A FULLY AUTOMATED, MULTI-SENSOR ASSESSMENT OF TERMINUS POSITION AND ICEBERG DENSITY OF HELHEIM OUTLET GLACIER, GREENLAND

Satellite imagery is an established means for mapping the cryopshere over large spatial and temporal scales. Automated techniques exist for the mapping of clean ice (predominantly pixel-based band ratios) but mostly require the subjective selection of thresholds for each data product, prohibiting fully automatic glacier mapping. Here, we use multi-sensor imagery (Sentinel-1, Sentinel-2, Landsat 5-8 and ASTER) to automatically classify the terminus position of Helheim Outlet Glacier, as well as detect icebergs both in the open fjord and those in the melange. Our workflow is automated and applicable to different sensors and images. We conducted our analysis within an object-based framework which allows for the exploitation of imagery using criteria based on the shape and contectuality of objects being classified. Our preliminery results are promising and show clear advantages of traditional pixel-based methods. Nevertheless, distinguishing icebergs from sea ice and the melange remain issues.