A Review of UAV-Based Monitoring in Agriculture and Forestry: Applications, Challenges, and Future Directions

Unmanned aerial vehicles (UAVs) are becoming increasingly important in agriculture and forestry because they provide high-resolution, flexible, and timely observations of managed terrestrial ecosystems. In agriculture, their main applications include weed detection, disease monitoring, crop growth assessment, yield estimation, and water- and nutrient-related management. In forestry, UAVs are widely used for forest inventory, canopy and stand characterization, tree species recognition, trait analysis, and forest health assessment. Recent advances in multispectral, thermal, and hyperspectral sensing, together with machine learning and deep learning, have further expanded their analytical potential and operational relevance. However, several limitations still constrain broader adoption, including methodological heterogeneity, limited transferability across contexts, operational complexity, and insufficient standardization. The aim of this review is to synthesize current UAV applications in agriculture and forestry and to discuss the main methodological challenges and future directions shaping their scientific and practical development.