Detalhes bibliográficos
| Ano de defesa: |
2024 |
| Autor(a) principal: |
Lima, Gabriella Santos Arruda de
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| Orientador(a): |
Ferreira, Manuel Eduardo
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| Banca de defesa: |
Ferreira , Manuel Eduardo,
Barreira, Sybelle,
Ruiz, Luis Fernando Chimelo,
Ferreira Júnior, Laerte Guimarães,
Bueno, Guilherme Taitson |
| Tipo de documento: |
Tese
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
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| Programa de Pós-Graduação: |
Programa de Pós-graduação em Geografia (IESA)
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| Departamento: |
Instituto de Estudos Socioambientais - IESA (RMG)
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/13542
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Resumo: |
In recent years, Unmanned Aerial Vehicles (UAVs), identified here by the acronym UAV, for Unmanned Aerial Vehicle, have rapidly advanced remote sensing systems, allowing for effective assessment of agricultural crops and natural areas through the processing and integration of field data and various sensors embedded in UAVs. This study addresses the scarcity of biomass and carbon estimates in integrated livestock and crop systems (iLP) and highlights the use of onboard sensors of unmanned aerial vehicles (UAVs) as an efficient and cost-effective method for acquiring precise remote sensing data. In this thesis (comprised of three articles), the first research was conducted in an experimental iLP area of Embrapa Rice and Bean, in the core area of the Goiás Cerrado, employing high-resolution multispectral aerial images to estimate the relationship between vegetation indices (VIs) and carbon stock in an upland rice field intercropped with Brachiaria, a species of exotic grass from the Brazilian Cerrado ecosystem. The results indicated that VIs incorporating near-infrared (NIR) exhibited a stronger correlation with biomass than those using only visible band information. Regression models successfully predicted biomass and carbon stock at different stages of the iLP cycle. Maps were generated showing the spatial and temporal distribution of biomass, emphasizing the advantages of using drones and multispectral sensors in this type of analysis. The second study organized in this research, also conducted in the company's experimental area in Goiás, explored the estimation of evapotranspiration (ET) in different crops and soil coverages through multispectral images captured by drones. The method employed - SAFER (Simple Algorithm for Evapotranspiration Retrieving) - showed good agreement for ET between drone and satellite data, highlighting its applicability and flexibility, without depending on satellite images affected by clouds or monitoring towers in the field. The study highlights the importance of integrated agricultural practices to better manage water resources and minimize negative impacts on the Cerrado's hydrological system. Lastly, the third study investigated the use of multispectral sensors onboard UAVs to monitor nitrogen status in agricultural crops, specifically in irrigated rice cultivation. The results demonstrated that aerial sensors performed well in estimating agronomic parameters related to nitrogen status, such as total above-ground biomass, leaf nitrogen content, and leaf area index, at different phenological stages of the rice cycle. This method shows promise in overcoming the limitations of satellite cloud cover and providing greater coverage with shorter operating times, compared to field optical sensors (non-imaging). These studies highlight the relevance and effectiveness of using drones and multispectral sensors for various agricultural applications, ranging from carbon and biomass estimation in integrated systems to monitoring evapotranspiration and nutrient status in specific crops, thereby contributing to a more sustainable and efficient management of the natural resources of the Cerrado. |
