Building Damage Assessment from Post-Event Polsar Image Based on Opce and Template Matching

Abstract

Timely detection and identification of building damage is vitally important for rescue planning after a catastrophic earthquake. Synthetic aperture radar (SAR) is a powerful tool for monitoring large-scale damage and can provide quick response. Compared with single-polarization SAR, fully polarimetric SAR (PolSAR) provides richer backscatter information of targets, making it possible to assess building damage with only post-event SAR data. In this study, we propose a novel building damage assessment method from post-seismic PolSAR image. This method combines the optimization of polarimetric contrast enhancement (OPCE) algorithm and the template matching thoughts to build a new building damage detector. The Radarsat-2 PolSAR image acquired in affected areas after the 2010 Yushu earthquake is used to analyze the performance of the proposed method. The result shows the effectiveness of the proposed method, and the detection rate of serious building damage areas can up to 83.2%.