Towards Best Practices in UAV Thermal Remote Sensing in Complex Environments

Abstract. Thermal infrared (TIR) remote sensing using uncrewed aerial vehicles (UAVs) is a promising approach for measuring surface temperatures in complex environments. This study examines the challenges encountered and the lessons learned from UAV TIR surveys of a cryospheric landform in the Swiss Alps. We conducted laboratory experiments and field observations to develop, implement and evaluate the effectiveness of different correction schemes. The results reveal significant dependencies between the internal temperature of the camera and the retrieved surface temperatures, showing a non-linear bias of the UAV TIR camera towards cold, warm, and hot targets. The correction schemes produce divergent outcomes; some amplify extremes, while others reduce the temperature spatial distribution. Validation against data from in situ radiometers and ground surface temperature loggers shows that field calibration provides the most accurate results, whereas drift correction can be misleading in environments with complex topography. By addressing technical and environmental limitations, we provide best practices for UAV TIR surveys and post-processing strategies. Our findings highlight the importance of robust calibration, topographic characterisation and site-specific validation to accurately retrieve surface energy budget-relevant variables in rapidly changing mountainous environments.