Publicación:
Tsunami damage detection with remote sensing: A review

dc.contributor.author Koshimura S. es_PE
dc.contributor.author Moya L. es_PE
dc.contributor.author Mas E. es_PE
dc.contributor.author Bai Y. es_PE
dc.date.accessioned 2024-05-30T23:13:38Z
dc.date.available 2024-05-30T23:13:38Z
dc.date.issued 2020
dc.description.abstract 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.
dc.description.sponsorship Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concytec
dc.identifier.doi https://doi.org/10.3390/geosciences10050177
dc.identifier.scopus 2-s2.0-85085920241
dc.identifier.uri https://hdl.handle.net/20.500.12390/2554
dc.language.iso eng
dc.publisher MDPI AG
dc.relation.ispartof Geosciences (Switzerland)
dc.rights info:eu-repo/semantics/openAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Tsunami
dc.subject Damage detection es_PE
dc.subject Deep learning es_PE
dc.subject Machine learning es_PE
dc.subject Remote sensing es_PE
dc.subject.ocde http://purl.org/pe-repo/ocde/ford#2.02.05
dc.title Tsunami damage detection with remote sensing: A review
dc.type info:eu-repo/semantics/article
dspace.entity.type Publication
Archivos