Classification of ice and water in the Arctic using radar altimeter and microwave radiometer data from HY-2B satellite

Several Chinese marine satellites have been launched in recent years. Monitoring sea ice and the ocean in the Arctic is of great importance for climate research. Sea ice in the Arctic has changed rapidly during the past few decades with respect to the extent and thickness. In this study, we applied combined passive and active microwave data from the Chinese HaiYang-2B (HY-2B) satellite to classify ice and sea water in the Arctic. We use data from a radar altimeter (RA) and a calibration microwave radiometer (CMR) to discriminate between ice and water by applying several approaches (1) the single parameter threshold criteria, (2) the multi-parameters linear segmentations and (3) the K-means clustering. The results yielded by these methods were in good agreement (classification accuracy >95%) with the Satellite Application Facility on Ocean and Sea Ice products between November and April. For other months (May-October), however, the agreement was less good (lowest classification accuracy approximate 85% in summer). A hybrid approach combined with graphical ice edges detection and microwave radar waveform analysis is therefore developed. A visual comparison with SAR images suggested the hybrid approach results greatly improved the ice and water discrimination in summer. This study demonstrated that multi-sensors (RA and CMR) configurations from HY satellites can offer comparable polar earth observation to the European Space Agency and NOAA satellite products.