Analysis of ice shelf front dynamics in Pine Island Bay (Antarctica) based on long-term SAR time series and deep learning

Kurzfassung

Ice shelves, the floating extensions of ice sheets, create a safety band around Antarctica by buttressing the upstream grounded ice. Loss of their stability leads to increased ice discharge contributing to sea level rise. Thus, it is important to monitor ice shelf dynamics. So far, the potential of spaceborne Synthetic Aperture Radar (SAR) data has not yet been full exhausted as early satellites have hardly been used. To fill this research gap, this study made use of the ERS and Envisat archive within Pine Island Bay, a region of drastic ongoing changes. A 20-year time series (1992-2011) of ice shelf front dynamics was derived using a deep neural network architecture that combines segmentation and edge detection. The product reveals individual destabilisation patterns - most considerable for Pine Island Ice Shelf in terms of frequency of calving events and Thwaites ice tongue in terms of size of break-up. The successful approach demonstrates the potential for long-term analysis of ice shelf dynamics over entire Antarctica.