Share Email Print
cover

Proceedings Paper

Multisensor analysis of Titan surface: SAR and radiometric data synergy for estimating wind speed and liquid optical thickness of hydrocarbon lakes
Author(s): B. Ventura; C. Notarnicola; D. Casarano; F. Posa; M. Janssen
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this work, scattering models and a Bayesian inversion algorithm are applied to Cassini SAR and radiometric data in order to characterize lake and land surfaces. Radar backscattering from lakes is described in terms of a double layer model, Bragg or facets scattering for the upper liquid layer and I.E.M model for the lower solid surface. This electromagnetic analysis is the starting point for the statistical inversion algorithm, to determine limits on the parameters values. Radiometer data are described with a forward radiative transfer model thus accounting for the presence of multiple layer emission and volume effects. A combined sensitivity study is performed on backscattering and brightness temperature models to define the best approach for the synergic use of active and passive data in the Bayesian algorithm. The use of e.m. scattering models allows evaluating the compatibility of the observed RCS with the expected scenarios in terms of dielectric constant of the surface constituents. A good correlation is found between the radar and the radiometric data. Brightness temperature modeling combined with SAR Bayesian inversion can improve parameter retrieval.

Paper Details

Date Published: 29 September 2009
PDF: 10 pages
Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 74771T (29 September 2009); doi: 10.1117/12.834973
Show Author Affiliations
B. Ventura, Univ. degli Studi di Bari (Italy)
C. Notarnicola, Univ. degli Studi di Bari (Italy)
EURAC research (Italy)
D. Casarano, CNR-IRPI (Italy)
F. Posa, Univ. degli Studi di Bari (Italy)
Politecnico di Bari (Italy)
M. Janssen, Jet Propulsion Lab. (United States)


Published in SPIE Proceedings Vol. 7477:
Image and Signal Processing for Remote Sensing XV
Lorenzo Bruzzone; Claudia Notarnicola; Francesco Posa, Editor(s)

© SPIE. Terms of Use
Back to Top