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dc.contributor.authorZakhvatkina, Natalia
dc.contributor.authorKorosov, Anton
dc.contributor.authorMuckenhuber, Stefan
dc.contributor.authorSandven, Stein
dc.contributor.authorBabiker, Mohamed
dc.description.abstractSynthetic 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 %.en_US
dc.publisherCopernicus Publicationsen_US
dc.relation.ispartof<a href="" target="blank">High resolution sea ice monitoring using space borne Synthetic Aperture Radar</a>en_US
dc.rightsThis work is distributed under the Creative Commons Attribution 3.0 License.eng
dc.titleOperational algorithm for ice–water classification on dual-polarized RADARSAT-2 imagesen_US
dc.typePeer reviewed
dc.typeJournal article
dc.rights.holderCopyright the authors.en_US
dc.source.journalThe Cryosphere
dc.subject.nsiVDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Petroleumsgeologi og -geofysikk: 464en_US

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