Challenges

Challenge: Many regions with significant glacier activity lack long-term continuous monitoring, making it harder to understand the long-term trends and predict future changes. 

Research: Establishing continuous monitoring geospatial databases that combine remote sensing with in-situ data collection (sensor sampling, dendrochronology, etc.)  to provide a long-term dataset for assessing glacier changes and associated risks. 

Challenge: Many remote sensing change detection methods rely on bi-temporal analysis, while glacier landscape changes occur as spatio-temporal continuous processes. Also combining data from different satellite platforms, sensor types, and in-situ sources poses challenges regarding data integration and harmonization.

Research: New ways of processing and understanding long-term data from different sources (e.g. combining satellite data with historical archives and drone data). Designing new models that combine machine learning and physical principles to help understand the dynamics. 

Challenge: The lack of advanced spatio-temporal technologies poses a significant challenge in effectively analyzing and visualizing changes over time. Current tools are limited in their ability to process and represent dynamic spatial data, making it difficult to capture the temporal evolution of glacier landscapes and geohazards. This gap hinders accurate modeling and prediction of climate impacts on glaciers and associated risks.

Research: Improved data integration frameworks shall be designed and developed for integrating multi-source spatio-temporal data. New tools for visualizing spatio-temporal data, allow researchers and decision-makers to interpret easily the changes over time in glacier landscapes. 

Challenge: Glaciers respond to climate change in complex ways, and predicting how they will evolve and contribute to hazards like GLOFs or avalanches is difficult due to limited understanding of underlying physical processes.

Research: Improved models that capture glacier mechanics, interactions with the atmosphere, landscape, and how these influence potential geohazards. 

Challenge: Glaciers are dynamic systems that change over multiple spatial and temporal scales (from seasonal to decadal). Massive datasets pose significant challenges for proper rendering and interactive exploration in real-time 3D environments, in addition to depicting the multiple processes. 

Research: Develop multiscale data fusion techniques to efficiently manage and visualize high data complexity. Methods such as level-of-detail (LOD) rendering, progressive data loading, and adaptive and dynamic meshing are essential to maintain interactivity while allowing users to seamlessly zoom in on fine details or move between time scales. 

Challenge: Glacier retreat affects water availability and increases the risk of hazards in communities that rely on glaciers for freshwater. Accurately assessing these impacts is complicated by uncertainties in future glacier melt patterns. 

Research: Creating more precise monitoring and assessment frameworks to link glacier melt to downstream water resources and identifying communities most at risk from both reduced water supply and geohazards.