Abstract ID: 28.7285 | Accepted as Poster | Poster | 2025-02-27 13:00 - 14:30 | Ágnes‐Heller‐Haus/Small Lecture Room

Glaciers are vital freshwater reservoirs on Earth, and Pakistan is home to some of the world’s largest mid-latitude glaciers, which greatly contribute to the country’s economy. The accelerated melting of glaciers worldwide due to climate change underscores the significance of regular monitoring. However, many glaciers especially in the Hinduskuh and Karakoram, are covered with deris, making it challenging to rely solely on optical satellite imagery for monitoring changes and creating glacier inventories for change detection. Consequently, studies in these regions often yield conflicting results. This study presents a new and robust approach that combines interferometrically derived synthetic aperture radar (InSAR) coherence with optical multispectral data in an object-based image analysis (OBIA) framework to delineate debris-covered glacier outlines accurately. InSAR coherence is capable of detecting temporally decorrelated surfaces, such as glaciers, regardless of their surface type (ice or debris). It effectively separates these surfaces from the highly coherent surrounding areas. OBIA offers numerous benefits compared to conventional classification methods because it can leverage multiple data sources and process data contextually and hierarchically. To the best of our knowledge, this approach has not been used previously for glacier delineation. This integrated method resulted in an overall glacier accuracy of 94.87% compared to manually corrected outlines. This highlights the excellent performance of this integrated approach, which showed minimal misclassifications and robustness against conventional methods. Furthermore, a comparative analysis involving Sentinel-2 multispectral data and previous glacier inventories highlighted the potential of the proposed robust processing chain, emphasizing its capability to consistently update the boundaries of land-terminating glaciers on a large scale.