UAV Remote Sensing

UAV remote sensing studies how imagery and measurements collected by drones can describe places and changes at fine spatial and temporal scales, supporting agriculture, forestry, infrastructure inspection, and disaster response. It uses RGB, multispectral, thermal, hyperspectral, and LiDAR data with methods such as object detection, segmentation, photogrammetry, stereo, and 3D mapping; newer work also explores multimodal fusion, self-supervised learning, and vision-language models. A central challenge is making models and measurements reliable across different sensors, seasons, sites, viewing angles, and environmental conditions, especially when labels are limited or imperfect. Practical systems must also balance accuracy and geometric or radiometric fidelity against flight constraints, processing latency, and the computing resources available onboard.