Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do solo

Detalhes bibliográficos
Autor(a) principal: Freitas, Higor Machado de
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Manancial - Repositório Digital da UFSM
Texto Completo: http://repositorio.ufsm.br/handle/1/21998
Resumo: Soil sampling for the mapping of its properties can be performed by a variety of arrangements with different levels of complexity. Considering the importance of exchangeable soil cations for crops, it is necessary to describe their distribution in space and time in the different agroecosystems. Among the variety of sampling arrangements used in the digital mapping of exchangeable soil cations, the Regular grid sampling (R), the Spatial Coverage sampling (S) and the Latin Conditioning Hypercube sampling (cLHS) stand out. Therefore, the objective of this research is to test whether the performance of the cLHS sampling arrangement that uses environmental covariates, when compared to the regular grid and spatial coverage arrangements, will increase the accuracy in the digital mapping of exchangeable soil cations, carried out by two methods of spatial modeling (geostatistics and mixed linear model), in an area of grain cultivation under central pivot irrigation. The study area covers 160 hectares. For the predictions of the spatial distribution of the exchangeable cations of the soil, the three sampling arrangements, regular grid, spatial coverage and conditioned Latin hypercube were used. The spatial predictions made in the ArcMap® software were used, using Krigagem, and also, mixed linear model in the software R. For the geostatistics the sampling arrangement that presented better accuracy in the prediction of Al and K was the mesh. R, the lowest predictive performance was presented in the S grid. In the case of Ca, the sampling arrangement that had the highest performance was that of the R mesh and the lowest was of the cLHS mesh. Finally, for Mg, the best performance was the S mesh, and the lowest performance was the R mesh. The sampling arrangement that showed the best accuracy in the prediction of exchangeable soil cations using the mixed linear model was the cLHS mesh model. It was observed that the mesh S obtained a good predictive performance, while, the lowest performance was of the R mesh sampling arrangement. Thus, the Hipercubo Latino Conditioned sampling arrangement proved to be superior to the other tested arrangements.
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spelling Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do soloPerformance of different sample arrangements and models in the spacialization of soil exchangeable cationsMapeamento digital de solosAgricultura de precisãoPedometriaDigital soil mappingPrecision agriculturePedometryCNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLOSoil sampling for the mapping of its properties can be performed by a variety of arrangements with different levels of complexity. Considering the importance of exchangeable soil cations for crops, it is necessary to describe their distribution in space and time in the different agroecosystems. Among the variety of sampling arrangements used in the digital mapping of exchangeable soil cations, the Regular grid sampling (R), the Spatial Coverage sampling (S) and the Latin Conditioning Hypercube sampling (cLHS) stand out. Therefore, the objective of this research is to test whether the performance of the cLHS sampling arrangement that uses environmental covariates, when compared to the regular grid and spatial coverage arrangements, will increase the accuracy in the digital mapping of exchangeable soil cations, carried out by two methods of spatial modeling (geostatistics and mixed linear model), in an area of grain cultivation under central pivot irrigation. The study area covers 160 hectares. For the predictions of the spatial distribution of the exchangeable cations of the soil, the three sampling arrangements, regular grid, spatial coverage and conditioned Latin hypercube were used. The spatial predictions made in the ArcMap® software were used, using Krigagem, and also, mixed linear model in the software R. For the geostatistics the sampling arrangement that presented better accuracy in the prediction of Al and K was the mesh. R, the lowest predictive performance was presented in the S grid. In the case of Ca, the sampling arrangement that had the highest performance was that of the R mesh and the lowest was of the cLHS mesh. Finally, for Mg, the best performance was the S mesh, and the lowest performance was the R mesh. The sampling arrangement that showed the best accuracy in the prediction of exchangeable soil cations using the mixed linear model was the cLHS mesh model. It was observed that the mesh S obtained a good predictive performance, while, the lowest performance was of the R mesh sampling arrangement. Thus, the Hipercubo Latino Conditioned sampling arrangement proved to be superior to the other tested arrangements.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESA amostragem do solo para o mapeamento de suas propriedades pode ser realizada por uma variedade de arranjos com diferentes níveis de complexidade. Dada a importância dos cátions trocáveis do solo para a produção vegetal, faz-se necessária a descrição da sua distribuição no espaço e no tempo nos diferentes agroecossistemas. Dentre os diversos arranjos amostrais empregados no mapeamento digital de cátions trocáveis do solo destacam-se a amostragem de grade Regular (R), a amostragem de Cobertura Espacial (S) e a amostragem de Hipercubo Latino Condicionado (cLHS). Portanto, o objetivo do presente trabalho é testar se o desempenho do arranjo amostral cLHS que utiliza covariáveis ambientais, quando comparado aos arranjos de grade regular e de cobertura espacial, aumentará a acurácia no mapeamento digital de cátions trocáveis do solo, realizados por dois métodos de modelagem espacial, sendo eles, a geoestatística e o modelo linear misto, numa área de cultivo de grãos de 160 hectares sob irrigação por pivô central. Para as predições da distribuição espacial dos cátions trocáveis do solo, foram utilizados os três arranjos