Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas

Detalhes bibliográficos
Autor(a) principal: Pelegrino,Marcelo Henrique Procópio
Data de Publicação: 2016
Outros Autores: Silva,Sérgio Henrique Godinho, Menezes,Michele Duarte de, Silva,Elidiane da, Owens,Phillip Ray, Curi,Nilton
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência e Agrotecnologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542016000500534
Resumo: ABSTRACT Existing soil maps (legacy data) associated with digital mapping techniques are alternatives to obtain information at lower costs, however, tests are required to do it more efficiently. This study had as objectives to compare different methods to extract information from detailed scale soil maps using decision trees for mapping soil classes at two watersheds in Minas Gerais, validate these maps in the field and use the best method to extrapolate information to larger areas, also validating these maps of larger areas. Detailed soil maps of Vista Bela creek (VBW) and Marcela creek (MCW) watersheds were used as source of information. Seven methods to extract information from maps were compared: the whole polygon, eliminating 20 and 40 m from the polygon boundaries, and with buffers around the sampled points with radii of 25 m, 50 m, 75 m, and 100 m. The Classification and Regression Trees (CART) algorithm was employed to create decision trees and enable creation of soil maps. Accuracy was assessed through overall accuracy and kappa index. The best method was used to extrapolate information to larger areas and maps were validated. The best methods for VCW and MCW were, respectively, eliminating 20 m from polygon edges and buffer of 25 m of radii from points. Maps for larger areas were obtained using these methods. Removing uncertainty areas from legacy soil maps contribute to better modeling and prediction of soil classes. Information generated in this work allowed for validated extrapolation of soil maps for regions surrounding the watersheds.
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spelling Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areasDecision treespedologytropical soilsABSTRACT Existing soil maps (legacy data) associated with digital mapping techniques are alternatives to obtain information at lower costs, however, tests are required to do it more efficiently. This study had as objectives to compare different methods to extract information from detailed scale soil maps using decision trees for mapping soil classes at two watersheds in Minas Gerais, validate these maps in the field and use the best method to extrapolate information to larger areas, also validating these maps of larger areas. Detailed soil maps of Vista Bela creek (VBW) and Marcela creek (MCW) watersheds were used as source of information. Seven methods to extract information from maps were compared: the whole polygon, eliminating 20 and 40 m from the polygon boundaries, and with buffers around the sampled points with radii of 25 m, 50 m, 75 m, and 100 m. The Classification and Regression Trees (CART) algorithm was employed to create decision trees and enable creation of soil maps. Accuracy was assessed through overall accuracy and kappa index. The best method was used to extrapolate information to larger areas and maps were validated. The best methods for VCW and MCW were, respectively, eliminating 20 m from polygon edges and buffer of 25 m of radii from points. Maps for larger areas were obtained using these methods. Removing uncertainty areas from legacy soil maps contribute to better modeling and prediction of soil classes. Information generated in this work allowed for validated extrapolation of soil maps for regions surrounding the watersheds.Editora da UFLA2016-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542016000500534Ciência e Agrotecnologia v.40 n.5 2016reponame:Ciência e Agrotecnologia (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLA10.1590/1413-70542016405011416info:eu-repo/semantics/openAccessPelegrino,Marcelo Henrique ProcópioSilva,Sérgio Henrique GodinhoMenezes,Michele Duarte deSilva,Elidiane daOwens,Phillip RayCuri,Niltoneng2016-09-19T00:00:00Zoai:scielo:S1413-70542016000500534Revistahttp://www.scielo.br/cagroPUBhttps://old.scielo.br/oai/scielo-oai.php||renpaiva@dbi.ufla.br|| editora@editora.ufla.br1981-18291413-7054opendoar:2022-11-22T16:31:28.964144Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas
title Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas
spellingShingle Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas
Pelegrino,Marcelo Henrique Procópio
Decision trees
pedology
tropical soils
title_short Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas
title_full Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas
title_fullStr Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas
title_full_unstemmed Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas
title_sort Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas
author Pelegrino,Marcelo Henrique Procópio
author_facet Pelegrino,Marcelo Henrique Procópio
Silva,Sérgio Henrique Godinho
Menezes,Michele Duarte de
Silva,Elidiane da
Owens,Phillip Ray
Curi,Nilton
author_role author
author2 Silva,Sérgio Henrique Godinho
Menezes,Michele Duarte de
Silva,Elidiane da
Owens,Phillip Ray
Curi,Nilton
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Pelegrino,Marcelo Henrique Procópio
Silva,Sérgio Henrique Godinho
Menezes,Michele Duarte de
Silva,Elidiane da
Owens,Phillip Ray
Curi,Nilton
dc.subject.por.fl_str_mv Decision trees
pedology
tropical soils
topic Decision trees
pedology
tropical soils
description ABSTRACT Existing soil maps (legacy data) associated with digital mapping techniques are alternatives to obtain information at lower costs, however, tests are required to do it more efficiently. This study had as objectives to compare different methods to extract information from detailed scale soil maps using decision trees for mapping soil classes at two watersheds in Minas Gerais, validate these maps in the field and use the best method to extrapolate information to larger areas, also validating these maps of larger areas. Detailed soil maps of Vista Bela creek (VBW) and Marcela creek (MCW) watersheds were used as source of information. Seven methods to extract information from maps were compared: the whole polygon, eliminating 20 and 40 m from the polygon boundaries, and with buffers around the sampled points with radii of 25 m, 50 m, 75 m, and 100 m. The Classification and Regression Trees (CART) algorithm was employed to create decision trees and enable creation of soil maps. Accuracy was assessed through overall accuracy and kappa index. The best method was used to extrapolate information to larger areas and maps were validated. The best methods for VCW and MCW were, respectively, eliminating 20 m from polygon edges and buffer of 25 m of radii from points. Maps for larger areas were obtained using these methods. Removing uncertainty areas from legacy soil maps contribute to better modeling and prediction of soil classes. Information generated in this work allowed for validated extrapolation of soil maps for regions surrounding the watersheds.
publishDate 2016
dc.date.none.fl_str_mv 2016-10-01
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=S1413-70542016000500534
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542016000500534
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1413-70542016405011416
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 Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv Ciência e Agrotecnologia v.40 n.5 2016
reponame:Ciência e Agrotecnologia (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
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reponame_str Ciência e Agrotecnologia (Online)
collection Ciência e Agrotecnologia (Online)
repository.name.fl_str_mv Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv ||renpaiva@dbi.ufla.br|| editora@editora.ufla.br
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