Abstract

ABSTRACTEuropean Space Agency Sentinel-1 (S1) synthetic aperture radar (SAR) datasets are used to assess their suitability for ocean surface feature extraction in the vicinity of the Gulf Stream. A SAR ocean feature detection tool originally developed to extract and classify brightness fronts in RADARSAT-2 (R2) SAR imagery has been updated to extract and classify brightness fronts from S1 ground range-detected products. Results indicate that the features extracted from S1 datasets are largely consistent with those derived from R2. However, more features are extracted from S1 data and, in limited examples, there are differences in how features are classified. In addition, S1 radial velocity (RVL) products were compared with simulated RVL products created from modeled ocean current data. This comparison shows that the orientation and magnitude of the Gulf Stream in S1 RVL products is generally consistent with modeled results, but does indicate that some regions of the Gulf Stream (meanders and ocean eddies) are likely to present challenges for automatic extraction algorithms. Taken together, this research shows that S1 data have utility for ocean surface feature extraction and provide an additional dataset that can be exploited to expand ocean feature analysis over Canadian waters.

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