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Soil moisture retrieval is one of the most challenging problems in the context of biophysical parameter estimation from remotely sensed data. Typically, microwave signals are used thanks to their sensitivity to variations in the water content of soil. However, especially in the Alps, the presence of vegetation and the heterogeneity of topographymay significantly affect the microwave signal, thus increasing the complexity of the retrieval. In this paper, the effectiveness of RADARSAT2 SAR images for the estimation of soil moisture in an alpine catchment is investigated.We first carry out a sensitivity analysis of the SAR signal to themoisture content of soil and other target properties (e.g., topography and vegetation). Then we propose a technique for estimating soilmoisture based on the Support Vector Regression algorithm and the integration of ancillary data. Preliminary results are discussed both in terms of accuracy over point measurements and effectiveness in handling spatially distributed data. [ABSTRACT FROM AUTHOR]