Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil

Detalhes bibliográficos
Autor(a) principal: ROSA,MATEUS L.
Data de Publicação: 2021
Outros Autores: SOBREIRA,FREDERICO G., BARELLA,CESAR F.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Anais da Academia Brasileira de Ciências (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000101202
Resumo: Abstract This 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 verification 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.
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spelling Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazilnatural disasterslandslide susceptibility mapstatistical methodsinformation valueterritorial planningAbstract This 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 verification 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.Academia Brasileira de Ciências2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000101202Anais da Academia Brasileira de Ciências v.93 n.1 2021reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202120180897info:eu-repo/semantics/openAccessROSA,MATEUS L.SOBREIRA,FREDERICO G.BARELLA,CESAR F.eng2021-01-13T00:00:00Zoai:scielo:S0001-37652021000101202Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2021-01-13T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil
title Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil
spellingShingle Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil
ROSA,MATEUS L.
natural disasters
landslide susceptibility map
statistical methods
information value
territorial planning
title_short Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil
title_full Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil
title_fullStr Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil
title_full_unstemmed Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil
title_sort Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil
author ROSA,MATEUS L.
author_facet ROSA,MATEUS L.
SOBREIRA,FREDERICO G.
BARELLA,CESAR F.
author_role author
author2 SOBREIRA,FREDERICO G.
BARELLA,CESAR F.
author2_role author
author
dc.contributor.author.fl_str_mv ROSA,MATEUS L.
SOBREIRA,FREDERICO G.
BARELLA,CESAR F.
dc.subject.por.fl_str_mv natural disasters
landslide susceptibility map
statistical methods
information value
territorial planning
topic natural disasters
landslide susceptibility map
statistical methods
information value
territorial planning
description Abstract This 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 verification 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.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765202120180897
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dc.publisher.none.fl_str_mv Academia Brasileira de Ciências
publisher.none.fl_str_mv Academia Brasileira de Ciências
dc.source.none.fl_str_mv Anais da Academia Brasileira de Ciências v.93 n.1 2021
reponame:Anais da Academia Brasileira de Ciências (Online)
instname:Academia Brasileira de Ciências (ABC)
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instname_str Academia Brasileira de Ciências (ABC)
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