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

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dc.contributor.authorMantovani, José Roberto [UNESP]
dc.contributor.authorBueno, Guilherme Taitson
dc.contributor.authorAlcântara, Enner [UNESP]
dc.contributor.authorPark, Edward
dc.contributor.authorCunha, Ana Paula [UNESP]
dc.contributor.authorLonde, Luciana [UNESP]
dc.contributor.authorMassi, Klécia [UNESP]
dc.contributor.authorMarengo, Jose A. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade Federal de Goiás (UFG)
dc.contributor.institutionNanyang Technological University (NTU)
dc.contributor.institutionNational Center for Monitoring and Early Warning of Natural Disasters (CEMADEN)
dc.date.accessioned2023-07-29T16:11:13Z
dc.date.available2023-07-29T16:11:13Z
dc.date.issued2023-06-01
dc.description.abstractWeather-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.en
dc.description.affiliationInstitute of Science and Technology São Paulo State University, SP
dc.description.affiliationInstitute of Socio-Environmental Studies Federal University of Goiás
dc.description.affiliationGraduate Program in Natural Disasters São Paulo State University, SP
dc.description.affiliationNational Institute of Education Earth Observatory of Singapore and Asian School of the Environment Nanyang Technological University (NTU)
dc.description.affiliationNational Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), SP
dc.description.affiliationUnespInstitute of Science and Technology São Paulo State University, SP
dc.description.affiliationUnespGraduate Program in Natural Disasters São Paulo State University, SP
dc.identifierhttp://dx.doi.org/10.1007/s41651-023-00138-0
dc.identifier.citationJournal of Geovisualization and Spatial Analysis, v. 7, n. 1, 2023.
dc.identifier.doi10.1007/s41651-023-00138-0
dc.identifier.issn2509-8829
dc.identifier.issn2509-8810
dc.identifier.scopus2-s2.0-85152619150
dc.identifier.urihttp://hdl.handle.net/11449/249863
dc.language.isoeng
dc.relation.ispartofJournal of Geovisualization and Spatial Analysis
dc.sourceScopus
dc.subjectAHP
dc.subjectHeritage sites
dc.subjectNatural hazards
dc.subjectVulnerability
dc.titleNovel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazilen
dc.typeArtigo
unesp.author.orcid0000-0002-7777-2119[3]
unesp.departmentEngenharia Elétrica - FEISpt

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Ilha Solteira - FEIS - Faculdade de Engenharia