Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil

Detalhes bibliográficos
Autor(a) principal: Giasson,Elvio
Data de Publicação: 2006
Outros Autores: Clarke,Robin Thomas, Inda Junior,Alberto Vasconcellos, Merten,Gustavo Henrique, Tornquist,Carlos Gustavo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162006000300008
Resumo: Soil surveys are necessary sources of information for land use planning, but they are not always available. This study proposes the use of multiple logistic regressions on the prediction of occurrence of soil types based on reference areas. From a digitalized soil map and terrain parameters derived from the digital elevation model in ArcView environment, several sets of multiple logistic regressions were defined using statistical software Minitab, establishing relationship between explanatory terrain variables and soil types, using either the original legend or a simplified legend, and using or not stratification of the study area by drainage classes. Terrain parameters, such as elevation, distance to stream, flow accumulation, and topographic wetness index, were the variables that best explained soil distribution. Stratification by drainage classes did not have significant effect. Simplification of the original legend increased the accuracy of the method on predicting soil distribution.
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spelling Digital soil mapping using multiple logistic regression on terrain parameters in southern BrazilGISDEMsoil surveyterrain analysisSoil surveys are necessary sources of information for land use planning, but they are not always available. This study proposes the use of multiple logistic regressions on the prediction of occurrence of soil types based on reference areas. From a digitalized soil map and terrain parameters derived from the digital elevation model in ArcView environment, several sets of multiple logistic regressions were defined using statistical software Minitab, establishing relationship between explanatory terrain variables and soil types, using either the original legend or a simplified legend, and using or not stratification of the study area by drainage classes. Terrain parameters, such as elevation, distance to stream, flow accumulation, and topographic wetness index, were the variables that best explained soil distribution. Stratification by drainage classes did not have significant effect. Simplification of the original legend increased the accuracy of the method on predicting soil distribution.Escola Superior de Agricultura "Luiz de Queiroz"2006-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162006000300008Scientia Agricola v.63 n.3 2006reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/S0103-90162006000300008info:eu-repo/semantics/openAccessGiasson,ElvioClarke,Robin ThomasInda Junior,Alberto VasconcellosMerten,Gustavo HenriqueTornquist,Carlos Gustavoeng2006-06-26T00:00:00Zoai:scielo:S0103-90162006000300008Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2006-06-26T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil
title Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil
spellingShingle Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil
Giasson,Elvio
GIS
DEM
soil survey
terrain analysis
title_short Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil
title_full Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil
title_fullStr Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil
title_full_unstemmed Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil
title_sort Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil
author Giasson,Elvio
author_facet Giasson,Elvio
Clarke,Robin Thomas
Inda Junior,Alberto Vasconcellos
Merten,Gustavo Henrique
Tornquist,Carlos Gustavo
author_role author
author2 Clarke,Robin Thomas
Inda Junior,Alberto Vasconcellos
Merten,Gustavo Henrique
Tornquist,Carlos Gustavo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Giasson,Elvio
Clarke,Robin Thomas
Inda Junior,Alberto Vasconcellos
Merten,Gustavo Henrique
Tornquist,Carlos Gustavo
dc.subject.por.fl_str_mv GIS
DEM
soil survey
terrain analysis
topic GIS
DEM
soil survey
terrain analysis
description Soil surveys are necessary sources of information for land use planning, but they are not always available. This study proposes the use of multiple logistic regressions on the prediction of occurrence of soil types based on reference areas. From a digitalized soil map and terrain parameters derived from the digital elevation model in ArcView environment, several sets of multiple logistic regressions were defined using statistical software Minitab, establishing relationship between explanatory terrain variables and soil types, using either the original legend or a simplified legend, and using or not stratification of the study area by drainage classes. Terrain parameters, such as elevation, distance to stream, flow accumulation, and topographic wetness index, were the variables that best explained soil distribution. Stratification by drainage classes did not have significant effect. Simplification of the original legend increased the accuracy of the method on predicting soil distribution.
publishDate 2006
dc.date.none.fl_str_mv 2006-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162006000300008
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162006000300008
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0103-90162006000300008
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
dc.source.none.fl_str_mv Scientia Agricola v.63 n.3 2006
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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