21 November 2012 Sea state measurements using TerraSAR-X data
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An empirical algorithm (XWAVE) to derive integrated sea state parameters from TerraSAR-X (TS-X) SAR data is developed and validated using NOAA in-situ buoy wave measurements. The comparison for significant wave height and peak wave length was performed as well for deep water locations in open ocean as well as for coastal areas. The significant wave height validation results show a correlation of 0.93% and a scatter index of 0.21 when using in-situ wave buoy data. Verification of the TS-X derived peak wavelength against in-situ buoy data resulted in a correlation of 0.96 and a scatter index of 0.13. The main highlights of TS-X imagery are a higher resolution of up to 1m, when compared to conventional C-band SAR data and a reduction of non-linear imaging effects of a moving target by lower platform altitude. Thus, ocean waves with wavelength less than 30m are detectable. This makes TS-X particularly useful to observe coastal areas where complex bathymetry strongly impacts the approaching waves. In this paper, TS-X images acquired in different coastal areas are presented, including three cases of the German coast and one case near the coast of the Azores Archipelago in the North Atlantic Ocean. Wave fields are derived from the TS-X imagery using the proposed XWAVE algorithm and compared not only to in-situ buoy wave measurements but also to results of a high resolution numerical wave model. The objective was to study the quality of significant wave height field estimation in the spatial domain in highly variable conditions which are typically dominant in coastal areas. The results show that the empirical XWAVE algorithm allows estimating wave fields from TS-X data with high resolution thus showing the spatial information on wave variations. Therefore it is a new useful tool to characterize sea state in coastal areas by remote sensing.
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Miguel Bruck, Miguel Bruck, Susanne Lehner, Susanne Lehner, "Sea state measurements using TerraSAR-X data", Proc. SPIE 8536, SAR Image Analysis, Modeling, and Techniques XII, 85360O (21 November 2012); doi: 10.1117/12.976872; https://doi.org/10.1117/12.976872


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