Optimal Compact Polarimetric Parameters and Texture Features for Discriminating Sea Ice Types during Winter and Advanced Melt

• Published in: Canadian Journal of Remote Sensing
• Main Authors: Sasha Nasonova, Randall K. Scharien, Torsten Geldsetzer, Stephen E. L. Howell, Desmond Power
• Format: Article in Journal/Newspaper
• Language: English; French
• Published: Taylor & Francis Group 2018
• Subjects: Environmental sciences; GE1-350; Technology; T; Arctic; Sea ice
• Online Access: https://doi.org/10.1080/07038992.2018.1527683; https://doaj.org/article/cd3133b6530041ec9f9c6a65cf2d0351

C-band synthetic aperture radar (SAR) is widely used for sea ice monitoring and operational activities. The RADARSAT Constellation Mission (RCM), with its anticipated launch in 2018, will provide hybrid compact polarimetric (CP) C-band SAR data offering near-polarimetric capabilities at large image acquisition widths suitable for achieving operational and scientific objectives in the Arctic. Although C-band SAR is effective for sea ice monitoring, it is difficult to implement during advanced melt, when the sea ice cover is melting and covered by melt ponds. Ice type separability during winter (pre-melt) and advanced melt conditions was assessed using Kolmogorov–Smirnov statistical separability analyses and Support Vector Machine supervised classifications of RCM parameters simulated from 2 winter and 2 advanced melt RADARSAT-2 scenes. Through a detailed analysis of the 2 advanced melt scenes, it was found that the steep incidence angle (22.3–24.2°) simulated RCM CP parameters provide improved ice type separability during the advanced melt period compared with shallow incidence angles (39.6–42.2°). With respect to classification, an overall accuracy of 77.06% was found for a scene comprising first-year and multiyear ice types, and a higher overall accuracy of 85.91% was achieved by including gray level co-occurrence matrix parameters in the classification.