SEA ICE CLASSIFICATION USING SAR BACKSCATTER STATISTICS

Sea ice classification accuracy using standard statistics and higher order texture statistics generated from Grey-Level Co-occurrence (GLC) matrices were compared for synthetic aperture radar (SAR) data collected during the Marginal Ice Zone Experiment (MIZEX) in April 1987. Standard stepwise discriminate analysis was used to identify the statistics most useful for the discrimination. Range was the most effective statistic, correctly classifying the ice types 75% of the time. Overall, the standard statistics (mean, variance, range, etc.) outperformed the texture statistics (87% accuracy vs. 75% accuracy). Given the added difficulty and computational cost of generating texture statistics, this result suggests that standard statistics should be used for sea ice classification. Odden and multiyear ice categories were the most difficult to statistically separate for these data.