Drone in hyperspectral remote sensing data analytics: techniques and applications

The integration of unmanned aerial vehicles with hyperspectral remote sensing technology has revolutionized Earth observation by enabling flexible high-resolution data acquisition. Unlike satellite platforms with fixed revisit times and low spatial resolution, UAVs provide unprecedented detail and on-demand deployment, making them indispensable for precision agriculture, environmental monitoring, and mineral exploration. This review provides a comprehensive and up-to-date synthesis of key techniques and applications of UAV-based HRS data analytics. We begin by outlining the essential HSI processing pipelines, from preprocessing to advanced analytics. The paper then delves into modern data analysis techniques, including physics-based models, state-of-the-art machines, and deep learning approaches. We further enhance the review by presenting real-world case studies and a critical discussion of practical deployment challenges, as well as ethical and policy considerations. By synthesizing recent developments and addressing existing gaps, this study offers forward-looking perspective on the capabilities and future of UAV-HRS, serving as a valuable resource.