Abstract
In this study a global data set of reprocessed synthetic aperture radar (SAR) data acquired by the European Remote Sensing satellite ERS-2 is used to study ocean wave grouping using wavelet based methods. For more than a decade the ERS-1/2 satellites have continuously recorded SAR images of the ocean surface. Operating in wave mode both instruments have acquired about 1400 imagettes of 10/spl times/5 km. size (every 200 km along the orbit) each day, which allows to study ocean waves on a global basis. Only coarsely gridded SAR image spectra are available as official wave mode products from the European Space Agency (ESA). As the full image information is required for the present study about 3 weeks of ERS-2 SAR wave mode raw data were reprocessed to 34000 complex SAR images using the BSAR processor from the German Aerospace Center (DLR). ENVISAT satellite, which was successfully launched on February 28, 2002, will provide almost 3000 imagettes a day due to its higher sampling rate (every 100 km). Applying a wavelet edge detection method on the SAR-amplitude-density image and using a region growing approach for the edgefree areas allows examinations of the wave groupiness on a single image. These examinations include group size and number of large groups. The wavelet coefficient as a measure for edge strength is correlated to both wave height and steepness. The wavelet method is compared with an alternative approach, which is based on the classical Hilbert-transform technique. For the latter method the actual sea surface elevation field has to be known. Therefore a quasilinear inversion scheme is used which estimates the surface elevation from complex SAR data.
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