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

    Research output: Contribution to journalArticlepeer-review

    15 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)1374-1384
    Number of pages11
    JournalInternational Journal of Disaster Risk Reduction
    Volume31
    DOIs
    Publication statusPublished - 2018 Oct

    Keywords

    • Collapsed buildings
    • SAR images
    • The 2011 Great East Japan Tsunami

    ASJC Scopus subject areas

    • Geotechnical Engineering and Engineering Geology
    • Safety Research
    • Geology

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