Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil

Detalhes bibliográficos
Autor(a) principal: Mantovani, José Roberto [UNESP]
Data de Publicação: 2023
Outros Autores: Bueno, Guilherme Taitson, Alcântara, Enner [UNESP], Park, Edward, Cunha, Ana Paula [UNESP], Londe, Luciana [UNESP], Massi, Klécia [UNESP], Marengo, Jose A. [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s41651-023-00138-0
http://hdl.handle.net/11449/249863
Resumo: Weather-related disasters have caused widespread deaths and economic losses in developing countries, including Brazil. Frequent floods and landslides in Brazil are mostly climatic driven, often aggravated by human activities and poor environmental planning. In this paper, we aimed to map and discuss the susceptibility to landslides in the urban area of Ouro Preto, Brazil, a municipality with colonial and world heritage houses. We used data on precipitation, soil types, geology, digital elevation model (DEM), and land use and land cover (LULC) of high spatial resolution (1 m). The location of landslides in the urban perimeter was provided by the Civil Defense of Ouro Preto, and these were validated by fieldwork. A novel mathematical model based on multi-criteria decision-making (MCDA) and the Analytic Hierarchy Process (AHP) was used to map the susceptible areas to landslides. Results show that areas most affected by strong landslides were low-density vegetation (high susceptibility) and rocky outcrops (very high susceptibility). The largest areas susceptible to landslides are urban land use areas. Particularly, landslides that occurred in February 2022 in the region were related to intense soil saturation. With an average monthly rainfall of 122.60 mm, the uneven relief and edaphoclimatic characteristics had caused percolation of the surface runoff, naturally triggering landslides. This study supports mitigation efforts by local governments and decision-makers.
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spelling Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, BrazilAHPHeritage sitesNatural hazardsVulnerabilityWeather-related disasters have caused widespread deaths and economic losses in developing countries, including Brazil. Frequent floods and landslides in Brazil are mostly climatic driven, often aggravated by human activities and poor environmental planning. In this paper, we aimed to map and discuss the susceptibility to landslides in the urban area of Ouro Preto, Brazil, a municipality with colonial and world heritage houses. We used data on precipitation, soil types, geology, digital elevation model (DEM), and land use and land cover (LULC) of high spatial resolution (1 m). The location of landslides in the urban perimeter was provided by the Civil Defense of Ouro Preto, and these were validated by fieldwork. A novel mathematical model based on multi-criteria decision-making (MCDA) and the Analytic Hierarchy Process (AHP) was used to map the susceptible areas to landslides. Results show that areas most affected by strong landslides were low-density vegetation (high susceptibility) and rocky outcrops (very high susceptibility). The largest areas susceptible to landslides are urban land use areas. Particularly, landslides that occurred in February 2022 in the region were related to intense soil saturation. With an average monthly rainfall of 122.60 mm, the uneven relief and edaphoclimatic characteristics had caused percolation of the surface runoff, naturally triggering landslides. This study supports mitigation efforts by local governments and decision-makers.Institute of Science and Technology São Paulo State University, SPInstitute of Socio-Environmental Studies Federal University of GoiásGraduate Program in Natural Disasters São Paulo State University, SPNational Institute of Education Earth Observatory of Singapore and Asian School of the Environment Nanyang Technological University (NTU)National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), SPInstitute of Science and Technology São Paulo State University, SPGraduate Program in Natural Disasters São Paulo State University, SPUniversidade Estadual Paulista (UNESP)Universidade Federal de Goiás (UFG)Nanyang Technological University (NTU)National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN)Mantovani, José Roberto [UNESP]Bueno, Guilherme TaitsonAlcântara, Enner [UNESP]Park, EdwardCunha, Ana Paula [UNESP]Londe, Luciana [UNESP]Massi, Klécia [UNESP]Marengo, Jose A. [UNESP]2023-07-29T16:11:13Z2023-07-29T16:11:13Z2023-06-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1007/s41651-023-00138-0Journal of Geovisualization and Spatial Analysis, v. 7, n. 1, 2023.2509-88292509-8810http://hdl.handle.net/11449/24986310.1007/s41651-023-00138-02-s2.0-85152619150Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Geovisualization and Spatial Analysisinfo:eu-repo/semantics/openAccess2024-07-04T19:06:25Zoai:repositorio.unesp.br:11449/249863Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:31:15.176406Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
title Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
spellingShingle Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
Mantovani, José Roberto [UNESP]
AHP
Heritage sites
Natural hazards
Vulnerability
title_short Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
title_full Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
title_fullStr Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
title_full_unstemmed Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
title_sort Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
author Mantovani, José Roberto [UNESP]
author_facet Mantovani, José Roberto [UNESP]
Bueno, Guilherme Taitson
Alcântara, Enner [UNESP]
Park, Edward
Cunha, Ana Paula [UNESP]
Londe, Luciana [UNESP]
Massi, Klécia [UNESP]
Marengo, Jose A. [UNESP]
author_role author
author2 Bueno, Guilherme Taitson
Alcântara, Enner [UNESP]
Park, Edward
Cunha, Ana Paula [UNESP]
Londe, Luciana [UNESP]
Massi, Klécia [UNESP]
Marengo, Jose A. [UNESP]
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Universidade Federal de Goiás (UFG)
Nanyang Technological University (NTU)
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN)
dc.contributor.author.fl_str_mv Mantovani, José Roberto [UNESP]
Bueno, Guilherme Taitson
Alcântara, Enner [UNESP]
Park, Edward
Cunha, Ana Paula [UNESP]
Londe, Luciana [UNESP]
Massi, Klécia [UNESP]
Marengo, Jose A. [UNESP]
dc.subject.por.fl_str_mv AHP
Heritage sites
Natural hazards
Vulnerability
topic AHP
Heritage sites
Natural hazards
Vulnerability
description Weather-related disasters have caused widespread deaths and economic losses in developing countries, including Brazil. Frequent floods and landslides in Brazil are mostly climatic driven, often aggravated by human activities and poor environmental planning. In this paper, we aimed to map and discuss the susceptibility to landslides in the urban area of Ouro Preto, Brazil, a municipality with colonial and world heritage houses. We used data on precipitation, soil types, geology, digital elevation model (DEM), and land use and land cover (LULC) of high spatial resolution (1 m). The location of landslides in the urban perimeter was provided by the Civil Defense of Ouro Preto, and these were validated by fieldwork. A novel mathematical model based on multi-criteria decision-making (MCDA) and the Analytic Hierarchy Process (AHP) was used to map the susceptible areas to landslides. Results show that areas most affected by strong landslides were low-density vegetation (high susceptibility) and rocky outcrops (very high susceptibility). The largest areas susceptible to landslides are urban land use areas. Particularly, landslides that occurred in February 2022 in the region were related to intense soil saturation. With an average monthly rainfall of 122.60 mm, the uneven relief and edaphoclimatic characteristics had caused percolation of the surface runoff, naturally triggering landslides. This study supports mitigation efforts by local governments and decision-makers.
publishDate 2023
dc.date.none.fl_str_mv 2023-07-29T16:11:13Z
2023-07-29T16:11:13Z
2023-06-01
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/10.1007/s41651-023-00138-0
Journal of Geovisualization and Spatial Analysis, v. 7, n. 1, 2023.
2509-8829
2509-8810
http://hdl.handle.net/11449/249863
10.1007/s41651-023-00138-0
2-s2.0-85152619150
url http://dx.doi.org/10.1007/s41651-023-00138-0
http://hdl.handle.net/11449/249863
identifier_str_mv Journal of Geovisualization and Spatial Analysis, v. 7, n. 1, 2023.
2509-8829
2509-8810
10.1007/s41651-023-00138-0
2-s2.0-85152619150
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of Geovisualization and Spatial Analysis
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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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