Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agriculture

Detalhes bibliográficos
Autor(a) principal: Malvezi, Katiaíres Evangelista Delpin Malvezi
Data de Publicação: 2020
Outros Autores: Sibaldelli, Rubson Natal Ribeiro, Pereira Neto, Osvaldo Coelho, Moraes, Larissa Alexandra Cardoso, Saab, Otávio Jorge Grigoli Abi, Moreira, Adônis
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Semina. Ciências Agrárias (Online)
Texto Completo: https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/37810
Resumo: Geostatistics is the main technique used to efficiently determine spatial variability. The objective of this study was to evaluate the applicability of the principles of geostatistics in the use of semivariograms elaborated through parametric monitoring and the assumption automatically made by software in the map preparation of soil chemical attributes. Available phosphorus (P), potassium (K+), calcium (Ca2+), magnesium (Mg2+), base saturation (V%), sulfur (SO42-), and pH were compared from the soil chemical attributes of 60 samples of a Typical Oxisol collected at a 0-20 cm depth and a distance of 300 m between the points. The maps were compared using error matrices and evaluated by the Global Accuracy (GA), Kappa (K), and Tau (T) indexes. The parameterized semivariograms and the automatic software model assumption did not present a high coincidence for the available P and Mg2+, making it necessary to adjust the semivariogram variables in the spatial analysis as a function of the outliers, sum of squares of residuals, coefficient of determination, and cross-validation to better represent the variability of the data and thus avoid distortions of the sample point range that would affect the adequate representativeness of the attributes, which contrasts with the automatic model generated by the software.
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spelling Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agricultureDissimilaridade de mapas gerados na geoestatística parametrizada e seu pressuposto modelo automático de software na agricultura de precisãoSpatial analysisSoil chemical attributesMapsSemivariogram.Análise espacialAtributos químicos do soloMapas de isolinhasSemivariograma.Geostatistics is the main technique used to efficiently determine spatial variability. The objective of this study was to evaluate the applicability of the principles of geostatistics in the use of semivariograms elaborated through parametric monitoring and the assumption automatically made by software in the map preparation of soil chemical attributes. Available phosphorus (P), potassium (K+), calcium (Ca2+), magnesium (Mg2+), base saturation (V%), sulfur (SO42-), and pH were compared from the soil chemical attributes of 60 samples of a Typical Oxisol collected at a 0-20 cm depth and a distance of 300 m between the points. The maps were compared using error matrices and evaluated by the Global Accuracy (GA), Kappa (K), and Tau (T) indexes. The parameterized semivariograms and the automatic software model assumption did not present a high coincidence for the available P and Mg2+, making it necessary to adjust the semivariogram variables in the spatial analysis as a function of the outliers, sum of squares of residuals, coefficient of determination, and cross-validation to better represent the variability of the data and thus avoid distortions of the sample point range that would affect the adequate representativeness of the attributes, which contrasts with the automatic model generated by the software.A geoestatística é uma das principais técnicas utilizadas para determinar a variabilidade espacial dos atributos do solo. O objetivo deste trabalho foi comparar o uso de semivariogramas elaborados através do acompanhamento paramétrico da geoestatística e seu pressuposto modelo realizado automaticamente por software na confecção dos mapas de fertilidade do solo. Foram comparados os mapas dos valores de pH, fósforo (P), potássio (K+), cálcio (Ca2+), magnésio (Mg2+), enxofre (SO42-) e saturação por bases (V%), provenientes de 60 amostras coletadas de área de Latossolo Vermelho Distrófico coletadas na profundidade 0-20 cm e malha de 300 m de distância entre os pontos. Os mapas foram comparados por matrizes de erro e avaliadas pelos índices Exatidão Global, Kappa e Tau. O uso de semivariogramas parametrizados e seu pressuposto modelo automático do software não apresentaram alta coincidência para os teores de P disponível e Mg2+, sendo necessário ajustes das variáveis dos semivariogramas na análise espacial em função dos outliers, soma dos quadrados dos resíduos, coeficiente de determinação e validação cruzada para melhor representação da variabilidade dos dados e assim, evitar distorções do alcance do ponto amostral para uma boa representatividade dos atributos estudados, o que contraria o modelo automático gerado pelo software.UEL2020-11-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPesquisa de Campoapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/3781010.5433/1679-0359.2020v41n6Supl2p2873Semina: Ciências Agrárias; Vol. 41 No. 6Supl2 (2020); 2873-2882Semina: Ciências Agrárias; v. 41 n. 6Supl2 (2020); 2873-28821679-03591676-546Xreponame:Semina. Ciências Agrárias (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELenghttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/37810/28245Copyright (c) 2020 Semina: Ciências Agráriashttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessMalvezi, Katiaíres Evangelista Delpin MalveziSibaldelli, Rubson Natal RibeiroPereira Neto, Osvaldo CoelhoMoraes, Larissa Alexandra CardosoSaab, Otávio Jorge Grigoli AbiMoreira, Adônis2022-10-04T16:02:36Zoai:ojs.pkp.sfu.ca:article/37810Revistahttp://www.uel.br/revistas/uel/index.php/semagrariasPUBhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/oaisemina.agrarias@uel.br1679-03591676-546Xopendoar:2022-10-04T16:02:36Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)false
dc.title.none.fl_str_mv Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agriculture
Dissimilaridade de mapas gerados na geoestatística parametrizada e seu pressuposto modelo automático de software na agricultura de precisão
title Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agriculture
spellingShingle Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agriculture
Malvezi, Katiaíres Evangelista Delpin Malvezi
Spatial analysis
Soil chemical attributes
Maps
Semivariogram.
