Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , |
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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Ciência e Agrotecnologia (Online) |
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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 |
institution |
UFLA |
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 |
_version_ |
1799874970300448768 |