Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil)
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1111/tgis.12962 http://hdl.handle.net/11449/240268 |
Resumo: | Cities increasingly face flood risk primarily due to extensive changes of the natural land cover to built-up areas with impervious surfaces. In urban areas, flood impacts come mainly from road interruption. This article proposes an urban flood risk map from hydrological and mobility data, considering the megacity of São Paulo, Brazil, as a case study. We estimate the flood susceptibility through the Height Above the Nearest Drainage algorithm; and the potential impact through the exposure and vulnerability components. We aggregate all variables into a regular grid and then classify the cells of each component into three classes: Moderate, High, and Very High. All components, except the flood susceptibility, have few cells in the Very High class. The flood susceptibility component reflects the presence of watercourses, and it has a strong influence on the location of those cells classified as Very High. |
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Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil)Cities increasingly face flood risk primarily due to extensive changes of the natural land cover to built-up areas with impervious surfaces. In urban areas, flood impacts come mainly from road interruption. This article proposes an urban flood risk map from hydrological and mobility data, considering the megacity of São Paulo, Brazil, as a case study. We estimate the flood susceptibility through the Height Above the Nearest Drainage algorithm; and the potential impact through the exposure and vulnerability components. We aggregate all variables into a regular grid and then classify the cells of each component into three classes: Moderate, High, and Very High. All components, except the flood susceptibility, have few cells in the Very High class. The flood susceptibility component reflects the presence of watercourses, and it has a strong influence on the location of those cells classified as Very High.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Deutsche ForschungsgemeinschaftFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Research Department National Center for Monitoring and Early Warning of Natural Disasters (Cemaden), São PauloPostgraduate Program in Applied Computing - CAP National Institute for Space Research (INPE), São PauloDepartment of Environmental Engineering São Paulo State UniversityDepartment of Computing Federal University of Ouro Preto, Minas GeraisDepartment of Environmental Engineering São Paulo State UniversityNational Center for Monitoring and Early Warning of Natural Disasters (Cemaden)National Institute for Space Research (INPE)Universidade Estadual Paulista (UNESP)Federal University of Ouro PretoTomás, Lívia RodriguesSoares, Giovanni GuarnieriJorge, Aurelienne A. S.Mendes, Jeferson Feitosa [UNESP]Freitas, Vander L. S.Santos, Leonardo B. L.2023-03-01T20:09:22Z2023-03-01T20:09:22Z2022-08-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article2341-2365http://dx.doi.org/10.1111/tgis.12962Transactions in GIS, v. 26, n. 5, p. 2341-2365, 2022.1467-96711361-1682http://hdl.handle.net/11449/24026810.1111/tgis.129622-s2.0-85132177753Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengTransactions in GISinfo:eu-repo/semantics/openAccess2023-03-01T20:09:22Zoai:repositorio.unesp.br:11449/240268Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-03-01T20:09:22Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil) |
title |
Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil) |
spellingShingle |
Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil) Tomás, Lívia Rodrigues |
title_short |
Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil) |
title_full |
Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil) |
title_fullStr |
Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil) |
title_full_unstemmed |
Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil) |
title_sort |
Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil) |
author |
Tomás, Lívia Rodrigues |
author_facet |
Tomás, Lívia Rodrigues Soares, Giovanni Guarnieri Jorge, Aurelienne A. S. Mendes, Jeferson Feitosa [UNESP] Freitas, Vander L. S. Santos, Leonardo B. L. |
author_role |
author |
author2 |
Soares, Giovanni Guarnieri Jorge, Aurelienne A. S. Mendes, Jeferson Feitosa [UNESP] Freitas, Vander L. S. Santos, Leonardo B. L. |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
National Center for Monitoring and Early Warning of Natural Disasters (Cemaden) National Institute for Space Research (INPE) Universidade Estadual Paulista (UNESP) Federal University of Ouro Preto |
dc.contributor.author.fl_str_mv |
Tomás, Lívia Rodrigues Soares, Giovanni Guarnieri Jorge, Aurelienne A. S. Mendes, Jeferson Feitosa [UNESP] Freitas, Vander L. S. Santos, Leonardo B. L. |
description |
Cities increasingly face flood risk primarily due to extensive changes of the natural land cover to built-up areas with impervious surfaces. In urban areas, flood impacts come mainly from road interruption. This article proposes an urban flood risk map from hydrological and mobility data, considering the megacity of São Paulo, Brazil, as a case study. We estimate the flood susceptibility through the Height Above the Nearest Drainage algorithm; and the potential impact through the exposure and vulnerability components. We aggregate all variables into a regular grid and then classify the cells of each component into three classes: Moderate, High, and Very High. All components, except the flood susceptibility, have few cells in the Very High class. The flood susceptibility component reflects the presence of watercourses, and it has a strong influence on the location of those cells classified as Very High. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-08-01 2023-03-01T20:09:22Z 2023-03-01T20:09:22Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1111/tgis.12962 Transactions in GIS, v. 26, n. 5, p. 2341-2365, 2022. 1467-9671 1361-1682 http://hdl.handle.net/11449/240268 10.1111/tgis.12962 2-s2.0-85132177753 |
url |
http://dx.doi.org/10.1111/tgis.12962 http://hdl.handle.net/11449/240268 |
identifier_str_mv |
Transactions in GIS, v. 26, n. 5, p. 2341-2365, 2022. 1467-9671 1361-1682 10.1111/tgis.12962 2-s2.0-85132177753 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Transactions in GIS |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
2341-2365 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1803649390804467712 |