Soil Moisture Retrieval from Polarimetric Sar Data: a Short Review of Existing Methods and a New One

Soil moisture retrieval from SAR data is not an easy task, especially in presence of vegetation cover. Accordingly, in recent years several methods for soil-moisture retrieval under vegetation cover have been developed, relying on model-based or hybrid polarimetric targetdecomposition techniques. However, most of these decomposition techniques suffer from the so-called negative-power problem, which is mainly related to poor modelling of surfaceand/or volume-scattering contributions. In this paper we, first, analyse the Polarimetric Two-Scale Two-Component Model and the Iterative Generalized Hybrid Decomposition method, proposing a way to combine the estimation results of the methods so that most vegetation conditions can be accounted for. Then, we introduce a method that tries to solve the case of dominant surface scattering and nonnegligible dihedral scattering, which is the case not covered by the abovementioned model combination. Meaningful estimation results are presented and discussed using polarimetric L-band SAR data of the AgriSAR 2006 campaign.