Time series analysis of the enhanced vegetation index to detect coffee crop development under different irrigation systems

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorSilva, Pedro A. de Azevedo-
Autor(es): dc.creatorAlves, Marcelo de Carvalho-
Autor(es): dc.creatorSáfadi, Thelma-
Autor(es): dc.creatorPozza, Edson A.-
Data de aceite: dc.date.accessioned2026-02-09T11:35:05Z-
Data de disponibilização: dc.date.available2026-02-09T11:35:05Z-
Data de envio: dc.date.issued2022-04-07-
Data de envio: dc.date.issued2022-04-07-
Data de envio: dc.date.issued2021-03-02-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/49707-
Fonte completa do material: dc.identifierhttps://doi.org/10.1117/1.JRS.15.014511-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1142900-
Descrição: dc.descriptionThe coffee crop spectral behavior identification throughout its cycle can contribute to its development monitoring under pest incidence. We aim to identify coffee development through time signatures of enhanced vegetation index (EVI), as well as to evaluate the use of seasonal autoregressive integrated moving average (SARIMA) models to identify coffee trees spectrum-time patterns under different irrigation management and design future scenarios. Three coffee fields were selected under different irrigation systems, whose EVI data of 8 years were obtained from the moderate resolution image spectroradiometer sensor. Each coffee crop model was subjected to residual autocorrelation test and classified according to information criteria, while its accuracy was assessed by means of prediction error measures and agreement index. The estimated and observed EVI values were similar, even for the predicted year. However, in agricultural years during which coffee diseases occurred, the crops showed vegetative vigor below the expected. We concluded that SARIMA models enabled the establishment of a reliable spectral signature expected for coffee crop, which could help with crop management defining, regardless of the irrigation system adopted. Based on the evaluation of divergence between expected and observed spectral signatures, early signs of coffee underdevelopment were detected, which could reduce economic loss risks on its commercial chain.-
Idioma: dc.languageen-
Publicador: dc.publisherSociety of Photo-Optical Instrumentation Engineers-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceJournal of Applied Remote Sensing-
Palavras-chave: dc.subjectModerate resolution image spectroradiometer-
Palavras-chave: dc.subjectVegetation index-
Palavras-chave: dc.subjectSeasonal autoregressive integrated moving average-
Palavras-chave: dc.subjectForecasting-
Palavras-chave: dc.subjectEspectrradiômetro de imagem de resolução moderada-
Palavras-chave: dc.subjectÍndice de vegetação-
Palavras-chave: dc.subjectMédia móvel integrada autoregressiva sazonal-
Título: dc.titleTime series analysis of the enhanced vegetation index to detect coffee crop development under different irrigation systems-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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