Proceedings
Authors
| Filter results5 paper(s) found. |
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1. Validation of UAV-Based NDVI Using Proximal Sensing in Mountain Coffee PlantationsUnmanned aerial vehicles (UAVs) with multispectral sensors have expanded remote sensing applications in precision agriculture, however validation against ground-truth measurements remains critical, especially for perennial crops in complex terrain such as coffee plantations in mountainous regions. Proximal sensing can be employed as a reference for evaluating the quality of data obtained by remote platforms. This study aimed to evaluate the reliability of Normalized Difference Vegetation Index... B. Costalonga Vargas, I.A. Barbosa, D. Queiroz, A.L. Coelho, D.M. Valente, M.C. Moreira |
2. Influence of Application Rate and Flight Orientation on Droplet Deposition by Remotely Piloted Aircraft (RPA) in ‘Gala’ Apple OrchardsApple production is a cornerstone of the fruit industry, with the ‘Gala’ variety holding a prominent position due to its commercial value. However, this cultivar is highly susceptible to apple scab (Venturia inaequalis), requiring application technologies of fungicides that ensure canopy protection, especially during flowering. In this sense, precision horticulture has sought alternatives to optimize the application of crop protection products, aiming to reduce... L. Espindola Müller, T. Buchener, B. Nogueira, R. Silva, S.J. Silveira, C. Bredemeier |
3. Harmonic Modeling of Coffee Biennial Bearing to Quantify Between-plot Variability: a Precision Agriculture Approach for Small-scale AgriculturePrecision Agriculture (PA) practices rely on detecting spatiotemporal variability within a plot to delineate subplots by pixels or by management zones (MZs). This paradigm has been assumed for large-scale plots, yet their adoption in smallholder systems, such as coffee crops under family-based agriculture, remains limited. In this context, within-plot variability is often less operationally relevant than between-plots divergency. Therefore, we assume each plot as a MZ and focus on manage them... J.P. Molin, B. Costa, B. Barreto |
4. Co-registration of RGB UAV Orthomosaics Through a Semi-automated Affine Method Based on Ground Control Points and Phase Correlation ValidationUAV images are crucial for Precision Agriculture (AP) purposes which require the monitoring of spatial variability regarding plant growth, especially to assess variation at plant level over time in perennial crops, such as banana plantations. However, spatial misalignments between orthomosaics from different dates requires post-processing image matching, i.e., co-registration, to ensure reliable spatiotemporal variability analysis. This study proposes a method for the co-registration of RGB UAV... B.R. Costa, J.P. Molin, B. Barreto |
5. Individualization of Banana Canopies Using Multispectral Vegetation Index and the Watershed AlgorithmThe individualization of canopies in perennial crops is an essential step in precision agriculture, enabling plant counting, vigor monitoring, yield prediction, pest management, and harvest planning. Banana (Musa spp.), characterized by large leaves, closed canopy, and high biomass, presents specific challenges for automated segmentation. This study evaluated the performance of the watershed algorithm for canopy individualization, using different multispectral vegetation index, between... B.R. Costa, J.P. Molin, B. Barreto |