Abstract
An algorithm for ice/water detection of ice less than 30 cm in thickness (thin ice) using dual-polarized synthetic aperture radar (SAR) and passive microwave data has been developed based on insights from previous work. The frequency chosen from those available was in the C-band. For the radiometer layer ice concentrations, land contaminated pixels were removed. For the SAR layers, a novel approach to their use in ice detection was developed using the coefficient of variation (COV), defined as the ratio of the standard deviation of the normalized radar cross section, σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> , to the mean σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> . The COV reduced the complicated signatures of breaking waves and thin ice to bright ice pixels on a dark water background. The co-pol and cross-pol COV layers and the radiometer layer were merged according to physics-based rules, except in regions adjacent to land or the ice edge where only the SAR layers were valid. The detection algorithm was applied to 233 Sentinel 1a and 1b dual-polarization images of the freeze-up from 2015, 2016, 2018, and 2019 in the Beaufort and Chukchi Seas. The synergistic ice retrievals showed improved agreement with manual operational analyses in the marginal ice zone over other automated operational products.
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More From: IEEE Transactions on Geoscience and Remote Sensing
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