Ice Concentration From Dual-Polarization SAR Images Using Ice and Water Retrievals at Multiple Spatial Scales.

A new technique for automated retrieval of ice concentration from RADARSAT-2 dual-polarization HH-HV ScanSAR Wide images for subsequent assimilation in ice numerical models is presented. First, we extended our previously introduced ice and water detection approach operating at a 2.05 km $\times2.05$ km spatial scale to a set of 19 different spatial scales ranging from 2.05 km (41 pixels) down to 0.25 km (5 pixels). As the spatial resolution was increased, the overall accuracy of ice and water detection stayed at a very high level across all scales (between 99.5% and 99.8%), but the number of water retrievals substantially dropped. Second, we designed an approach for estimating ice concentration in a 2 km $\times 2$ km ($40\times40$ pixels) area consisting of $64\,\,5 \times 5$ pixel blocks. The $5\times 5$ pixel blocks which are initially classified as unknowns are iteratively combined in clusters with effective spatial scales larger than 5 pixels. The clusters are further classified as ice or water using the ice probability model corresponding to the effective spatial scale. The $40\times40$ pixel area becomes populated with high-resolution ($5\times 5$ pixels) ice and water retrievals, and the ice concentration is estimated based on the number of ice and water retrievals. The proposed approach produces a much better agreement with the Canadian Ice Service Image Analysis ice concentrations (root-mean-square error (RMSE) = 2.2%) compared to the original 2-km ice/water detection approach (RMSE = 19.9%). The developed technique will be adapted to the RADARSAT Constellation Mission data for data assimilation in Environment and Climate Change Canada Regional Ice-Ocean Prediction System. [ABSTRACT FROM AUTHOR]