Sea Ice Classification Using Combined Sentinel-1 and Sentinel-3 Data

We present a new approach for sea ice mapping based on Synthetic Aperture Radar (SAR) data from Sentinel-1 and an existing sea ice classification using optical-thermal data based on Sentinel-3. SAR and optical-thermal sensors provide different information about the sea ice situation: while SAR backscatter depends mainly on the topography of the sea ice surface and properties of the ice volume, optical sensors provide further information about the structure and moisture of ice and snow. In order profit from both sensors, a convolutional neural network (CNN) is trained with collocated images from both satellite missions. Compared to a pure SAR classification, the results of the combined approach show an improved classification reliability, especially in areas with open water.