Polarimetric synthetic aperture radar change detection for specific land cover types

This paper presents a supervised polarimetric synthetic aperture radar(PolSAR)change detection method applied to specific land cover types.For each pixel of a PolSAR image,its target scattering vector can be modeled as having a complex multivariate normal distribution.Based on this assumption,the joint distribution of two corresponding vectors in a pair of PolSAR images is derived.Then,a generalized likelihood ratio test statistic for the equality of two likelihood functions of such joint distribution is considered and a maximum likelihood distance measure for specific land cover types is presented.Subsequently,the Kittler and Illingworth minimum error threshold segmenta-tion method is applied to extract the specific changed areas.Experiments on two repeat-pass Radarsat-2 fully polarimetric images of Suzhou,China,demonstrate that the proposed change detection method gives a good performance in determining the specific changed areas in PolSAR images,especially the areas that have changed to water.