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A New Algorithm (ECICE) to Estimate Ice Concentration From Remote Sensing Observations: An Application to 85-GHz Passive Microwave Data

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3 Author(s)
Shokr, M. ; Sci. & Technol. Branch, Environ. Canada, Toronto, ON ; Lambe, A. ; Agnew, T.

A new algorithm, called Environment Canada's Ice Concentration Extractor (ECICE), has been developed to calculate total ice concentration and partial concentration of each ice type from remote-sensing observations. It employs two new concepts. First, it obtains a best estimate of ice concentrations by minimizing the sum of squared difference between observed and estimated radiometric values based on a linear radiometric model for each ice type. Second, instead of employing a single radiometric value (tie point) for each ice type, it utilizes the probability density distribution of the radiometric values for each ice type. Then, in a Monte Carlo simulation, 1000 radiometric values are randomly selected, total and ice-type concentrations are calculated by solving the minimization problem, and finally, median values from the 1000 simulations are chosen. The algorithm was applied to the winter sea ice in the Gulf of St. Lawrence, Canada, using observations from Special Sensor Microwave Imager (SSM/I) 85-GHz channel. Results were evaluated against ice concentration estimates from the operational analysis of Radarsat images at the Canadian Ice Service (CIS). Statistics of the differences between the output concentration and CIS estimates show that ECICE can successfully identify open water and consolidated pack ice pixels better than the Enhanced NASA Team algorithm. However, in areas of ice concentrations between 20% and 70%, the algorithm's performance could not be precisely evaluated because the typical size of the CIS's analysis polygon is much larger than the footprint of the 85-GHz SSM/I channel. Hence, the algorithm captures information at a finer spatial scale. Examples of using one, two, and three radiometric parameters to calculate the concentrations are presented.

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Geoscience and Remote Sensing, IEEE Transactions on  (Volume:46 ,  Issue: 12 )