Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry

• Published in: Remote Sensing of Environment
• Main Authors: Wangchuk, Sonam, Bolch, Tobias, Robson, Benjamin Aubrey
• Other Authors: University of St Andrews. Environmental Change Research Group, University of St Andrews. Bell-Edwards Geographic Data Institute, University of St Andrews. School of Geography & Sustainable Development
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2022
• Subjects: Sentinel-1; SAR; Radar backscatter; Google Earth Engine; Persistent scatterer interferometry; Glacial lake monitoring; Glacial lake hazard; Slope stability; Outburst susceptibility; GB Physical geography; NDAS; SDG 13 - Climate Action; AC; GB; Glacial Lake; Psi; Ice; permafrost
• Online Access: http://hdl.handle.net/10023/25413; https://doi.org/10.1016/j.rse.2022.112910

Funding to support this research from the University of St Andrews and the School of Geography and Sustainable Development is gratefully acknowledged. Continuous monitoring of glacial lakes, their parent glaciers and their surroundings is crucial because possible outbursts of these lakes pose a serious hazard to downstream areas. Ongoing climate change increases the risk of this hazard globally due to recession of glaciers leading to formation and expansion of glacial lakes, and permafrost degradation which impacts the stability of glaciers, slopes and moraines. Here, we demonstrate the capability of our approach for monitoring lake outburst susceptibility using time-series of Sentinel-1 Synthetic Aperture Radar (S-1 SAR) data. We selected Lunana in the Bhutanese Himalayas as an example region as it is highly susceptible to glacial lake outburst floods and suitable baseline data were available. We used Google Earth Engine (GEE) to calculate average radar backscatter intensity (ARBI) of glaciers, lakes, basins, and moraines. To determine the periodicity of the highest and the lowest radar backscatter intensity, we denoised the ARBI data using a Fast Fourier Transform and autocorrelated using a Pearson correlation function. Additionally, we determined glacier melt area, basin melt area, lake area, open water area, and lake ice area using radar backscatter intensity data. The Persistent Scatterer Interferometry (PSI) technique was used to investigate the stability of moraines and slopes around glacial lakes. The PSI results were qualitatively validated by comparison with high-resolution digital elevation model differencing results. Our approach showed that glaciers and basins in the region underwent seasonal and periodic changes in their radar backscatter intensity related to changes in ice and snow melt. Lakes also showed seasonal changes in their radar backscatter intensity related to the variation of lake ice and open water area, but the radar backscatter intensity change was not periodic. We could also infer ...