An integrated method to extract collapsed buildings from satellite imagery, hazard distribution and fragility curves

DOI Web Site Web Site 被引用文献9件 参考文献24件 オープンアクセス

書誌事項

公開日
2018-10
資源種別
journal article
権利情報
  • https://www.elsevier.com/tdm/userlicense/1.0/
  • https://www.elsevier.com/legal/tdmrep-license
  • http://creativecommons.org/licenses/by-nc-nd/4.0/
DOI
  • 10.1016/j.ijdrr.2018.03.034
公開者
Elsevier BV

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説明

Abstract Remote sensing satellite imagery plays an important role in estimating collapsed buildings in the aftermath of a large-scale disaster. However, some previous methodologies are restricted to using specific radar sensors. Others methods, such as machine learning algorithms, require training data, which are extremely difficult to obtain immediately after a disaster. This paper proposes a novel method to extract collapsed buildings based on the integration of satellite imagery, the spatial distribution of a demand parameter, fragility functions, and a geospatial building inventory. The proposed method is applicable regardless of the type of radar sensor and does not require any training data. The method was applied to extract buildings that collapsed during the 2011 Great East Japan Tsunami. The results showed that the proposed method is effective and consistent with the surveyed building damage data.

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