Seasonal Changes of Glacier Lakes in Tibetan Plateau Revealed by Multipolarization SAR Data

In the context of global warming, monitoring glacial lakes is of great significance for revealing climate change and mitigating glacier lake outburst floods (GLOFs). Multitemporal mapping of glacier lakes through optical satellite remote-sensing imageries can only provide us comparative analysis of glacier lake changes during long time intervals. In recent years, the rapid development of synthetic aperture radar (SAR) has made it possible to observe seasonal changes of glacial lakes. This letter proposed a polarization enhancement-based maximum interclass variance (PE-MIV) method to accurately and automatically mapping the seasonal cycles of glacial lakes based on multipolarization SAR data. Taking the Gongcuo and Langcuo glacial lakes in Laigu village, Tibetan Plateau, as examples, based on 113 Sentinel-1 SAR imageries covering 2017 to 2020 with a 12-day revisiting time, the seasonal boundary changes of both lakes were extracted automatically with a relative accuracy of 93.59%. The seasonal variations of glacial lake area are closely related to temperature and precipitation. This letter demonstrated that the satellite SAR (short revisiting time, multipolarization, etc.) is an effective tool to monitor areal changes of glacier lakes, which can be widely applied in detecting glacier lakes, GLOFs, and their response to climate change.