Interpretation of SAR-data using polarimetric techniques

Classification of Earth terrain components within full polarimetric data sets is an important application of Radar Polarimetry. Several investigations have reported the use of polarimetric data to map earth terrain types and land covers [1],[2],[3] and have advanced a good understanding of polarimetric scattering mechanisms. In this paper an approach based on the Shane R. Cloude's Decomposition Theorem [1] is outlined. The Entropy H and alpha - angle Classification is extended by using not only the H and a parameters but also the first eigenvalue. The main advantage of these approaches is the strong correlation between the polarimetric results and the physical reality which makes this methods suitable for unsupervised and automatic classification. The potential of this methods is demonstrated using space borne data acquired during SIR-C/X-SAR mission as well as airborne SAR data in L-band from DLR's Experimental SAR (ESAR) system of the test site Oberpfaffenhofen, Germany. The classifications are geocoded and compared to ground data for validation purposes.