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Remote Sens. 2017, 9(12), 1270; https://doi.org/10.3390/rs9121270

Improving Sea Ice Characterization in Dry Ice Winter Conditions Using Polarimetric Parameters from C- and L-Band SAR Data

1
Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC H9P 1J3, Canada
2
Canadian Ice Service, Environment and Climate Change Canada, Ottawa, ON K1A 0H3, Canada
3
National Wildlife Research Center, Environment and Climate Change Canada, Ottawa, ON K1A 0H3, Canada
4
Climate Research Division, Environment and Climate Change Canada, Toronto, ON M3H 5T4, Canada
5
Department of Earth and Space Science and Engineering, York University, Toronto, ON M3J 1P3, Canada
*
Author to whom correspondence should be addressed.
Received: 31 October 2017 / Revised: 27 November 2017 / Accepted: 4 December 2017 / Published: 7 December 2017
(This article belongs to the Section Ocean Remote Sensing)
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Abstract

Sea ice monitoring and classification is one of the main applications of Synthetic Aperture Radar (SAR) remote sensing. C-band SAR imagery is regarded as an optimal choice for sea ice applications; however, other SAR frequencies has not been extensively assessed. In this study, we evaluate the potential of fully polarimetric L-band SAR imagery for monitoring and classifying sea ice during dry winter conditions compared to fully polarimetric C-band SAR. Twelve polarimetric SAR parameters are derived using sets of C- and L-band SAR imagery and the capabilities of the derived parameters for the discrimination between First Year Ice (FYI) and Old Ice (OI), which is considered to be a mixture of Second Year Ice (SYI) and Multiyear Ice (MYI), are investigated. Feature vectors of effective C- and L-band polarimetric parameters are extracted and used for sea ice classification. Results indicate that C-band SAR provides high classification accuracy (98.99%) of FYI and OI in comparison to the obtained accuracy using L-band SAR (82.17% and 81.85%), as expected. However, L-band SAR was found to classify only the MYI floes as OI, while merging both FYI and SYI into one separate class. This comes in contrary to C-band SAR, which classifies as OI both MYI and SYI. This indicates a new potential for discriminating SYI from MYI by combining C- and L-band SAR in dry ice winter conditions. View Full-Text
Keywords: L-band SAR; sea ice; polarimetric parameters; classification L-band SAR; sea ice; polarimetric parameters; classification
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Dabboor, M.; Montpetit, B.; Howell, S.; Haas, C. Improving Sea Ice Characterization in Dry Ice Winter Conditions Using Polarimetric Parameters from C- and L-Band SAR Data. Remote Sens. 2017, 9, 1270.

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