Sea Ice Detection by an Unsupervised Method Using Ku- and Ka-Band Radar Data at Low Incidence Angles: First Results

• Published in: Remote Sensing
• Main Authors: Maria Panfilova, Vladimir Karaev
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2023
• Subjects: dual frequency precipitation radar; global precipitation measurement satellite; near nadir normalized radar cross section; sea ice detection; clustering; Science; Q; Antarctic; Arctic; Antarc*; Sea ice
• Online Access: https://doi.org/10.3390/rs15143530; https://doaj.org/article/5e9cb6015c3b40149388436cbb8b659c

This paper presents the first results of sea ice detection using the data of Ka- and Ku-band radars at low incidence angles. A classification method based on an unsupervised K-means approach is applied to the arrays of the data for the Arctic and Antarctic regions. Comparison with Advanced Microwave Scanning Radiometer 2 (AMSR-2) data was performed, and the dependence of classification performance was evaluated for incidence angles from 0° to 18.15°. This paper evaluates the classification accuracy of sea ice detection based on Ku-band, Ka-band, and their combination. Preliminary results indicate that the classification based solely on Ku-band data achieves the best performance.