Abstract:
In this paper, polarization signatures are extracted for utilization of the fully polarimetrie L-band ALOS-PALSAR 2 data. These signatures are extracted for different land cover classes (i.e., urban, water, short vegetation, tall vegetation and bare soil). Critical analysis is performed on the polarization signatures generated of different classes. Further, polarization signatures of different classes are compared with the help of normalized Euclidean distance (NED) and normalized signature correlation mapper (NSCM). Decision tree based algorithm is developed with the help of NSCM, NED and backscattered image for the classification of different land cover classes.