Dr.-Ing. Nora Gourmelon’s keynote focused on the application of artificial intelligence and remote sensing for monitoring glacier change in the Arctic. In particular, it highlighted recent work on using deep learning to automatically analyse satellite imagery and support large-scale monitoring of glacier dynamics.
Glaciers are important indicators of climate change, but monitoring their evolution across large and remote regions remains challenging. Satellite observations provide extensive coverage, yet extracting relevant information from these data often requires substantial manual effort. AI-based methods can help automate this process and enable more frequent and comprehensive monitoring.
The keynote was part of the AI for Climate and Conservation Workshop at ECCV 2026, which brought together researchers working at the intersection of computer vision, artificial intelligence, climate science, and conservation.
