The identification of the most valuable radar observation parameters (e.g., frequency, polarisation, incidence angle) is important both for designing nonredundant
high-performance sensors (i.e. selection of frequency bands and polarisations) and for specifying mission operation requirements (i.e. temporal sampling, incidence angle). Moreover, the task of classifying multiparameter SAR images may require to adopt a strategy that implies the selection of a number of features among those available fromthis kind of sensors. In this paper we have performed this kind of analysis in a specific area of interest to account for the particular conditions in which remotely sensed data are going to be used. The paper summarises the results of the analysis of the radar data acquired during the MAC Europe ’91 and X-SAR/SIR-C campaigns over the Montespertoli test site in Italy. The analysis is based mainly on a statistical approach aiming at demonstrating what is the
contribution of different measurements performed by the polarimetric SAR for discriminating the surface coverage. The work is intended to furnish a guideline to develop an optimal strategy for acquiring and processing polarimetric data to be used for land classification
