THE APPLICATION OF DRONE TECHNOLOGY AND IMAGE ANALYSIS FOR MONITORING GRAZING PATTERNS AND RANGELAND CAPACITY IN CATTLE FARMING - Ricardo Figueroa; Carlos Chavarria; Luis Ramirez (Techno Agriculturae Studium of Research, 2025)
The increasing demand for sustainable cattle farming and the pressure on rangeland resources have highlighted the need for efficient monitoring of grazing patterns and land carrying capacity. Traditional methods of monitoring rely on manual field surveys, which are labor-intensive and have limited coverage. Recent advancements in drone technology and image analysis present new opportunities for data-driven decision-making in livestock and rangeland management. This study explores the use of drone technology combined with image analysis techniques to monitor grazing patterns and assess rangeland capacity. A research and development design was employed, with drones capturing high-resolution aerial imagery of grazing areas at regular intervals. Image analysis techniques, including vegetation index extraction and spatial pattern analysis, were used to assess grazing intensity, vegetation cover, and biomass distribution. Data from the drone-based imagery were validated through ground observations and rangeland productivity records. The results show that drone-derived imagery accurately captured spatial variations in grazing behavior and vegetation condition, allowing for precise mapping of grazing zones and reliable estimates of rangeland carrying capacity. Compared to traditional methods, the drone-based approach was more efficient, offered greater spatial accuracy, and reduced the need for field surveys. In conclusion, integrating drone technology and image analysis offers a scalable solution for sustainable rangeland and livestock management.