Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami
Descripción del Articulo
We developed tsunami fragility functions using three sources of damage data from the 2018 Sulawesi tsunami at Palu Bay in Indonesia obtained from (i) field survey data (FS), (ii) a visual interpretation of optical satellite images (VI), and (iii) a machine learning and remote sensing approach utiliz...
Autores: | , , , , , , , , , , |
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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:20.500.12390/2545 |
Enlace del recurso: | https://hdl.handle.net/20.500.12390/2545 https://doi.org/10.1007/s00024-020-02501-4 |
Nivel de acceso: | acceso abierto |
Materia: | tsunami 2018 Sulawesi earthquake Fragility function http://purl.org/pe-repo/ocde/ford#1.05.11 |
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CONCYTEC-Institucional |
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4689 |
dc.title.none.fl_str_mv |
Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami |
title |
Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami |
spellingShingle |
Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami Mas E. tsunami 2018 Sulawesi earthquake Fragility function http://purl.org/pe-repo/ocde/ford#1.05.11 |
title_short |
Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami |
title_full |
Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami |
title_fullStr |
Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami |
title_full_unstemmed |
Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami |
title_sort |
Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami |
author |
Mas E. |
author_facet |
Mas E. Paulik R. Pakoksung K. Adriano B. Moya L. Suppasri A. Muhari A. Khomarudin R. Yokoya N. Matsuoka M. Koshimura S. |
author_role |
author |
author2 |
Paulik R. Pakoksung K. Adriano B. Moya L. Suppasri A. Muhari A. Khomarudin R. Yokoya N. Matsuoka M. Koshimura S. |
author2_role |
author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Mas E. Paulik R. Pakoksung K. Adriano B. Moya L. Suppasri A. Muhari A. Khomarudin R. Yokoya N. Matsuoka M. Koshimura S. |
dc.subject.none.fl_str_mv |
tsunami |
topic |
tsunami 2018 Sulawesi earthquake Fragility function http://purl.org/pe-repo/ocde/ford#1.05.11 |
dc.subject.es_PE.fl_str_mv |
2018 Sulawesi earthquake Fragility function |
dc.subject.ocde.none.fl_str_mv |
http://purl.org/pe-repo/ocde/ford#1.05.11 |
description |
We developed tsunami fragility functions using three sources of damage data from the 2018 Sulawesi tsunami at Palu Bay in Indonesia obtained from (i) field survey data (FS), (ii) a visual interpretation of optical satellite images (VI), and (iii) a machine learning and remote sensing approach utilized on multisensor and multitemporal satellite images (MLRS). Tsunami fragility functions are cumulative distribution functions that express the probability of a structure reaching or exceeding a particular damage state in response to a specific tsunami intensity measure, in this case obtained from the interpolation of multiple surveyed points of tsunami flow depth. We observed that the FS approach led to a more consistent function than that of the VI and MLRS methods. In particular, an initial damage probability observed at zero inundation depth in the latter two methods revealed the effects of misclassifications on tsunami fragility functions derived from VI data; however, it also highlighted the remarkable advantages of MLRS methods. The reasons and insights used to overcome such limitations are discussed together with the pros and cons of each method. The results show that the tsunami damage observed in the 2018 Sulawesi event in Indonesia, expressed in the fragility function developed herein, is similar in shape to the function developed after the 1993 Hokkaido Nansei-oki tsunami, albeit with a slightly lower damage probability between zero-to-five-meter inundation depths. On the other hand, in comparison with the fragility function developed after the 2004 Indian Ocean tsunami in Banda Aceh, the characteristics of Palu structures exhibit higher fragility in response to tsunamis. The two-meter inundation depth exhibited nearly 20% probability of damage in the case of Banda Aceh, while the probability of damage was close to 70% at the same depth in Palu. © 2020, The Author(s). |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2024-05-30T23:13:38Z |
dc.date.available.none.fl_str_mv |
2024-05-30T23:13:38Z |
dc.date.issued.fl_str_mv |
2020 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12390/2545 |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1007/s00024-020-02501-4 |
dc.identifier.scopus.none.fl_str_mv |
2-s2.0-85085939746 |
url |
https://hdl.handle.net/20.500.12390/2545 https://doi.org/10.1007/s00024-020-02501-4 |
identifier_str_mv |
2-s2.0-85085939746 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.none.fl_str_mv |
Pure and Applied Geophysics |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.uri.none.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.publisher.none.fl_str_mv |
Birkhauser |
publisher.none.fl_str_mv |
Birkhauser |
dc.source.none.fl_str_mv |
reponame:CONCYTEC-Institucional instname:Consejo Nacional de Ciencia Tecnología e Innovación instacron:CONCYTEC |
instname_str |
Consejo Nacional de Ciencia Tecnología e Innovación |
instacron_str |
CONCYTEC |
institution |
CONCYTEC |
reponame_str |
CONCYTEC-Institucional |
collection |
CONCYTEC-Institucional |
repository.name.fl_str_mv |
Repositorio Institucional CONCYTEC |
repository.mail.fl_str_mv |
repositorio@concytec.gob.pe |
_version_ |
1844883065956990976 |
spelling |
