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Conference Paper

Improved sea floor topography from sea-surface gravity gradiometry inversion

Authors

Seoane,  Lucia
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Ramillien,  Guillaume
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Rouxel,  Didier
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Darrozes,  José
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Plazolles,  Bastien
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Salaün,  Corinne
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Schmitt,  Thierry
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Seoane, L., Ramillien, G., Rouxel, D., Darrozes, J., Plazolles, B., Salaün, C., Schmitt, T. (2023): Improved sea floor topography from sea-surface gravity gradiometry inversion, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-1865


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017692
Abstract
Besides sea floor topography maps can be estimated by inversion of satellite-based gravity and/or geoid height anomalies, in particular in large oceanic provinces that are uncovered by ship tracks, it has been demonstrated that gravity gradiometry is a powerful technique to retrieve more details of regional bathymetry as gravity tensor is composed by the high frequency of the gravity field. Inversion of vertical gravity gradient data derived from the radar altimetry technique offers the possibility to reach greater resolutions (< 10 km). We propose an efficient approach based on Kalman filter to restore seafloor shape as well as lithospheric parameters, e.g. the crust and elastic thicknesses, for combining different types of geophysical information including mainly GG data. For validation, our estimated maps of bathymetry are confronted to existing data sets in areas well-covered by observation surveys.