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

Luis Moya, Erick Mas, Bruno Adriano, Shunichi Koshimura, Fumio Yamazaki, Wen Liu

    研究成果: Article査読

    11 被引用数 (Scopus)

    抄録

    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.

    本文言語English
    ページ(範囲)1374-1384
    ページ数11
    ジャーナルInternational Journal of Disaster Risk Reduction
    31
    DOI
    出版ステータスPublished - 2018 10

    ASJC Scopus subject areas

    • 地盤工学および土木地質学
    • 安全研究
    • 地質学

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