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A Bayesian approach to invert GOCE gravity gradient

Mrs Gwendoline Pajot(1), Mr Michel Diament(1) , Mrs Marie-Francoise Lequentrec-Lalancette(2) , and Dr Christel Tiberi(3)

(1) Institut de Physique du Globe de Paris, 4 Pl. Jussieu, 75252 Paris Cedex 5, France
(2) EPSHOM, BP 31316, 29603 Brest CEDEX, France
(3) Universite Pierre et Marie Curie - Paris 6, Tour 26-16 1er etage - Case 129, 4, Place Jussieu, 75252 Paris Cedex 05, France

Abstract

The measurements made by the gradiometer on board in the GOCE satellite are gravity gradients in three directions of space. The main goal of these data is to compute the Earth gravity field at global scale with improved accuracy and a spatial resolution . However, it is quite clear gradiometric data themselves might help to infer the inner structure of the Earth. The vertical gravity gradient has actually been successfully used to improve the inversion of gravity data for density, and the full gradiometric tensor is now measured in the oil and gas prospection for the imaging of subsurface structures, when seismic methods are not suitable. For those reasons, we propose to build an inversion method for gradiometric data, dedicated to geodynamical studies both at global and regional scales, since those scales of study are indeed allowed by GOCE data spatial distribution. We choose to use a bayesian approach, which is seldom applied in the field of gravity inversion, even though often mentionned. This type of approach is less consuming for heavy computations and then should allow us to deal more easily with a great among of data. We discuss here on the contribution of the FTG (Full Tensor Gradiometry) data.

 

Full paper

Workshop poster

Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry

GOCE04