Fixed-Wing UAV Flight Operation under Harsh Weather Conditions: A Case Study in Livingston Island Glaciers, Antarctica

How do the weather conditions typical of the polar maritime glaciers in the western Antarctic Peninsula region affect flight operations of fixed-wing drones and how should these be adapted for a successful flight? We tried to answer this research question through a case study for Johnsons and Hurd glaciers, Livingston Island, using a fixed-wing RPAS, in particular, a Trimble UX5 UAV with electric pusher propeller by brushless 700 W motor, chosen for its ability to fly long distances and reach inaccessible areas. We also evaluated the accuracy of the point clouds and digital surface models (DSM) generated by aerial photogrammetry in our case study. The results were validated against ground control points taken by differential GNSS techniques, showing an accuracy of 0.16 +/- 0.12 m in the vertical coordinate. Various hypotheses were proposed and flight-tested, based on variables affecting the flight operation and the data collection, namely, gusty winds, low temperatures, battery life, camera configuration, and snow reflectivity. We aim to provide some practical guidelines that can help other researchers using fixed-wing drones under climatic conditions similar to those of the South Shetland Islands. Performance of the drone under harsh weather conditions, the logistical considerations, and the amount of snow at the time of data collection are factors driving the necessary modifications from those of conventional flight operations. We make suggestions concerning wind speed and temperature limitations, and avoidance of sudden fog banks, aimed to improve the planning of flight operations. Finally, we make some suggestions for further research.

Automated summary

This study conducted a case study on the Johnsons and Hurd glaciers in the western Antarctic Peninsula region to examine the impact of weather conditions on the flight operations of fixed-wing drones. The results showed that the Trimble UX5 UAV used in the study performed well under harsh weather conditions and yielded accurate data collection.