Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction

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 soun...

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Main Authors: McMillan, Malcolm, Shepherd, Andrew, Vaughan, David G., Laxon, Seymour, McAdoo, David
Format: Article in Journal/Newspaper
Language:unknown
Published: IEEE Geoscience and Remote Sensing Society 2009
Subjects:
Online Access:http://nora.nerc.ac.uk/id/eprint/17925/
https://ieeexplore.ieee.org/document/5196715
id ftnerc:oai:nora.nerc.ac.uk:17925
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spelling ftnerc:oai:nora.nerc.ac.uk:17925 2023-05-15T13:23:51+02:00 Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction McMillan, Malcolm Shepherd, Andrew Vaughan, David G. Laxon, Seymour McAdoo, David 2009 http://nora.nerc.ac.uk/id/eprint/17925/ https://ieeexplore.ieee.org/document/5196715 unknown IEEE Geoscience and Remote Sensing Society McMillan, Malcolm; Shepherd, Andrew; Vaughan, David G. orcid:0000-0002-9065-0570 Laxon, Seymour; McAdoo, David. 2009 Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction. IEEE Transactions on Geosciences & Remote Sensing, 47 (12). 4223-4228. https://doi.org/10.1109/TGRS.2009.2023665 <https://doi.org/10.1109/TGRS.2009.2023665> Marine Sciences Publication - Article PeerReviewed 2009 ftnerc 2023-02-04T19:31:25Z 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. Article in Journal/Newspaper Amundsen Sea Antarc* Antarctica West Antarctica Natural Environment Research Council: NERC Open Research Archive West Antarctica Amundsen Sea
institution Open Polar
collection Natural Environment Research Council: NERC Open Research Archive
op_collection_id ftnerc
language unknown
topic Marine Sciences
spellingShingle Marine Sciences
McMillan, Malcolm
Shepherd, Andrew
Vaughan, David G.
Laxon, Seymour
McAdoo, David
Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction
topic_facet Marine Sciences
description 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.
format Article in Journal/Newspaper
author McMillan, Malcolm
Shepherd, Andrew
Vaughan, David G.
Laxon, Seymour
McAdoo, David
author_facet McMillan, Malcolm
Shepherd, Andrew
Vaughan, David G.
Laxon, Seymour
McAdoo, David
author_sort McMillan, Malcolm
title Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction
title_short Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction
title_full Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction
title_fullStr Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction
title_full_unstemmed Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction
title_sort amundsen sea bathymetry: the benefits of using gravity data for bathymetric prediction
publisher IEEE Geoscience and Remote Sensing Society
publishDate 2009
url http://nora.nerc.ac.uk/id/eprint/17925/
https://ieeexplore.ieee.org/document/5196715
geographic West Antarctica
Amundsen Sea
geographic_facet West Antarctica
Amundsen Sea
genre Amundsen Sea
Antarc*
Antarctica
West Antarctica
genre_facet Amundsen Sea
Antarc*
Antarctica
West Antarctica
op_relation McMillan, Malcolm; Shepherd, Andrew; Vaughan, David G. orcid:0000-0002-9065-0570
Laxon, Seymour; McAdoo, David. 2009 Amundsen Sea bathymetry: The benefits of using gravity data for bathymetric prediction. IEEE Transactions on Geosciences & Remote Sensing, 47 (12). 4223-4228. https://doi.org/10.1109/TGRS.2009.2023665 <https://doi.org/10.1109/TGRS.2009.2023665>
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