Project/Area Number |
15310114
|
Research Category |
Grant-in-Aid for Scientific Research (B)
|
Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Social systems engineering/Safety system
|
Research Institution | Chiba University |
Principal Investigator |
YAMAZAKI Fumio Chiba University, Faculty of Engineering, Professor, 工学部, 教授 (50220322)
|
Co-Investigator(Kenkyū-buntansha) |
MATSUOKA Masashi National Institute of Earth Science and Disaster Mitigation, EDM, Team Leader, 地震防災フロンティアセンター, 研究員 (80242311)
MITOMI Hajime Asia Air Survey Co., Ltd., Research Engineer, 防災総合防災課, 研究員
小檜山 雅之 東京大学, 生産技術研究所, 助手 (10333577)
|
Project Period (FY) |
2003 – 2004
|
Project Status |
Completed (Fiscal Year 2004)
|
Budget Amount *help |
¥15,800,000 (Direct Cost: ¥15,800,000)
Fiscal Year 2004: ¥6,000,000 (Direct Cost: ¥6,000,000)
Fiscal Year 2003: ¥9,800,000 (Direct Cost: ¥9,800,000)
|
Keywords | high-resolution satellite / damage detection / earthquake / QuickBird / IKONOS / Iran / Tsunami / building damage / 建物倒壊 / アルジェリア地震 |
Research Abstract |
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.
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