The study provides new insights into snowpack characteristics by combining UAS‑based thermal products, such as snow‑depth estimates and temperature‑variance maps, with in‑situ measurements. Lena also developed a reproducible workflow for classifying snow surfaces over time, enabling detailed mapping of snow properties across the landscape. While challenges remain—such as image artifacts and the difficulty of detecting older ice layers—the thesis demonstrates the strong potential of thermal UAS to complement existing methods in Arctic snow research.

The project was supervised by Dr. Mirjana Bevanda (EORC, University of Würzburg) and Dr. Larissa T. Beumer from the University Centre in Svalbard (UNIS), whose expertise supported both the methodological development and the Arctic fieldwork component.