Environmental critical thresholds based on statistical analysis for modelling landslide susceptibility in Continental Basaltic Provinces

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorNational Center for Monitoring and Early Warning of Natural Disasters (CEMADEN)-
Autor(es): dc.creatorRenk, Jennifer Fortes Cavalcante-
Autor(es): dc.creatorMendes, Tatiana Sussel Gonçalves-
Autor(es): dc.creatorSimões, Silvio Jorge Coelho-
Autor(es): dc.creatorde Andrade, Marcio Roberto Magalhães-
Autor(es): dc.creatorPampuch Bortolozo, Luana Albertani-
Autor(es): dc.creatorJunqueira, Adriano Martins-
Autor(es): dc.creatorSilva, Melina Almeida-
Data de aceite: dc.date.accessioned2025-08-21T23:22:16Z-
Data de disponibilização: dc.date.available2025-08-21T23:22:16Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-11-03-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.5194/isprs-annals-X-3-2024-463-2024-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/306868-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/306868-
Descrição: dc.descriptionThe study aims to estimate the environmental critical thresholds using statistical approaches to understand the landslide conditioning factors that can trigger landslides in the Continental Basaltic Provinces a landslide-prone area, using as reference the landslides that occurred in an extreme rainfall event. The study area is a region that was the scene of an extreme hydrological event in January 2017, with an accumulated volume of rain of 163.9 mm in 8 hours, causing a widespread event of shallow planar landslides with more than 400 scars detected. Hydrological, anthropic, geological, geomorphological, and topographical features of this region were analyzed considering landslides and non-landslides samples set, and their influence in the event was carried out using the Frequency Ratio method, followed by Pearson's Linear Correlation Coefficient and Linear Regression. The results showed that this process helped us to understand environmental critical thresholds based on classes of conditioning factors that have a greater influence on rainfall-triggered landslide occurrences and, consequently, higher predictive capacity in the landslide susceptibility models with the same geoenvironmental parameters which is a valuable insight for risk management.-
Descrição: dc.descriptionUniversidade Estadual Paulista-
Descrição: dc.descriptionGraduate Program in Natural Disasters (UNESP/CEMADEN), SP-
Descrição: dc.descriptionInstitute of Science and Technology São Paulo State University (UNESP), SP-
Descrição: dc.descriptionNational Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), SP-
Descrição: dc.descriptionSchool of Engineering São Paulo State University (UNESP), SP-
Descrição: dc.descriptionGraduate Program in Natural Disasters (UNESP/CEMADEN), SP-
Descrição: dc.descriptionInstitute of Science and Technology São Paulo State University (UNESP), SP-
Descrição: dc.descriptionSchool of Engineering São Paulo State University (UNESP), SP-
Formato: dc.format463-470-
Idioma: dc.languageen-
Relação: dc.relationISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectContinental Basaltic Provinces-
Palavras-chave: dc.subjectFrequency Ratio-
Palavras-chave: dc.subjectLandslides Susceptibility-
Palavras-chave: dc.subjectNatural Disasters-
Palavras-chave: dc.subjectPearson's Linear Correlation Coefficient-
Título: dc.titleEnvironmental critical thresholds based on statistical analysis for modelling landslide susceptibility in Continental Basaltic Provinces-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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