Spatial distribution of climatic variables in Tocantins State, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/40133 |
Resumo: | The recognition of spatial distribution of climatic variables is essential for planning land use and occupation. This is especially relevant in regions where the agricultural frontier is expanding, as it is the case of Tocantins State, Brazil. One of the tools widely used for spatialization of environmental variables is geostatistics, which allows the identification of the spatial dependence of these variables. In this context, this study evaluates the performance of geostatistical interpolators ordinary kriging (OK) and cokriging (CK) by adjusting different semivariogram models, and the subsequent spatialization of the variables mean air temperature, insolation, air relative humidity, and potential evapotranspiration for Tocantins State. The main results and conclusions were: i) variogram analysis is essential to improve the mapping results of each variable; ii) cross-validation showed acceptable errors, indicating reliability of results; (iii) the OK outperformed CK, which can be explained by the good spatial dependence structure presented by the primary variable; and iv) the maps produced can corroborate the management of natural resources and land use planning in Tocantins State. |
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Spatial distribution of climatic variables in Tocantins State, BrazilDistribuição espacial de variáveis climáticas no Estado do TocantinsClimatic variablesAnálise variográficaGestão de recursos naturaisUso do solo - PlanejamentoVariáveis climáticasVariographic analysisNatural resource managementLand use - PlanningThe recognition of spatial distribution of climatic variables is essential for planning land use and occupation. This is especially relevant in regions where the agricultural frontier is expanding, as it is the case of Tocantins State, Brazil. One of the tools widely used for spatialization of environmental variables is geostatistics, which allows the identification of the spatial dependence of these variables. In this context, this study evaluates the performance of geostatistical interpolators ordinary kriging (OK) and cokriging (CK) by adjusting different semivariogram models, and the subsequent spatialization of the variables mean air temperature, insolation, air relative humidity, and potential evapotranspiration for Tocantins State. The main results and conclusions were: i) variogram analysis is essential to improve the mapping results of each variable; ii) cross-validation showed acceptable errors, indicating reliability of results; (iii) the OK outperformed CK, which can be explained by the good spatial dependence structure presented by the primary variable; and iv) the maps produced can corroborate the management of natural resources and land use planning in Tocantins State.O reconhecimento da distribuição espacial de variáveis climáticas é essencial para o planejamento do uso e da ocupação do solo. Isto é especialmente relevante em regiões de expansão da fronteira agrícola, como é o caso do Estado do Tocantins. Uma das ferramentas amplamente empregadas na espacialização de variáveis ambientais é a geoestatística, que possibilita a identificação da dependência espacial dessas variáveis. Nesse contexto, objetivou-se avaliar o desempenho dos interpoladores geoestatísticos krigagem ordinária (OK) e co-krigagem (CK), por meio do ajuste de diferentes modelos de semivariograma, e a posterior espacialização das variáveis temperatura média do ar, insolação, umidade relativa do ar e evapotranspiração potencial mensais para o Estado do Tocantins. Os principais resultados e conclusões foram: i) a análise variográfica é essencial para melhorar os resultados do mapeamento de cada variável; ii) a validação cruzada mostrou erros aceitáveis, indicando confiabilidade dos resultados; iii) o desempenho da OK sobressaiu-se ao da CK, o que pode ser explicado pela boa estrutura de dependência espacial apresentada pela variável primária, e iv) os mapas produzidos podem corroborar a gestão de recursos naturais e o planejamento do uso do solo no Estado do Tocantins.Universidade Estadual Paulista2020-04-17T12:06:41Z2020-04-17T12:06:41Z2019info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfÁVILA, L. F. et al. Spatial distribution of climatic variables in Tocantins State, Brazil. Científica, Jaboticabal, v. 47, n. 3, p. 269-277, 2019.http://repositorio.ufla.br/jspui/handle/1/40133Científicareponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessÁvila, Léo FernandesCassalho, FelícioViola, Marcelo RibeiroBeskow, SamuelCoelho, GilbertoNardes, Kleudson da Silvaeng2023-05-02T19:11:46Zoai:localhost:1/40133Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-02T19:11:46Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Spatial distribution of climatic variables in Tocantins State, Brazil Distribuição espacial de variáveis climáticas no Estado do Tocantins |
title |
Spatial distribution of climatic variables in Tocantins State, Brazil |
spellingShingle |
Spatial distribution of climatic variables in Tocantins State, Brazil Ávila, Léo Fernandes Climatic variables Análise variográfica Gestão de recursos naturais Uso do solo - Planejamento Variáveis climáticas Variographic analysis Natural resource management Land use - Planning |
title_short |
Spatial distribution of climatic variables in Tocantins State, Brazil |
title_full |
Spatial distribution of climatic variables in Tocantins State, Brazil |
title_fullStr |
Spatial distribution of climatic variables in Tocantins State, Brazil |
title_full_unstemmed |
Spatial distribution of climatic variables in Tocantins State, Brazil |
title_sort |
Spatial distribution of climatic variables in Tocantins State, Brazil |
author |
Ávila, Léo Fernandes |
author_facet |
Ávila, Léo Fernandes Cassalho, Felício Viola, Marcelo Ribeiro Beskow, Samuel Coelho, Gilberto Nardes, Kleudson da Silva |
author_role |
author |
author2 |
Cassalho, Felício Viola, Marcelo Ribeiro Beskow, Samuel Coelho, Gilberto Nardes, Kleudson da Silva |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Ávila, Léo Fernandes Cassalho, Felício Viola, Marcelo Ribeiro Beskow, Samuel Coelho, Gilberto Nardes, Kleudson da Silva |
dc.subject.por.fl_str_mv |
Climatic variables Análise variográfica Gestão de recursos naturais Uso do solo - Planejamento Variáveis climáticas Variographic analysis Natural resource management Land use - Planning |
topic |
Climatic variables Análise variográfica Gestão de recursos naturais Uso do solo - Planejamento Variáveis climáticas Variographic analysis Natural resource management Land use - Planning |
description |
The recognition of spatial distribution of climatic variables is essential for planning land use and occupation. This is especially relevant in regions where the agricultural frontier is expanding, as it is the case of Tocantins State, Brazil. One of the tools widely used for spatialization of environmental variables is geostatistics, which allows the identification of the spatial dependence of these variables. In this context, this study evaluates the performance of geostatistical interpolators ordinary kriging (OK) and cokriging (CK) by adjusting different semivariogram models, and the subsequent spatialization of the variables mean air temperature, insolation, air relative humidity, and potential evapotranspiration for Tocantins State. The main results and conclusions were: i) variogram analysis is essential to improve the mapping results of each variable; ii) cross-validation showed acceptable errors, indicating reliability of results; (iii) the OK outperformed CK, which can be explained by the good spatial dependence structure presented by the primary variable; and iv) the maps produced can corroborate the management of natural resources and land use planning in Tocantins State. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 2020-04-17T12:06:41Z 2020-04-17T12:06:41Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
ÁVILA, L. F. et al. Spatial distribution of climatic variables in Tocantins State, Brazil. Científica, Jaboticabal, v. 47, n. 3, p. 269-277, 2019. http://repositorio.ufla.br/jspui/handle/1/40133 |
identifier_str_mv |
ÁVILA, L. F. et al. Spatial distribution of climatic variables in Tocantins State, Brazil. Científica, Jaboticabal, v. 47, n. 3, p. 269-277, 2019. |
url |
http://repositorio.ufla.br/jspui/handle/1/40133 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual Paulista |
publisher.none.fl_str_mv |
Universidade Estadual Paulista |
dc.source.none.fl_str_mv |
Científica reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1815439315883261952 |