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

Ice shelves, the floating extensions of glaciers and ice sheets, create a safety band around Antarctica. They control the flow of ice that drains into the ocean by buttressing the upstream grounded ice. Loss of ice shelf stability and integrity results in reduced buttressing and leads to increased discharge contributing to global sea level rise. Therefore, it is important to monitor ice shelf dynamics to accurately estimate future sea level rise.

So far, the potential of SAR data has not yet been full exhausted as data of early SAR satellites has only been used to a very limited extent for calving front monitoring. To fill this research gap, we made use of the entire ERS and Envisat archive within West Antarctic Pine Island Bay, a region that requires particular attention due to drastic ongoing changes. A 20-year time series (1992-2011) of ice shelf front dynamics was derived based on a deep neural network architecture that combines segmentation and edge detection. By testing different data preparation, training and post-processing configurations we identified the best performing model for ERS and Envisat data. This includes transfer learning based on a model originally trained on Sentinel-1 data and post-processing with filtering and temporal compositing to remove artefacts from geolocation errors and limited data availability.

The resulting product of yearly, half-year and monthly ice shelf front positions reveals individual dynamic patterns for all five investigated ice shelves. The most considerable fluctuations were found for Pine Island Ice Shelf in terms of frequency of calving events (multiple cycles of calving and re-advance) and Thwaites ice tongue in terms of size of break-up (80 km retreat in early 2002). Despite different change rates and magnitudes, most ice shelves show similar signs of destabilisation. This manifests through retreating front positions and changing ice shelf geometries. Signs of weakening appear in the form of fracturing, disintegration events and loss of connection to lateral confinements.