[1] A parametric inversion scheme for the retrieval of two-dimensional (2-D) ocean wave spectra from look cross spectra acquired by spaceborne synthetic aperture radar (SAR) is presented. The scheme uses SAR observations to adjust numerical wave model spectra. The Partition Rescaling and Shift Algorithm (PARSA) is based on a maximum a posteriori approach in which an optimal estimate of a 2-D wave spectrum is calculated given a measured SAR look cross spectrum (SLCS) and additional prior knowledge. The method is based on explicit models for measurement errors as well as on uncertainties in the SAR imaging model and the model wave spectra used as prior information. Parameters of the SAR imaging model are estimated as part of the retrieval. Uncertainties in the prior wave spectrum are expressed in terms of transformation variables, which are defined for each wave system in the spectrum, describing rotations and rescaling of wave numbers and energy as well as changes of directional spreading. Technically, the PARSA wave spectra retrieval is based on the minimization of a cost function. A Levenberg-Marquardt method is used to find a numerical solution. The scheme is tested using both simulated SLCS and ERS-2 SAR data. It is demonstrated that the algorithm makes use of the phase information contained in SLCS, which is of particular importance for multimodal sea states. Statistics are presented for a global data set of 11,000 ERS-2 SAR wave mode SLCS acquired in southern winter 1996.Citation: Schulz-Stellenfleth, J., S. Lehner, and D. Hoja (2005), A parametric scheme for the retrieval of two-dimensional ocean wave spectra from synthetic aperture radar look cross spectra,
Morphological changes in coastal areas, especially in river estuaries, are of high interest in many parts of the world. Satellite data from both optical and radar sensors can help to monitor and investigate these changes. Data from both kinds of sensors being available for up to 30 years now, allow examinations over large timescales, while high resolution sensors developed within the last decade allow increased accuracy. So the creation of digital elevation models (DEMs) of, for example, the wadden sea from a series of satellite images is already possible. ENVISAT, successfully launched on March 1, 2002, continues the line of higher resolution synthetic aperture radar (SAR) imaging sensors with its ASAR instrument and now also allows several polarization modes for better separation of land and water areas. This article gives an overview of sensors and algorithms for waterline determination as well as several applications. Both optical and SAR images are considered. Applications include morphodynamic monitoring studies and DEM generation.
A noise model for synthetic aperture radar (SAR) look cross spectra (LCS) acquired over the ocean is proposed. The study is meant to contribute to the improvement of algorithms for retrieval of two dimensional ocean wave spectra from LCS.Error bars for the LCS phase, which contains information on the ocean wave phase speed and propagation direction are derived. The error estimates depent on the respective LCS coherence and the amount of smoothing applied in the LCS estimation process.A model for the LCS coherence is introduced. The first part of the model describes the dependence of the coherence on system parameters like spatial resolution. The second part is associated with the motion of the imaged ocean wave field. Decorrelation is shown to be caused by the coupling of dispersive ocean wave components in the SAR image formation process.Forward simulations for the cross spectrum coherence are carried out using parameterized swell and wind sea spectra. Coherence is estimated from a global data set of reprocessed ERS-2 wave mode data and compared to theory.
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