Proceedings
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| Filter results5 paper(s) found. |
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1. High Resolution 3D Crop Analysis and Decision Support using UAV LiDAR TechnologyAgriculture is one of the most significant economic activities in Brazil, with coffee cultivation playing a particularly prominent role in the state of Minas Gerais, which leads national production. During the early stages of the coffee growth cycle, systematic monitoring practices are required to assess the spatial uniformity of plant development. These observations support management decisions, including the identification of areas requiring specific interventions and the targeted application... A. Pavanelli, L. Carneiro De Souza, C.E. Inácio, M. De Oliveira, V. Rennó, F. Portelinha, L. Mendes |
2. Digital Livestock Management Solution for Cattle Identification, Traceability, and Real-time MonitoringBrazil is a global player in the beef industry with the world's largest commercial bovine herd, exceeding 230 million head, and leads the international market, accounting for approximately 25% of the global beef trade, reaching over 150 international markets. The combination of edaphoclimatic diversity, high-performance genetics, rigorous sanitary protocols, and the adoption of technological framework for tropical livestock accounts for decoupling of Brazilian ranching from extensive, low-productivity... A. Bernardi, A.R. Garcia, E.S. Guimarães, F. Tonato, S.R. Medeiros, W. Barioni Jr., J.B. Portugal, T.C. Alves, W.P. Cavalcante, M. Serão Filho, C. Gaioli Jr |
3. Influence of Meteorological Variables on Bean Yield in the Semi-Arid Region: A Data-Driven Approach for Agricultural Decision SupportCommon bean is a strategic crop for the Brazilian semi-arid region, predominantly cultivated under rainfed systems that are highly dependent on climate variability. In regions characterized by irregular rainfall patterns, high temperatures, and extreme weather events, incorporating temporal analyses based on meteorological data becomes essential for evidence-based agricultural planning. Within the context of precision agriculture, the integration of historical climate series and productivity indicators... A. Fonseca, J.F. Dos Anjos, E.F. Da Silva, G.B. Moura, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, A.C. Bezerra |
4. Nonlinear Modeling of Vegetation Response to Rainfall Variability in the Brazilian Semi-Arid Region Using Sentinel-2 and CHIRPS DataHigh climate variability in the Brazilian semi-arid region poses significant challenges to agriculture and the sustainable management of Caatinga ecosystems, requiring monitoring tools capable of anticipating vegetation responses to rainfall fluctuations. However, the spectral response of vegetation to precipitation does not always follow linear patterns and may reflect ecohydrological thresholds and water saturation effects. Sentinel-2 data were used to derive the Soil Adjusted Vegetation Index... A. Fonseca, E.F. Da Silva, A.C. Bezerra, G.B. Moura, J.F. Dos Anjos, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, J.I. Silva |
5. Comparative Evaluation of Ground Point Classifiers in LiDAR Point Clouds for DEM Generation in Pasture AreasThe classification of ground points in LiDAR point clouds is an essential step for generating reliable Digital Terrain Models (DTMs), particularly in livestock production systems based on pastures. Despite methodological advances in forested and urban environments, studies specifically addressing ground classification in pasture areas remain limited, where the proximity between the forage canopy and the ground surface makes altimetric distinction between classes challenging. The heterogeneous... |