ID.59344: DETAILED CONTEMPORARY GLACIER CHANGES IN HIGH MOUNTAIN ASIA USING MULTI-SOURCE SATELLITE DATA

Cryosphere and Hydrology

Summary

Glaciers are sensitive indicators of climate change and affect regional and global water circulation. High Mountain Asia (HMA) has the largest volume of glacier ice in mid-latitude regions and is considered as the water tower of Asia. HMA glaciers do not only provide drinking and irrigation water for millions of people in and beyond the mountain ranges especially in drought-affected regions, but also provide water to ecosystems. Therefore, continued monitoring of glacier changes and its influences is essential. In this project, we plan to monitor contemporary glacier changes and influences in HMA using recently available satellite data with the focus on Sentinel-1 and 2 and ICESat-2 data but also very high-resolution stereo data. We will develop new methods to monitor glacier with unprecedented detail focusing on changes in area, thickness, velocity and accumulation area ratio (AAR), and reveal the most their recent trends in HMA. Area change. We aim to develop a novel method using repeat Sentinel-2 images on a cloud-computation platform to automatically map clean ice using spectral reflectance information based on composite of cloud-free and seasonal snow-free pixels. For the debris-covered parts which cannot be identified using spectral information alone we aim to develop novel decision tree and random forest algorithms using multisource information including besides spectral reflectance SAR coherence and surface velocity measurements. Thickness change. We will develop and apply an automated method to measure glacier thickness changes for whole HMA by newly launched ICESat-2 laser altimetry data. Moreover we aim to test the suitability (1) to calculate glacier mass balance using the generated outlines from a similar time and density estimates and (2) to measure seasonal mass balance. The accuracy of thickness change from ICESat-2 will be validated in different mountainous areas. Velocity change. Glacier surface velocity provides important information about glacier mass fluxes and allows to calculate surface mass balance using the thickness change data. Monitoring of glacier velocity provides also insights into glacier surging behaviour. We will develop an automated pipeline to derive glacier velocity based on feature tracking using both Sentinel-1 and 2 images. Using both SAR and optical data allows cross-validate glacier velocities and the changes. Accumulation area ratio (AAR). The AAR is a sensitive indicator of glacier mass balance. In late summer, the AAR can be estimated by the wet snow zone ratio using synthetic aperture radar(SAR). The late summer snow line can be delineated from the boundary of the accumulation area. The Glacier mass balance estimates based on the snow-line/AAR observations will be cross-validated using the thickness change data. The methods will be developed, validated and calibrated in selected benchmark sites located in different climatic regions by multi-temporal very high-resolution stereo satellite data such as TerraSAR-X, Pleiades, ZY3, GF7 and glaciological field measurements. In the next step it will then be tested with which accuracy the methods can be applied to whole HMA using especially S1, S2 and ICESat-2 data. Overall, this project will provide comprehensive information about heterogenous glacier characteristics and changes. The results will be analyzed in order to reveal detailed insights into the spatial heterogeneity of glacier mass balance, surface mass balance and velocity and observed annual and seasonal trends. The data and results will be of high value calibrate and validate the glacier component of glacio-hydrological models. It is foreseen that a partner project (led by F. Pellicciotti and M. Menenti) will use these data to better understand the importance of glacier to overall runoff and project future changes using different climate scenarios.


Information

PI Europe
Dr. Tobias Bolch, University of St Andrews, UK
PI China
Dr. Lei Huang, Aerospace Information Research Institute, Chinese Academy of Sciences, CHINA