Why?

Rapid environmental and, in particular, cryosphere changes caused by global warming pose a major challenge to societies on a global scale. High mountain regions are exposed to various processes, which occur simultaneously. These include glacier decrease, ice, snow, and rock avalanches and landslides occurrence, new lake formations, and intensification of erosional processes, which potentially induce geohazards. Many communities in mountainous areas face these hazards, and understanding the related risks is the key to being prepared for them.

What?

Studies show that glaciers have been melting and shrinking faster over the last two decades. Global studies identify major trends, while local studies show details to understand physical processes. However, we still don’t fully understand how different types of glaciers change over time, making it hard to predict where they might cause hazards. Key questions include the future of glacierized mountain areas, how these changes will affect geohazards and their implications for societal resilience and adaptation. The main goal of the team is to understand these long-term interactions.

How?

A long-term geo-spatial data archive integrating diverse data sources allows for a more comprehensive examination of cryosphere processes. Furthermore, it is essential to increase the spatial and temporal resolution to gain better insights into the processes and their interactions. The development of novel machine learning models for remote sensing time-series data analysis shall shift the focus from bi-temporal change detection to continuous monitoring. This will provide a deeper understanding of the interactions between the processes and consequently design adaptive strategies to reduce vulnerability and risks of local communities.