Rapid and accurate damage detection in built-up areas combining stripmap and spotlight SAR images

C. Marín, F. Bovolo, L. Bruzzone
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引用次数: 2

Abstract

In this paper an approach that exploits and combines the acquisition modes offered by satellite SAR systems is presented that: i) quickly and automatically identifies the areas severely affected by a catastrophic event (i.e., hotspots), such as an earthquake by analyzing images characterized by a large coverage and a medium to high geometrical resolution; and ii) analyzes images characterized by very high geometrical resolution acquired over hot-spots in order to detect collapsed buildings. Experimental results obtained on a dataset made up of COSMO-SkyMed (CSK) data acquired before and after the 2009 L'Aquila earthquake (Italy) demonstrate the effectiveness of the proposed approach.
结合条形图和聚束SAR图像,快速准确地识别建成区损伤
本文提出了一种利用并结合卫星SAR系统提供的采集模式的方法:i)通过分析具有大覆盖范围和中高几何分辨率的图像,快速自动识别受灾难性事件(即热点)严重影响的区域,例如地震;ii)分析在热点上获得的具有非常高几何分辨率的图像,以检测倒塌的建筑物。在2009年意大利拉奎拉地震前后的COSMO-SkyMed (CSK)数据集上获得的实验结果证明了该方法的有效性。
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