Key points are not available for this paper at this time.
The integration of Unmanned Aerial Vehicles (UAVs) into agricultural practices represents a significant transition from conventional farming methods toward precision-oriented, data-driven systems that align with the broader objectives of precision agriculture. This review systematically examines the evolving applications of UAVs within agricultural domains, emphasizing their growing role in enhancing operational efficiency and supporting sustainable farming practices. Equipped with advanced Remote Sensing (RS) technologies including multispectral and hyperspectral sensors, thermal imaging systems, Light Detection and Ranging (LiDAR), and Global Positioning Systems (GPS), UAVs enable real-time, high-resolution environmental monitoring. In addition, they play a critical role in high-throughput phenotyping, livestock surveillance, and site-specific irrigation management, collectively supporting the development of climate-resilient and sustainable agricultural ecosystems. The integration of Artificial Intelligence (AI) and Machine Learning (ML) algorithms into UAV data pre-processing and post-processing workflows further enhances their functionality by enabling advanced predictive modeling and analytics. However, despite these advantages, the widespread adoption of UAVs is constrained by several challenges, including limited flight endurance due to power constraints, high operational and maintenance costs, regulatory and airspace restrictions, and the inherent complexity associated with managing and processing large volumes of UAV-acquired data. Further technical limitations, including restricted payload capacity and vulnerability to unfavorable weather conditions, also constrain UAV performance. Nevertheless, recent advancements such as hybrid UAV platforms, multi-sensor integration, autonomous swarm-based operations, and energy-efficient design architectures are steadily mitigating these challenges. By consolidating recent technological developments, application use cases, and prevailing limitations, this study provides a comprehensive reference for researchers, agronomists, and policymakers seeking to effectively harness UAV technologies for future agricultural innovation.
Mashori et al. (Wed,) studied this question.