Development of Automated Damage Detection Method for Urban Areas Using High-resolution Satellite Images

利用QuickBird(QB)在2004年12月26日伊朗巴姆地震前后获得的巴姆城的高分辨率卫星图像，对建筑物损坏进行了直观的解释。对比震前和震后全锐化的QB图像，根据欧洲宏观地震等级(EMS-98)，识别出被废墟包围的建筑物(3级)、部分倒塌的建筑物(4级)和完全倒塌的建筑物(5级)。共有12,063栋建筑被分类，其中4,951栋为5级，1,700栋为4级。与Hisada等人详细的现场调查数据相比较。(2004)，视觉损害的解释似乎给出了相当准确的结果。针对0.6m分辨率的近垂直图像存在一定的遗漏误差，提出了一种基于图像边缘特征的损伤自动检测方法，该方法利用了图像的边缘特征。由于事件后QB图像与IKONOS图像相比显示出一点不自然的色调，因此在自动损伤检测之前对事件后QB图像进行了颜色修改。从IKONOS和QB图像得到的损坏区域与目视检查结果和现场调查数据吻合得很好。将自动损伤检测方法应用于事前QB图像，发现误差是有限的，在此基础上，论证了高分辨率光学卫星图像在建筑物损伤检测中的准确性和实用性。对于来自不同灾难的各种图像，需要对所提出的方法进行进一步的验证。

Using high-resolution satellite images of Bam City acquired by QuickBird(QB) before and after the 26 December, 2004 Bam, Iran earthquake, visual interpretation of building damage was carried out. Comparing the pre-event and post-event pan-sharpened QB images, buildings surrounded by debris (Grade 3), partially collapsed buildings (Grade 4), and totally collapsed buildings (Grade 5) were identified based on the European Macroseismic Scale (EMS-98). A total of 12,063 buildings were classified ; 4,951 as Grade 5 and 1,700 as Grade 4. Comparing with detailed field survey data by Hisada et al. (2004), the visual damage interpretation seems to give reasonably accurate results. However some amount of omission error was observed due to the limitation of near-vertical images with 0.6m resolution.Post-event IKONOS and QB images were employed in an automated damage detection method, which uses the edge characteristics calculated from post-event gray scale images. Since the post-event QB image shows a bit unnatural color tone comparing with that of the IKONOS image, the color modification was applied to the post-event QB image before the automated damage detection. The resultant damaged areas from the IKONOS and QB images agreed reasonably well with the visual inspection results and the field survey data. The automated damage detection method was also applied to the pre-event QB image, and the commission errors were found to be limited.Based on these studies, the accuracy and usefulness of the high-resolution optical satellite images in building damage detection was demonstrated. A further validation of the proposed method is required for various images from different disasters.