Tsunami damage detection with remote sensing: A review

Shunichi Koshimura, Luis Moya, Erick Mas, Yanbing Bai

Research output: Contribution to journalReview articlepeer-review

44 Citations (Scopus)


Tsunamis are rare events compared with the other natural disasters, but once it happens, it can be extremely devastating to the coastal communities. Extensive inland penetration of tsunamis may cause the difficulties of understanding its impact in the aftermath of its generation. Therefore the social needs to technologies of detecting the wide impact of great tsunamis have been increased. Recent advances of remote sensing and technologies of image analysis meet the above needs and lead to more rapid and efficient understanding of tsunami affected areas. This paper provides a review of how remote sensing methods have developed to contribute to post-tsunami disaster response. The evaluations in the performances of the remote sensing methods are discussed according to the needs of tsunami disaster response with future perspective.

Original languageEnglish
Article number177
JournalGeosciences (Switzerland)
Issue number5
Publication statusPublished - 2020 May


  • Damage detection
  • Deep learning
  • Machine learning
  • Remote sensing
  • Tsunami


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