Optimal use of polarimetric signature on PALSAR-2 data for land cover classification

Abstract

SAR data is playing key role in monitoring, the current status or change in, the land cover. For unsupervised SAR image classification, polarization signatures can play a significant role. Since it is difficult to obtain specific polarization signature of real land cover, it is customary to represent them with standard canonical structures polarization signatures. A critical analysis of the complex signatures of real targets is essential thereafter it is also a challenge to decide the thresholds or class boundary value on the correlation images. Therefore, in this paper an attempt has been made to critically analyze the polarimetric signature of complex targets and based on the correlation image analysis an OTSU multi-thresholding based approach is proposed to decide the individual class boundary values which will finally help in building a decision tree (DT) based classification technique. For this purpose L band fully polarimetric SAR data (PALSAR-2) has been used. DT class thresholds are computed using OTSU multi-thresholding method, scatter plot method, and a priori information. Obtained results reveal that complementary features like polarization signatures can help in identification as well as classification of land surface objects significantly by the proposed method. © 2017 IEEE.