Volume XLI-B7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 543-548, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-543-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 543-548, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-543-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  21 Jun 2016

21 Jun 2016

COMPARISON OF C-BAND AND X-BAND POLARIMETRIC SAR DATA FOR RIVER ICE CLASSIFICATION ON THE PEACE RIVER

H. Łoś1, K. Osińska-Skotak1, J. Pluto-Kossakowska1, M. Bernier2, Y. Gauthier2, M. Jasek3, and A. Roth4 H. Łoś et al.
  • 1Dept. of Photogrammetry, Remote Sensing and GIS, Faculty of Geodesy and Cartography, Warsaw University of Technology, Poland
  • 2Centre Eau, Terre et Environement, Institut National de la Recherche Scientifique, Quebec, Canada
  • 3Bc Hydro, Burnaby, Canada
  • 4Remote Sensing Data Center, DLR, Oberpfaffenhofen, Germany

Keywords: River ice dynamics, SAR, Polarimetry

Abstract. In this study, synthetic aperture radar (SAR) data from TerraSAR-X were compared with RADARSAT-2 data to evaluate their effectiveness for river ice monitoring on the Peace River. For several years RADARSAT-2 data have been successfully used for river ice observation. However, it is important to take into account data from other satellites as they may provide solutions when it is not possible to obtain images from the preferred system (e.g., in the case of acquisition priority conflicts). In this study we compared three TerraSAR-X (X-band) and three RADARSAT-2 (C-band) datasets acquired in December 2013 on a section of the Peace River, Canada. For selected classes (open water, skim ice, juxtaposed skim ice, agglomerated skim ice, frazil run and consolidated ice) we compared backscattering values in HH and VV polarisation and performed Wishart supervised classification. Covariance matrices that were previously filtered using a refined Lee filter were used as input data for classification. For all data sets the overall accuracy was higher than 80%. Similar errors associated with classification output were observed for data from both satellite systems.