Integration of Building Unit Based and Zonal Based Approaches to Detect Washed-away Buildings in a Tsunami Affected Area Using TerraSAR-X Data

• GOKON Hideomi

  Institute of Industrial Science, The University of Tokyo

• KOSHIMURA Shunichi

  Tohoku University

• MATSUOKA Masashi

  Tokyo Institute of Technology

Bibliographic Information

Other Title

• TerraSAR-X画像の建物一棟ベース・解析区画ベース解析の融合による津波被災地の建物流失被害の把握

Abstract

A new method to detect buildings washed away by a tsunami is proposed using high-resolution Synthetic Aperture Radar (TerraSAR-X) data. The main focus of this study is to integrate building unit based approach and zonal based approach to detect building damage at a building unit scale. These were integrated based on decision tree application (C4.5) of machine learning algorithm. Finally, classifier for detecting washed-away buildings was developed and applied to Sendai coast, performing 91.0 % overall accuracy and kappa statistic of 0.82.

Journal

• Journal of Japan Association for Earthquake Engineering

  Journal of Japan Association for Earthquake Engineering 16 (3), 3_147-3_156, 2016

  JAPAN ASSOCIATION FOR EARTHQUAKE ENGINEERING

Keywords

• Tsunami
• Synthetic Aperture Radar
• Building damage

Details

• CRID: 1390282680334403200
• NII Article ID: 130005133029
• DOI: 10.5610/jaee.16.3_147
• ISSN: 18846246
• Web Site: https://www.jstage.jst.go.jp/article/jaee/16/3/16_3_147/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed