Flood Detection in PolSAR Images Based on Level Set Method Considering Prior Geoinformation

This letter presents a novel flood detection approach using full polarimetric synthetic aperture radar (PolSAR) images based on a level set method considering prior geoinformation. The prior geoinformation includes information derived from vector data and topography data. The main approach accomplishes flood detection by the improved level set method, an active contour segmentation model, based on the classical Wishart distribution. Vector data are used to generate the zero initial level set curves. To investigate the separability between water and nonwater low–backscattering objects in PolSAR images, topography information is incorporated into the level set function as a constraint. Moreover, we introduce a piecewise statistical method to refine the result with the Kullback–Leibler divergence of circular polarization coherence. In addition, we design a new quantitative evaluation index to assess flood detection results. For validation, three real PolSAR images of flooded area are tested. The experimental results confirm the effectiveness of the proposed method.