Publicação
Multispectral imaging applied to precision agriculture
| Resumo: | The growing challenges of food demand, climate variability, and resource scarcity have highlighted the need for innovative technological solutions in agriculture. This work presents a software platform for the analysis of multispectral images of agricultural fields for Precision Agriculture, with a focus on improving crop monitoring and resource management. The proposed platform integrates data collected from Unmanned Aerial Vehicles (UAVs) equipped with multispectral sensors to assess vegetation health using spectral vegetation indices (VIs), such as NDVI, SAVI, GNDVI, and NDRE. These indices are computed automatically within a user-friendly desktop application, allowing farmers to analyse plant growth, identify stress conditions, and make informed management decisions. Experimental validation employing a publicly available multispectral dataset demonstrated the platform’s capacity to identify variations in crop vigour and chlorophyll content across various growth stages. The results highlight the relevance of multispectral imaging as a dependable, non-destructive, and cost-efficient instrument for sustainable agricultural practices. Overall, this research advances the digital transformation of agriculture by providing a user-friendly decision-support platform that enhances crop productivity and encourages the efficient utilisation of resources. |
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| Autores principais: | Felício, Tiago Miguel Martins |
| Assunto: | Precision agriculture Imagem multiespectral -- Multispectral imaging Vegetation indices (VIs) Unmanned Aerial Vehicle (UAV) Crop monitoring Processamento de imagens -- Image processing Agricultura de precisão Índices de vegetação Veículo aéreo não tripulado Monitorização de cultivos |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | ISCTE |
| Idioma: | inglês |
| Origem: | Repositório ISCTE |
| Resumo: | The growing challenges of food demand, climate variability, and resource scarcity have highlighted the need for innovative technological solutions in agriculture. This work presents a software platform for the analysis of multispectral images of agricultural fields for Precision Agriculture, with a focus on improving crop monitoring and resource management. The proposed platform integrates data collected from Unmanned Aerial Vehicles (UAVs) equipped with multispectral sensors to assess vegetation health using spectral vegetation indices (VIs), such as NDVI, SAVI, GNDVI, and NDRE. These indices are computed automatically within a user-friendly desktop application, allowing farmers to analyse plant growth, identify stress conditions, and make informed management decisions. Experimental validation employing a publicly available multispectral dataset demonstrated the platform’s capacity to identify variations in crop vigour and chlorophyll content across various growth stages. The results highlight the relevance of multispectral imaging as a dependable, non-destructive, and cost-efficient instrument for sustainable agricultural practices. Overall, this research advances the digital transformation of agriculture by providing a user-friendly decision-support platform that enhances crop productivity and encourages the efficient utilisation of resources. |
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