Tsunami damage detection with remote sensing: A review

• Autores: Koshimura S., Moya L., Mas E., Bai Y.
• Formato: artículo
• Fecha de Publicación: 2020
• Institución: Consejo Nacional de Ciencia Tecnología e Innovación
• Repositorio: CONCYTEC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.concytec.gob.pe:20.500.12390/2554
• Enlace del recurso: https://hdl.handle.net/20.500.12390/2554; https://doi.org/10.3390/geosciences10050177
• Nivel de acceso: acceso abierto
• Materia: Tsunami; Damage detection; Deep learning; Machine learning; Remote sensing; http://purl.org/pe-repo/ocde/ford#2.02.05

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. ©2020 by the authors. Licensee MDPI, Basel, Switzerland.