| Project/Area Number |
17H02050
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
Matsuoka Masashi 東京工業大学, 環境・社会理工学院, 教授 (80242311)
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| Co-Investigator(Kenkyū-buntansha) |
三浦 弘之 広島大学, 工学研究科, 准教授 (30418678)
越村 俊一 東北大学, 災害科学国際研究所, 教授 (50360847)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥17,810,000 (Direct Cost: ¥13,700,000、Indirect Cost: ¥4,110,000)
Fiscal Year 2019: ¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2018: ¥6,240,000 (Direct Cost: ¥4,800,000、Indirect Cost: ¥1,440,000)
Fiscal Year 2017: ¥7,670,000 (Direct Cost: ¥5,900,000、Indirect Cost: ¥1,770,000)
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| Keywords | リモートセンシング / 合成開口レーダ / 建物被害 / ガス管被害 / 橋梁沈下 / 液状化被害 / 熊本地震 / 東北地方太平洋沖地震 / PS-InSAR / 干渉InSAR / 橋梁 / 建物 / ガス管 / 地震 / ライフライン / 干渉SAR / ダム |
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| Outline of Final Research Achievements |
It was clarified by simulation that the coherence of PALSAR-2 images before and after the earthquake changed in the liquefaction area of the Kumamoto earthquake. It was also shown that a similar tendency was observed in the liquefaction area of the Hokkaido Iburi Tobu Earthquake. Then, the fragility function was constructed from the building damage data of the Kumamoto earthquake, and the relationship between the ground strain calculated from the SAR image and the gas pipeline damage was clarified. As an example of bridge monitoring, a long-term InSAR analysis from 2004 to 2017 was carried out using four satellite SAR images for a bridge over Lake Urmia, located in the northwestern part of Iran, and clarified the factors of bridge settlement.
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| Academic Significance and Societal Importance of the Research Achievements |
都市インフラ施設の機能を平常時からモニタリングし，地震等の大規模災害後の復旧・復興活動においては，施設の利用可否を判断する必要がある。また，都市における広域的な地盤災害や建物被害の状況を把握することは迅速な災害対応を行う上で重要である。本研究成果は，被災地の現場に行くことなく，宇宙からの人工衛星リモートセンシングにより定常時や災害時の被害状況の把握を可能にする技術で，実際の観測データに基づいて実証していることから，今後，南海トラフ巨大地震や首都直下地震などへの応用が期待できる。
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