Abstract
In this work, the polarimetric capability of RADARSAT-2 images is exploited in the aim of soil moisture content retrieval in Alpine meadows and pastures. Three feature extraction methods are investigated: the simple polarimetric intensity and phase processing, the H/A/α polarimetric decomposition, and the Independent Component Analysis (ICA). The features extracted according to these strategies were assessed for their capability to improve the soil moisture estimation by considering both quantitative performance on a set of reference samples and qualitative analysis of the corresponding output soil moisture content maps. The method proposed for the soil moisture estimation was based on the Support Vector Regression technique combined with an innovative multi-objective model selection strategy. The results indicated that the use of polarimetric features such as HH and HV channels improved the estimation of soil moisture content in the investigated mountain area, especially because the HV channel was able to disentangle the vegetation effect on the radar signal. From the preliminary results presented in this paper, the use of the H/A/α polarimetric decomposition and the ICA technique seem to not determine a significant improvement in the soil moisture estimation.
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