Background: Precision agriculture has revolutionized crop monitoring through the integration of advanced remote sensing technologies, including unmanned aerial vehicles (UAVs), satellite imagery, and ground-based sensors. These technologies provide farmers and researchers with unprecedented capabilities for real-time crop assessment, yield prediction, and agricultural management.
Objective: This study examines the current applications, methodologies, and effectiveness of drones, satellite imagery, and remote sensing technologies in crop monitoring, analyzing their individual and combined contributions to modern agricultural practices.
Methods: A comprehensive review of recent literature was conducted, analyzing various remote sensing platforms, sensor technologies, and data processing techniques used in crop monitoring. Field studies and case analyses were examined to evaluate the practical applications and limitations of these technologies.
Results: The integration of multi-platform remote sensing approaches demonstrates significant improvements in crop monitoring accuracy, with UAVs providing high-resolution spatial data (sub-meter resolution), satellites offering large-scale temporal coverage, and ground sensors delivering continuous monitoring capabilities. Vegetation indices such as NDVI, SAVI, and EVI show strong correlations with crop health and yield parameters.
Conclusion: The synergistic use of drones, satellite imagery, and remote sensing technologies represents a paradigm shift in precision agriculture, enabling data-driven decision making, optimized resource utilization, and enhanced crop productivity. Future developments in sensor technology, artificial intelligence, and data integration platforms will further enhance the effectiveness of these monitoring systems.