Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
Autor(a) principal: | |
---|---|
Data de Publicação: | 2023 |
Outros Autores: | , , , , , , |
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. |
id |
UNSP_68491b52aa8b46ffdfc4d455cea8e2f8 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/249863 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
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 |
|
_version_ |
1808129081200345088 |