Articles | Volume 12, issue 1
https://doi.org/10.5194/tc-12-343-2018
https://doi.org/10.5194/tc-12-343-2018
Research article
 | 
26 Jan 2018
Research article |  | 26 Jan 2018

Estimation of degree of sea ice ridging based on dual-polarized C-band SAR data

Alexandru Gegiuc, Markku Similä, Juha Karvonen, Mikko Lensu, Marko Mäkynen, and Jouni Vainio

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Cited articles

Barale, V. and Gade, M. (Eds.): Remote Sensing of the European Seas, Springer Science + Business Media B.V., ISBN-13:978-1402067716, 2008.
Barber, D. G. and LeDrew, E. F.: SAR sea ice discrimination using texture statistics: A multivariate approach, Photogramm. Eng. Rem. S, 57, 385–395, 1991.
Beitsch, A., Kaleschke, L., and Kern, S.: Investigating High-Resolution AMSR2 Sea Ice Concentrations during the February 2013 Fracture Event in the Beaufort Sea, Remote Sens., 6, 3841–3856, 2014.
Berthod, M., Kato, Z., Yu, S., and Zerubia, J.: Bayesian image classification using Markov random fields, Image and Vision Comput., 14, 285–295, 1996.
Besag, J.: Spatial interaction and the statistical analysis of lattice systems, J. R. Stat. Soc. B, 36, 192–236, 1974.
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The paper demonstrates the use of SAR imagery in retrieving ice-ridging information for navigation. Based on image segmentation and several texture features extracted from SAR, we perform a classification into four ridging categories from level ice to heavily ridged ice. We compare our results with the manually drawn ice charts over the Baltic Sea. We conclude that the SAR-based product is more detailed than FIS and can be used by ships (non-icebreakers) to aid independent navigation.
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