Publicationrp05687600rp06549600rp06550600rp06546600rp05688600rp06553600rp06552600rp06547600rp06548600rp06551600rp05690600Mas E.Paulik R.Pakoksung K.Adriano B.Moya L.Suppasri A.Muhari A.Khomarudin R.Yokoya N.Matsuoka M.Koshimura S.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2020https://hdl.handle.net/20.500.12390/2545https://doi.org/10.1007/s00024-020-02501-42-s2.0-85085939746We developed tsunami fragility functions using three sources of damage data from the 2018 Sulawesi tsunami at Palu Bay in Indonesia obtained from (i) field survey data (FS), (ii) a visual interpretation of optical satellite images (VI), and (iii) a machine learning and remote sensing approach utilized on multisensor and multitemporal satellite images (MLRS). Tsunami fragility functions are cumulative distribution functions that express the probability of a structure reaching or exceeding a particular damage state in response to a specific tsunami intensity measure, in this case obtained from the interpolation of multiple surveyed points of tsunami flow depth. We observed that the FS approach led to a more consistent function than that of the VI and MLRS methods. In particular, an initial damage probability observed at zero inundation depth in the latter two methods revealed the effects of misclassifications on tsunami fragility functions derived from VI data; however, it also highlighted the remarkable advantages of MLRS methods. The reasons and insights used to overcome such limitations are discussed together with the pros and cons of each method. The results show that the tsunami damage observed in the 2018 Sulawesi event in Indonesia, expressed in the fragility function developed herein, is similar in shape to the function developed after the 1993 Hokkaido Nansei-oki tsunami, albeit with a slightly lower damage probability between zero-to-five-meter inundation depths. On the other hand, in comparison with the fragility function developed after the 2004 Indian Ocean tsunami in Banda Aceh, the characteristics of Palu structures exhibit higher fragility in response to tsunamis. The two-meter inundation depth exhibited nearly 20% probability of damage in the case of Banda Aceh, while the probability of damage was close to 70% at the same depth in Palu. © 2020, The Author(s).Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengBirkhauserPure and Applied Geophysicsinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/4.0/tsunami2018 Sulawesi-1earthquake-1Fragility function-1http://purl.org/pe-repo/ocde/ford#1.05.11-1Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunamiinfo:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/2545oai:repositorio.concytec.gob.pe:20.500.12390/25452024-05-30 16:09:14.937https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="2533c48b-03b4-47d7-9f0f-e4d1adab65e4"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Characteristics of Tsunami Fragility Functions Developed Using Different Sources of Damage Data from the 2018 Sulawesi Earthquake and Tsunami</Title> <PublishedIn> <Publication> <Title>Pure and Applied Geophysics</Title> </Publication> </PublishedIn> <PublicationDate>2020</PublicationDate> <DOI>https://doi.org/10.1007/s00024-020-02501-4</DOI> <SCP-Number>2-s2.0-85085939746</SCP-Number> <Authors> <Author> <DisplayName>Mas E.</DisplayName> <Person id="rp05687" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Paulik R.</DisplayName> <Person id="rp06549" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Pakoksung K.</DisplayName> <Person id="rp06550" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Adriano B.</DisplayName> <Person id="rp06546" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Moya L.</DisplayName> <Person id="rp05688" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Suppasri A.</DisplayName> <Person id="rp06553" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Muhari A.</DisplayName> <Person id="rp06552" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Khomarudin R.</DisplayName> <Person id="rp06547" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Yokoya N.</DisplayName> <Person id="rp06548" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Matsuoka M.</DisplayName> <Person id="rp06551" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Koshimura S.</DisplayName> <Person id="rp05690" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Birkhauser</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by-nc-nd/4.0/</License> <Keyword>tsunami</Keyword> <Keyword>2018 Sulawesi</Keyword> <Keyword>earthquake</Keyword> <Keyword>Fragility function</Keyword> <Abstract>We developed tsunami fragility functions using three sources of damage data from the 2018 Sulawesi tsunami at Palu Bay in Indonesia obtained from (i) field survey data (FS), (ii) a visual interpretation of optical satellite images (VI), and (iii) a machine learning and remote sensing approach utilized on multisensor and multitemporal satellite images (MLRS). Tsunami fragility functions are cumulative distribution functions that express the probability of a structure reaching or exceeding a particular damage state in response to a specific tsunami intensity measure, in this case obtained from the interpolation of multiple surveyed points of tsunami flow depth. We observed that the FS approach led to a more consistent function than that of the VI and MLRS methods. In particular, an initial damage probability observed at zero inundation depth in the latter two methods revealed the effects of misclassifications on tsunami fragility functions derived from VI data; however, it also highlighted the remarkable advantages of MLRS methods. The reasons and insights used to overcome such limitations are discussed together with the pros and cons of each method. The results show that the tsunami damage observed in the 2018 Sulawesi event in Indonesia, expressed in the fragility function developed herein, is similar in shape to the function developed after the 1993 Hokkaido Nansei-oki tsunami, albeit with a slightly lower damage probability between zero-to-five-meter inundation depths. On the other hand, in comparison with the fragility function developed after the 2004 Indian Ocean tsunami in Banda Aceh, the characteristics of Palu structures exhibit higher fragility in response to tsunamis. The two-meter inundation depth exhibited nearly 20% probability of damage in the case of Banda Aceh, while the probability of damage was close to 70% at the same depth in Palu. © 2020, The Author(s).</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1 |
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13.243185 |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).