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Proceedings Paper

Effect of prior information on Bayesian estimates of dielectric constant from remotely sensed data
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Paper Abstract

Bayesian inference has been proved to be a valuable tool in inversion processes. In this study, it is applied in two cases, both aimed at estimating dielectric constant from radar measurements. The first case is devoted to merge point measurements deriving from radiometer and scatterometer data on bare soils. The second case uses, in the inversion process, only active scatterometer data, but introduces supplementary information from the simulations of a hydrological model. In this Bayesian algorithm the key point is the evaluation of a joint probability density function based on the knowledge of data sets consisting of soil parameters measurements and the corresponding remote sensed data. It is obtained by applying the maximum likelihood procedure. As a further step, the influence of prior information about roughness is assessed within the context of the dielectric constant retrieval. At the beginning, a prior uniform distribution is assumed for all surface parameters. Subsequently, a non-uniform prior distribution, based on field measurements, is introduced in order to verify its impact on the estimates and the relative errors.

Paper Details

Date Published: 7 March 2003
PDF: 12 pages
Proc. SPIE 4883, SAR Image Analysis, Modeling, and Techniques V, (7 March 2003); doi: 10.1117/12.463064
Show Author Affiliations
Claudia Notarnicola, Univ. degli Studi di Bari (Italy)
Francesco Posa, Univ. degli Studi di Bari (Italy)

Published in SPIE Proceedings Vol. 4883:
SAR Image Analysis, Modeling, and Techniques V
Francesco Posa, Editor(s)

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