Análise espacial
Atributos químicos do solo
Mapas de isolinhas
Semivariograma.
title_short Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agriculture
title_full Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agriculture
title_fullStr Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agriculture
title_full_unstemmed Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agriculture
title_sort Dissimilarity of parameterized maps generated in geostatistics and the assumption of an automatic software model in precision agriculture
author Malvezi, Katiaíres Evangelista Delpin Malvezi
author_facet Malvezi, Katiaíres Evangelista Delpin Malvezi
Sibaldelli, Rubson Natal Ribeiro
Pereira Neto, Osvaldo Coelho
Moraes, Larissa Alexandra Cardoso
Saab, Otávio Jorge Grigoli Abi
Moreira, Adônis
author_role author
author2 Sibaldelli, Rubson Natal Ribeiro
Pereira Neto, Osvaldo Coelho
Moraes, Larissa Alexandra Cardoso
Saab, Otávio Jorge Grigoli Abi
Moreira, Adônis
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Malvezi, Katiaíres Evangelista Delpin Malvezi
Sibaldelli, Rubson Natal Ribeiro
Pereira Neto, Osvaldo Coelho
Moraes, Larissa Alexandra Cardoso
Saab, Otávio Jorge Grigoli Abi
Moreira, Adônis
dc.subject.por.fl_str_mv Spatial analysis
Soil chemical attributes
Maps
Semivariogram.
Análise espacial
Atributos químicos do solo
Mapas de isolinhas
Semivariograma.
topic Spatial analysis
Soil chemical attributes
Maps
Semivariogram.
Análise espacial
Atributos químicos do solo
Mapas de isolinhas
Semivariograma.
description Geostatistics is the main technique used to efficiently determine spatial variability. The objective of this study was to evaluate the applicability of the principles of geostatistics in the use of semivariograms elaborated through parametric monitoring and the assumption automatically made by software in the map preparation of soil chemical attributes. Available phosphorus (P), potassium (K+), calcium (Ca2+), magnesium (Mg2+), base saturation (V%), sulfur (SO42-), and pH were compared from the soil chemical attributes of 60 samples of a Typical Oxisol collected at a 0-20 cm depth and a distance of 300 m between the points. The maps were compared using error matrices and evaluated by the Global Accuracy (GA), Kappa (K), and Tau (T) indexes. The parameterized semivariograms and the automatic software model assumption did not present a high coincidence for the available P and Mg2+, making it necessary to adjust the semivariogram variables in the spatial analysis as a function of the outliers, sum of squares of residuals, coefficient of determination, and cross-validation to better represent the variability of the data and thus avoid distortions of the sample point range that would affect the adequate representativeness of the attributes, which contrasts with the automatic model generated by the software.
publishDate 2020
dc.date.none.fl_str_mv 2020-11-06
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Pesquisa de Campo
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/37810
10.5433/1679-0359.2020v41n6Supl2p2873
url https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/37810
identifier_str_mv 10.5433/1679-0359.2020v41n6Supl2p2873
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/37810/28245
dc.rights.driver.fl_str_mv Copyright (c) 2020 Semina: Ciências Agrárias
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Semina: Ciências Agrárias
http://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv UEL
publisher.none.fl_str_mv UEL
dc.source.none.fl_str_mv Semina: Ciências Agrárias; Vol. 41 No. 6Supl2 (2020); 2873-2882
Semina: Ciências Agrárias; v. 41 n. 6Supl2 (2020); 2873-2882
1679-0359
1676-546X
reponame:Semina. Ciências Agrárias (Online)
instname:Universidade Estadual de Londrina (UEL)
instacron:UEL
instname_str Universidade Estadual de Londrina (UEL)
instacron_str UEL
institution UEL
reponame_str Semina. Ciências Agrárias (Online)
collection Semina. Ciências Agrárias (Online)
repository.name.fl_str_mv Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)
repository.mail.fl_str_mv semina.agrarias@uel.br
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