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

利用高分辨率卫星图像开发城市地区自动损害检测方法

基本信息

批准号：
15310114
负责人：
YAMAZAKI Fumio
金额：
$ 10.11万
依托单位：
Chiba University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2004
项目状态：
已结题

项目摘要

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.

利用QuickBird（QB）在2004年12月26日伊朗巴姆地震前后获得的巴姆市高分辨率卫星图像，对建筑物损坏情况进行了目视判读。比较事件前和事件后的泛锐化QB图像，被碎片包围的建筑物（3级），部分倒塌的建筑物（4级），完全倒塌的建筑物（5级）被确定为基于欧洲宏观地震等级（EMS-98）。共有12，063幢楼宇被评定为五级楼宇，其中4，951幢为五级楼宇，1，700幢为四级楼宇。与Hisada等人（2004）的详细现场调查数据相比，目视损害解释似乎给出了相当准确的结果。然而，由于0.6m分辨率的近垂直图像的限制，观察到一定量的遗漏错误。在一个自动损伤检测方法中，使用灾后IKONOS和QB图像，它使用从灾后灰度图像计算的边缘特征。由于与IKONOS图像相比，事件后QB图像显示出有点不自然的色调，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图像得到的受损面积与目视检查结果和实地调查数据相当吻合。将该方法应用于地震前的QB影像，检测误差较小，证明了高分辨率光学卫星影像在建筑物损伤检测中的准确性和实用性。所提出的方法的进一步验证，需要从不同的灾害的各种图像。