Scattering-Mechanism-Based Investigation of Optimal Combinations of Polarimetric SAR Frequency Bands for Land Cover Classification

Abstract

Aiming at steering the selection of optimal combinations of polarimetric SAR (PolSAR) frequency bands for different land cover classification schemes, this study investigates the land cover classification capabilities of all the possible combinations of L-band ALOS PALSAR fully PolSAR data, C-band RADARSAT-2 fully PolSAR data, and X-band TerraSAR-X HH SAR data. A method that integrates polarimetric decomposition, object-based image analysis, decision tree algorithms, and support vector machines is used for the classification. Polarimetric decomposition theorems are used to interpret the scattering mechanisms at the different frequency bands to reveal the effect mechanisms of PolSAR frequency variation on the classification capability. This study finds that (1) X-band HH SAR is not necessary for classifying the land cover types involved in this study when C- or L-band fully PolSAR are used; (2) C-band fully PolSAR alone is adequate for classifying primitive land cover types, namely, water, bare land, vegetation, and built-up areas; and (3) L-band fully PolSAR alone is adequate for distinguishing between various vegetation types, such as crops, banana trees, and forests.