Land cover classification of polarimetric synthetic aperture radar (POLSAR) data based on scattering mechanisms and complex wishart distribution

The use of C- and L-band polarimetric synthetic aperture radar (POLSAR) data for classifying land cover features in a tropical area is investigated in this study. The POLSAR data were acquired during the NASA/JPL PACRIM-1 mission over the northern part of Peninsular Malaysia on 3(rd) December 1996. Prior to classification, the Lee polarimetric filter was applied to the complex covariance matrix for speckle suppression. In unsupervised classification, the scattering mechanism of each pixel in the speckle-suppressed images was analyzed and grouped into one of the three categories: (1) odd-bounce, (2) even-bounce, or (3) diffuse scattering. Training samples were then generated from the outputs of the unsupervised classification, to be used in subsequent supervised classifications of various frequency and polarization combinations. The Kappa statistics computed for classification using single-frequency fully polarized C- and L-band data were 0.69 and 0.73, respectively. An improvement to 0.79 was achieved by using the dual-frequency (combined C and L bands), fully polarized data in the classification.