Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/58771
Título: Análise de discrepâncias entre vigor vegetativo e produtividade de grãos de milho com abordagem multisensor
Título(s) alternativo(s): Analysis of discrepancies between vegetative vigor and corn grain yield with a multisensor approach
Autores: Alves, Marcelo de Carvalho
Noetzold, Rafael
Araújo, José Sérgio de
Palavras-chave: Sensoriamento remoto
Agricultura de precisão
Sentinel-2
Landsat-8
Índices de vegetação
Remote sensing
Precision agriculture
Vegetation index
Data do documento: 12-Jan-2024
Editor: Universidade Federal de Lavras
Citação: SOUZA, G. C. Análise de discrepâncias entre vigor vegetativo e produtividade de grãos de milho com abordagem multisensor. 2023. 24 p. Dissertação (Mestrado em Engenharia Agrícola)–Universidade Federal de Lavras, Lavras, 2023.
Resumo: Imagery from sensors embedded in satellites enables low-cost crop analysis and has been the subject of correlation studies between vegetation indices and productivity. Vegetation indices obtained from orbital platforms and crop maps have been important tools in the context of popularizing precision agriculture. However, there are many factors that affect maize yields and the resulting harvest maps. As a result, correlations between vegetation indices and yields are not always obtained. This leaves a gap for methodologies to identify areas of non-correlation and investigate the possible causes in a targeted manner. The aim of this study was to use freely available satellite images, together with yield data from a maize harvester, to identify regions with and without a correlation between yields and vegetation indices. In areas with correlation, a linear model of yield as a function of NDVI was obtained. A map of discrepancies was calculated, in which most of the crop was correlated, with yields varying by around 2 ton ha−1 in relation to the model. Areas with discrepant yields were identified, both negatively and positively in relation to the model, enabling a localized investigation into the possible causes of the phenomenon and crop management.
URI: http://repositorio.ufla.br/jspui/handle/1/58771
Aparece nas coleções:Engenharia Agrícola - Mestrado (Dissertações)



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