root mean square error of depth estimates at unsurveyed locations in our solution to be ~120 m. We use a Monte Carlo method to assess the value of gravity as a bathymetric predictor in sparsely surveyed regions by comparing our solution to predictions formed from depth soundings alone. When less than ~11% of 10-km grid cells contain depth soundings, inclusion of gravity data improves the depth accuracy of the solution by up to 17%, as compared to a minimum curvature surface interpolation of the depth soundings alone. When depth data are sparse, our gravity-derived prediction reveals additional short-wavelength bathymetric features, such as troughs on the continental shelf, which are not resolved by interpolations of the depth soundings alone.
  • Keywords
    Monte Carlo methods; bathymetry; oceanographic regions; remote sensing; seafloor phenomena; underwater sound; Amundsen Sea; ERS-1 satellite altimeter; European Remote Sensing; Monte Carlo method; Southern Ocean arm; West Antarctica; bathymetric prediction; continental shelf; continental troughs; oceanic depth sounding; oceanic process model; root mean square error; satellite-derived gravity data; seafloor depth measurement; short-wavelength bathymetric feature; Altimetry; Arctic regions; gravity measurement; satellites; sea floor; terrain mapping;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2009.2023665
  • Filename
    5196715