Articles | Volume 11, issue 1
Research article
11 Jan 2017
Research article |  | 11 Jan 2017

Operational algorithm for ice–water classification on dual-polarized RADARSAT-2 images

Natalia Zakhvatkina, Anton Korosov, Stefan Muckenhuber, Stein Sandven, and Mohamed Babiker

Abstract. Synthetic Aperture Radar (SAR) data from RADARSAT-2 (RS2) in dual-polarization mode provide additional information for discriminating sea ice and open water compared to single-polarization data. We have developed an automatic algorithm based on dual-polarized RS2 SAR images to distinguish open water (rough and calm) and sea ice. Several technical issues inherent in RS2 data were solved in the pre-processing stage, including thermal noise reduction in HV polarization and correction of angular backscatter dependency in HH polarization. Texture features were explored and used in addition to supervised image classification based on the support vector machines (SVM) approach. The study was conducted in the ice-covered area between Greenland and Franz Josef Land. The algorithm has been trained using 24 RS2 scenes acquired in winter months in 2011 and 2012, and the results were validated against manually derived ice charts of the Norwegian Meteorological Institute. The algorithm was applied on a total of 2705 RS2 scenes obtained from 2013 to 2015, and the validation results showed that the average classification accuracy was 91 ± 4 %.

Short summary
The presented fully automated algorithm distinguishes open water (rough/calm) and sea ice based on dual-polarized RS2 SAR images. Texture features are used for Support Vector Machines supervised image classification. The algorithm includes pre-processing and validation procedures. More than 2700 scenes were processed and the results show the good discrimination between open water and sea ice areas with accuracy 91 % compared with ice charts produced by MET Norway service.