In the present work we present the main algorithms used in the GIULIA project in which GOCE gravity data, in terms of global gravity field model, are exploited to estimate the main features of the Earth crust at a regional scale for the “Assets e Prospects” operation. In detail, once a regional area is considered, local available information in terms of main geological provinces, seismic profiles, and crustal densities and will combine these local datasets with GOCE derive gravity field to determine a crustal model consistent with all the available source of information. The inversion algorithm is based on a refinement of geological provinces by means of Bayesian classification procedure followed by a Wiener filter in the frequency domain to invert the gravitational signal.


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  1. Carlson, R. and Raskin, G.
    [1984] Density of the ocean crust. Nature, 311(5986), 555–558.
    [Google Scholar]
  2. Christensen, N. and Mooney, W.
    [1995] Seismic velocity structure and composition of the continental crust: A global view. Journal of Geophysical Research: Solid Earth, 100(B6), 9761–9788.
    [Google Scholar]
  3. Gilardoni, M., Reguzzoni, M. and Sampietro, D.
    [2016] GECO: a global gravity model by locally combining GOCE data and EGM2008. Studia Geophysica et Geodaetica, 60(2), 228–247.
    [Google Scholar]
  4. Reguzzoni, M. and Sampietro, D.
    [2015] GEMMA: An Earth crustal model based on GOCE satellite data. International Journal of Applied Earth Observation and Geoinformation, 35, 31–43.
    [Google Scholar]
  5. Sampietro, D.
    [2015] Geological units and Moho depth determination in the Western Balkans exploiting GOCE data. Geophysical Journal International, 202(2), 1054–1063.
    [Google Scholar]

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