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A comprehensive, automated approach to determining sea ice thickness from SAR data

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3 Author(s)
Haverkamp, D. ; Dept. of Electr. Eng. & Comput. Sci., Kansas Univ., Lawrence, KS, USA ; Leen Kiat Soh ; Tsatsoulis, C.

Documents an approach to sea ice classification through a combination of methods, both algorithmic and heuristic. The resulting system is a comprehensive technique, which uses dynamic local thresholding as a classification basis and then supplements that initial classification using heuristic geophysical knowledge organized in expert systems. The dynamic local thresholding method allows separation of the ice into thickness classes based on local intensity distributions. Because it utilizes the data within each image, it can adapt to varying ice thickness intensities to regional and seasonal changes and is not subject to limitations caused by using predefined parameters

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Geoscience and Remote Sensing, IEEE Transactions on  (Volume:33 ,  Issue: 1 )