Comparing automated sea ice classification on single-pol and dual-pol TerraSAR-X data

We compare classification of sea ice based on TerraSAR-X (TS-X) images for single-polarization and dual-polarization imaging modes. A texture based implementation for neural network classification on single-polarized ScanSAR data is presented. Likewise we propose an approach for operational generation of dual-polarized Stripmap data (with a different neural network architecture). Polarimetric feature quality in terms of information content is discussed for the latter implementation. Based on these results, neural network classification is applied to image acquired over Svalbard, Baffin Bay, and the Barents Sea. Our successful results justify to increase efforts into exploring further application potential of a software suite which comprises both algorithms. Such a tool may then provide navigational assistance for maritime users in near-real time.