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Caracterização dinâmica da evolução de índice de vegetação na cultura do milho
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Advisor(s)
Abstract(s)
A inovação tecnológica é uma constante na agricultura de precisão e com ela vem
uma necessidade de experimentação e confirmação por parte destas. Dentro desta panóplia
de tecnologias, os dados fornecidos pelos sensores de deteção remota juntamente com outras
informações, como por exemplo dados meteorológicos, permitem fornecer, ao empresário
agrícola, uma alternativa aprimorada e muito mais viável em relação à observação in situ e
assim tomar uma decisão mais consciente e sustentável.
O Programa Espacial Europeu (ESA), entre outros, através do satélite Sentinel-2,
fornece estes dados multiespectrais de forma gratuita, mas nem sempre são de fácil
manipulação tornando o processo de análise moroso. Programas como o GranularLink,
disponibilizam e manipulam dados/informação atempadamente, proporcionando ao
empresário agrícola conhecimento que lhe permita tomar as melhores decisões.
Esta dissertação teve como objetivo a comparação e avaliação de índices vegetativos,
nomeadamente NDVI (Normalized Difference Vegetation Index), NDMI (Normalized
Difference Moisture Index) ou NDRE (Normalized Difference of Red Edge), calculados a
partir de imagens obtidas diretamente dos programas de observação da terra versus
plataformas. Este objetivo foi alcançado através da caraterização da evolução destes índices
de vegetação na cultura do milho implementada na Parcela Grande (Pivot) da empresa
Sociedade Agro-Florestal CampoDobrado, localizada em Vale de Figueira (Santarém)
durante o ano de 2021.
Foram encontradas diferenças ao nível da saturação, entre o NDVI e NDRE, em fases
mais tardias da cultura e na correlação com o NDMI, em que o NDRE não satura tanto e
obteve uma correlação superior. A variabilidade espacial, encontrada na parte direita do
pivot, está de acordo com a forte relação da produtividade com os valores obtidos de NDVI
e NDRE. A utilização da aplicação Granular Link, para o processamento e análise de
imagens, evidenciou bastantes benefícios para o agricultor em relação ao método
“tradicional” (via Sentinel-2) sendo a rapidez e facilidade de obtenção de imagens umas das
principais vantagens. No entanto, caso seja necessária uma maior manipulação de dados,
neste momento, apenas é possível através do download direto dessas imagens.
Technological innovation is a constant in precision agriculture and with it comes a need for experimentation and confirmation. Within this panoply of technologies, the data provided by remote sensing sensors together with other information, such as meteorological data, makes it possible to provide the agricultural entrepreneur with an improved and much more viable alternative to in situ observation and thus make a more conscious and sustainable decision. The European Space Programme (ESA), among others, through the Sentinel-2 satellite, provides this multispectral data free of charge, but it isn`t always easy to manipulate, making the analysis process time-consuming. Programmes such as GranularLink provide and manipulate data/information in a timely manner, giving agricultural entrepreneurs the knowledge to make the best decisions. The aim of this dissertation was to compare and evaluate vegetation indices, namely NDVI (Normalised Difference Vegetation Index), NDMI (Normalised Difference Moisture Index) or NDRE (Normalised Difference of Red Edge), calculated from images obtained directly from earth observation programmes versus platforms. This objective was achieved by characterising the evolution of these vegetation indices in the maize crop implemented in the Large Plot (Pivot) of the company Sociedade Agro-Florestal CampoDobrado, located in Vale de Figueira (Santarém) during 2021. Differences were found in the level of saturation between NDVI and NDRE at later stages of the crop and in the correlation with NDMI, where NDRE did not saturate as much and obtained a higher correlation. The spatial variability found in the right part of the pivot is in line with the strong relationship between productivity and the values obtained for NDVI and NDRE. The use of the Granular Link application for processing and analysing images has shown many benefits for farmers compared to the "traditional" method (via Sentinel-2), with the speed and ease of obtaining images being one of the main advantages. However, if further data manipulation is required, which, for the time being, is only possible by directly downloading these images.
Technological innovation is a constant in precision agriculture and with it comes a need for experimentation and confirmation. Within this panoply of technologies, the data provided by remote sensing sensors together with other information, such as meteorological data, makes it possible to provide the agricultural entrepreneur with an improved and much more viable alternative to in situ observation and thus make a more conscious and sustainable decision. The European Space Programme (ESA), among others, through the Sentinel-2 satellite, provides this multispectral data free of charge, but it isn`t always easy to manipulate, making the analysis process time-consuming. Programmes such as GranularLink provide and manipulate data/information in a timely manner, giving agricultural entrepreneurs the knowledge to make the best decisions. The aim of this dissertation was to compare and evaluate vegetation indices, namely NDVI (Normalised Difference Vegetation Index), NDMI (Normalised Difference Moisture Index) or NDRE (Normalised Difference of Red Edge), calculated from images obtained directly from earth observation programmes versus platforms. This objective was achieved by characterising the evolution of these vegetation indices in the maize crop implemented in the Large Plot (Pivot) of the company Sociedade Agro-Florestal CampoDobrado, located in Vale de Figueira (Santarém) during 2021. Differences were found in the level of saturation between NDVI and NDRE at later stages of the crop and in the correlation with NDMI, where NDRE did not saturate as much and obtained a higher correlation. The spatial variability found in the right part of the pivot is in line with the strong relationship between productivity and the values obtained for NDVI and NDRE. The use of the Granular Link application for processing and analysing images has shown many benefits for farmers compared to the "traditional" method (via Sentinel-2), with the speed and ease of obtaining images being one of the main advantages. However, if further data manipulation is required, which, for the time being, is only possible by directly downloading these images.
Description
Dissertação de Mestrado na área da Engenharia Agronómica, apresentada na Escola Superior Agrária de Santarém
Keywords
Zea mays Milho Aplicação de computador NDMI NDRE NDVI produtividade yield Ribatejo
Citation
Neves, Gonçalo Filipe Severino Ferreira das (2024). Caracterização dinâmica da evolução de índice de vegetação na cultura do milho. Dissertação apresentada para obtenção do grau de Mestre na área de Engenharia Agronómica, na Escola Superior Agrária de Santarém