Sequential SAR Coherence Method for the Monitoring of Buildings in Sarpole-Zahab, Iran

DOI Web Site 被引用文献11件 参考文献26件 オープンアクセス
  • Sadra Karimzadeh
    Department of Architecture and Building Engineering, Tokyo Institute of Technology, Yokohama 226-8502, Japan
  • Masashi Matsuoka
    Department of Architecture and Building Engineering, Tokyo Institute of Technology, Yokohama 226-8502, Japan
  • Masakatsu Miyajima
    School of Geosciences and Civil Engineering, Kanazawa University, Kanazawa 920-1192, Japan
  • Bruno Adriano
    Geoinformatics Unit, RIKEN Center for Advanced Intelligence Project, Tokyo 103-0027, Japan
  • Abdolhossein Fallahi
    Department of Civil Engineering, Azarbaijan Shahid Madani University, Tabriz 5375171379, Iran
  • Jafar Karashi
    Department of Civil Engineering, Azarbaijan Shahid Madani University, Tabriz 5375171379, Iran

書誌事項

公開日
2018-08-10
資源種別
journal article
権利情報
  • https://creativecommons.org/licenses/by/4.0/
DOI
  • 10.3390/rs10081255
公開者
MDPI AG

説明

<jats:p>In this study, we used fifty-six synthetic aperture radar (SAR) images acquired from the Sentinel-1 C-band satellite with a regular period of 12 days (except for one image) to produce sequential phase correlation (sequential coherence) maps for the town of Sarpole-Zahab in western Iran, which experienced a magnitude 7.3 earthquake on 12 November 2017. The preseismic condition of the buildings in the town was assessed based on a long sequential SAR coherence (LSSC) method, in which we considered 55 of the 56 images to produce a coherence decay model with climatic and temporal parameters. The coseismic condition of the buildings was assessed with 3 later images and normalized RGB visualization using the short sequential SAR coherence (SSSC) method. Discriminant analysis between the completely collapsed and uncollapsed buildings was also performed for approximately 700 randomly selected buildings (for each category) by considering the heights of the buildings and the SSSC results. Finally, the area and volume of debris were calculated based on a fusion of a discriminant map and a 3D vector map of the town.</jats:p>

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