Change detections from sar images for damage estimation based on a spatial chaotic model

Abstract

Because of its all-weather and all-time characteristics, SAR images are particularly effective to monitor disaster events. When a disaster occurs, the image acquired from a SAR sensor changes dramatically. As a result, damage estimation for natural and human-made disasters from SAR images can be achieved by applying a change detection technique. Theoretically, SAR signals can be characterized as a chaotic phenomenon because that the scattering signals within a resolution cell are summed up coherently. Accordingly, SAR signal can be represented by a spatial chaotic model and characterized by its fractal dimension. In this paper, based on the spatial chaotic model, a simplified SAR image change detection procedure is proposed. The proposed method is then applied to estimate the flood-damage area caused by flooding events. Experimental results reveal that the proposed method is an effective and efficient tool for damage estimation from SAR images.