Towards an Antarctic Ice Shelf and Glacier Front Monitoring Service based on Sentinel-1 Data

Abstract

The extent of Antarctic ice shelves and glacier tongues is important for accurate sea level rise predictions. If ice shelf areas with strong buttressing effects are lost the ice discharge of the Antarctic Ice Sheet increases. Therefore, it is crucial to monitor ice shelf front positions and keep track of glacier and ice shelf front dynamics. The German Aerospace Center (DLR) is currently facilitating a project aiming to bring together the expertise in polar research: The Polar Monitor Project. Within this project, we are establishing an automated calving front monitoring service providing monthly Ice Shelf and Glacier Front Time Series (IceLines) via the EOC GeoService hosted by DLR. IceLines is based on a deep learning architecture combining segmentation and edge detection optimized for calving front extraction. The monthly front positions are extracted from Sentinel-1 SAR data over the Antarctic coastline. We will outline the implementation of IceLines within the DLR processing infrastructure, present first results and highlight the potential future usage for the scientific community. Future implementations within the Polar Monitor Project will also provide access to daily global snow cover (GlobalSnowPack) and the Antarctic grounding line derived from Sentinel-1 imagery.