The Use of Space-Temporal Geostatistics in the Prediction of Maximum Air Temperature

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Federal de Viçosa (UFV)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorInstituto Federal do Espírito Santos (IFES-
Autor(es): dc.creatorViana, Rosane Soares Moreira-
Autor(es): dc.creatorRodrigues, Gérson dos Santos-
Autor(es): dc.creatorMoreira, Demerval Soares-
Autor(es): dc.creatorLouzada, João Marcos-
Autor(es): dc.creatorRosa, Lidiane Maria Ferraz-
Data de aceite: dc.date.accessioned2025-08-21T18:50:26Z-
Data de disponibilização: dc.date.available2025-08-21T18:50:26Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2019-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.26848/rbgf.v12.1.p096-111-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/245848-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/245848-
Descrição: dc.descriptionStochastic processes of spatio-temporal nature consist of phenomenons that are characterized by spatial and temporal variability. Currently, it is one of the great growing areas with diverse applications in environmental, geographic, biological, epidemiological sciences, among others. Certainly, conventional statistical methods are not adequate to modeling self-correlated structures in space and time. In fact, there are still major challenges regarding the computational implementation of the geostatistical methodology for the analysis of space-time processes, with emphasis on the spacetime package of the R program used in this study. Thus, this work aims to apply the geostatistical methodology of covariance functions in order to infer about the maximum air temperature of the State of Minas Gerais from 1996 to 2016, aiming to contribute with challenges such as heating uncontrolled urbanization, scarcity of natural resources, epidemics and natural disasters. Using the data from 61 meteorological stations, the geostatistical space-time analysis was performed, in which the sum-metric covariance model was the most adequate, considering the criterion of the Mean Squared Error. Thus, it was possible to prepare maps of predictions of maximum air temperatures in the state of Minas Gerais through of ordinary kriging, assuming first order stationarity of the evaluated stochastic process. It can be observed that the models of space-time geostatistics have shown to be efficient in the space-time studies of maximum air temperatures.-
Descrição: dc.descriptionUniversidade Federal de Viçosa (UFV), MG-
Descrição: dc.descriptionDepartamento de Física Universidade Estadual Paulista (Unesp) Faculdade de Ciências, SP-
Descrição: dc.descriptionInstituto Federal do Espírito Santos (IFES, ES-
Descrição: dc.descriptionDepartamento de Física Universidade Estadual Paulista (Unesp) Faculdade de Ciências, SP-
Formato: dc.format96-111-
Idioma: dc.languagept_BR-
Relação: dc.relationRevista Brasileira de Geografia Fisica-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectCovariance-
Palavras-chave: dc.subjectOrdinary Kriging-
Palavras-chave: dc.subjectSpatial-temporal Data Modeling-
Palavras-chave: dc.subjectVariogram-
Título: dc.titleThe Use of Space-Temporal Geostatistics in the Prediction of Maximum Air Temperature-
Título: dc.titleO Uso da Geoestatística Espaço-Temporal na Predição da Temperatura Máxima do Ar-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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