de amostragem (R, S e cLHS). A predição espaciai realizada pela krigagem foi desenvolvida no software ArcMap®, enquanto a predição pelo modelo linear misto foi desenvolvida no software R. Para a geoestatística o arranjo amostral que apresentou melhor acurácia na predição do Al e do K foi o da malha R, o menor desempenho preditivo foi apresentado na malha S. No caso do Ca, o arranjo amostral que teve maior desempenho foi o de malha R e o menor foi da malha cLHS. Por fim, para o Mg, o melhor desempenho foi o da malha S, e o menor desempenho foi da malha R. O arranjo amostral que apresentou melhor acurácia na predição dos cátions trocáveis do solo utilizando o modelo linear misto foi o da malha cLHS. Observou-se que a malha S obteve um bom desempenho preditivo, enquantoa malha R apresentou o menor desempenho preditivo. Assim, o arranjo amostral do Hipercubo Latino Condicionado mostrou-se superior aos demais arranjos testados.Universidade Federal de Santa MariaBrasilAgronomiaUFSMPrograma de Pós-Graduação em Ciência do SoloCentro de Ciências RuraisPedron, Fabrício de Araújohttp://lattes.cnpq.br/6868334304493274Schenato, Ricardo BergamoCancian, Luciano CamposFreitas, Higor Machado de2021-08-19T12:55:21Z2021-08-19T12:55:21Z2021-04-16info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://repositorio.ufsm.br/handle/1/21998porAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM2021-08-20T06:00:43Zoai:repositorio.ufsm.br:1/21998Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2021-08-20T06:00:43Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do solo
Performance of different sample arrangements and models in the spacialization of soil exchangeable cations
title Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do solo
spellingShingle Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do solo
Freitas, Higor Machado de
Mapeamento digital de solos
Agricultura de precisão
Pedometria
Digital soil mapping
Precision agriculture
Pedometry
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO
title_short Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do solo
title_full Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do solo
title_fullStr Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do solo
title_full_unstemmed Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do solo
title_sort Desempenho de diferentes arranjos amostrais e modelos na espacialização de cátions trocáveis do solo
author Freitas, Higor Machado de
author_facet Freitas, Higor Machado de
author_role author
dc.contributor.none.fl_str_mv Pedron, Fabrício de Araújo
http://lattes.cnpq.br/6868334304493274
Schenato, Ricardo Bergamo
Cancian, Luciano Campos
dc.contributor.author.fl_str_mv Freitas, Higor Machado de
dc.subject.por.fl_str_mv Mapeamento digital de solos
Agricultura de precisão
Pedometria
Digital soil mapping
Precision agriculture
Pedometry
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO
topic Mapeamento digital de solos
Agricultura de precisão
Pedometria
Digital soil mapping
Precision agriculture
Pedometry
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO
description Soil sampling for the mapping of its properties can be performed by a variety of arrangements with different levels of complexity. Considering the importance of exchangeable soil cations for crops, it is necessary to describe their distribution in space and time in the different agroecosystems. Among the variety of sampling arrangements used in the digital mapping of exchangeable soil cations, the Regular grid sampling (R), the Spatial Coverage sampling (S) and the Latin Conditioning Hypercube sampling (cLHS) stand out. Therefore, the objective of this research is to test whether the performance of the cLHS sampling arrangement that uses environmental covariates, when compared to the regular grid and spatial coverage arrangements, will increase the accuracy in the digital mapping of exchangeable soil cations, carried out by two methods of spatial modeling (geostatistics and mixed linear model), in an area of grain cultivation under central pivot irrigation. The study area covers 160 hectares. For the predictions of the spatial distribution of the exchangeable cations of the soil, the three sampling arrangements, regular grid, spatial coverage and conditioned Latin hypercube were used. The spatial predictions made in the ArcMap® software were used, using Krigagem, and also, mixed linear model in the software R. For the geostatistics the sampling arrangement that presented better accuracy in the prediction of Al and K was the mesh. R, the lowest predictive performance was presented in the S grid. In the case of Ca, the sampling arrangement that had the highest performance was that of the R mesh and the lowest was of the cLHS mesh. Finally, for Mg, the best performance was the S mesh, and the lowest performance was the R mesh. The sampling arrangement that showed the best accuracy in the prediction of exchangeable soil cations using the mixed linear model was the cLHS mesh model. It was observed that the mesh S obtained a good predictive performance, while, the lowest performance was of the R mesh sampling arrangement. Thus, the Hipercubo Latino Conditioned sampling arrangement proved to be superior to the other tested arrangements.
publishDate 2021
dc.date.none.fl_str_mv 2021-08-19T12:55:21Z
2021-08-19T12:55:21Z
2021-04-16
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://repositorio.ufsm.br/handle/1/21998
url http://repositorio.ufsm.br/handle/1/21998
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
Brasil
Agronomia
UFSM
Programa de Pós-Graduação em Ciência do Solo
Centro de Ciências Rurais
publisher.none.fl_str_mv Universidade Federal de Santa Maria
Brasil
Agronomia
UFSM
Programa de Pós-Graduação em Ciência do Solo
Centro de Ciências Rurais
dc.source.none.fl_str_mv reponame:Manancial - Repositório Digital da UFSM
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Manancial - Repositório Digital da UFSM
collection Manancial - Repositório Digital da UFSM
repository.name.fl_str_mv Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv atendimento.sib@ufsm.br||tedebc@gmail.com
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