Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/jspui/handle/123456789/13631
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dc.contributor.authorRosa, Mateus Lima-
dc.contributor.authorSobreira, Frederico Garcia-
dc.contributor.authorBarella, Cesar Falcão-
dc.date.accessioned2021-09-01T20:20:33Z-
dc.date.available2021-09-01T20:20:33Z-
dc.date.issued2021pt_BR
dc.identifier.citationROSA, M. L.; SOBREIRA, F. G.; BARELLA, C. F. Landslide susceptibility mapping using the statistical method of information value: a study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil. Anais da Academia Brasileira de Ciências, v. 93, n. 1, 2021. Disponível em: <https://www.scielo.br/scielo.php?pid=S0001-37652021000101202&script=sci_abstract>. Acesso em: 24 mar. 2021.pt_BR
dc.identifier.issn1678-2690-
dc.identifier.urihttp://www.repositorio.ufop.br/jspui/handle/123456789/13631-
dc.description.abstractThis research study was developed in the Ribeirão dos Macacos basin at the district of Nova Lima, Minas Gerais state, Brazil. The information value statistical method was applied in the construction of the landslide susceptibility map at the 1:25,000 scale. Different partitions of the inventory were tested, as well as different landslide predisposing factors. In the construction of the landslide inventory, the south, southeast and south-west slopes generally present a higher quality in aerial / orbital images due to the position of the sun (lighting direction), which emphasizes the surface structures and it may omit old landslides on slopes facing north, northeast, and northwest. This condition can generate misleading models when using the slope aspect. Another verifi cation was that the models with better Area Under the Curve index will not always restrict the high susceptibility class in smaller areas. This incongruence occurs due to the different curve conformations, since a smaller index curve can present more restrictive results than a larger index curve. The results showed that the model has a high capacity of adjustment to the input data and high landslide predictive capacity.pt_BR
dc.language.isoen_USpt_BR
dc.rightsabertopt_BR
dc.subjectNatural disasterspt_BR
dc.subjectTerritorial planningpt_BR
dc.titleLandslide susceptibility mapping using the statistical method of information value : a study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil.pt_BR
dc.typeArtigo publicado em periodicopt_BR
dc.rights.licenseOs trabalhos publicados no periódico Anais da Academia Brasileira de Ciências, exceto onde identificado, está sob uma licença Creative Commons que permite copiar, distribuir e transmitir o trabalho desde que sejam citados o autor e o licenciante. Fonte: Anais da Academia Brasileira de Ciências <http://www.scielo.br/scielo.php?script=sci_serial&pid=0001-3765&lng=en&nrm=iso>. Acesso em: 23 jan. 2020.pt_BR
dc.identifier.doihttps://doi.org/10.1590/0001-3765202120180897pt_BR
Appears in Collections:DEAMB - Artigos publicados em periódicos

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