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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 1
The Cryosphere, 11, 33-46, 2017
https://doi.org/10.5194/tc-11-33-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 11, 33-46, 2017
https://doi.org/10.5194/tc-11-33-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 11 Jan 2017

Research article | 11 Jan 2017

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

Natalia Zakhvatkina1,2, Anton Korosov3, Stefan Muckenhuber3, Stein Sandven3, and Mohamed Babiker3 Natalia Zakhvatkina et al.
  • 1Nansen International Environmental and Remote Sensing Centre (Nansen Centre, NIERSC), 14th Line 7, Office 49, Vasilievsky Island, St. Petersburg, 199034, Russian Federation
  • 2Arctic and Antarctic Research Institute (AARI), Bering Str. 38, St. Petersburg, 199397, Russian Federation
  • 3Nansen Environmental and Remote Sensing Center (NERSC), Thormøhlensgate 47, 5006 Bergen, Norway

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%.

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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.
The presented fully automated algorithm distinguishes open water (rough/calm) and sea ice based...
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