In this work, the outcomes of a research activity, that lasted approximately seven years (2003–2010), in which soil moisture was monitored on a test site in Northern Italy by collecting a series of SAR images and in situ data are presented. Radar data were provided by the C-band ENVISAT/ASAR instrument. The research activity aimed at calibrating and validating a pre-operational algorithm, conceived to be used by the Italian Civil Protection, for high resolution soil moisture mapping from SAR data. The algorithm is focused on the Bayesian theory of parameter estimation. The Maximum A Posteriori (MAP) probability criterion or the Minimum Variance one are used to retrieve soil moisture by inverting a forward scattering model. Ancillary data such as optical images and land cover data are also used. The results of the validation activity have confirmed the validity of the proposed mapping approach. In particular, the algorithm allowed us to retrieve soil moisture with a R2 coefficient of 0.77 and with a root mean square error in the order of 0.07 m3/m3.
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