Shallow water depth retrieval from space-borne SAR imagery

Based on shallow water bathymetry synthetic aperture radar (SAR) imaging mechanism and the microwave scattering imaging model for oceanic surface features, we developed a new method for shallow water depth retrieval from space-borne SAR images. The first guess of surface currents and winds are estimated from the normalized radar crossing section (NRCS) profile of shallow water bathymetry SAR imagery, according to the linear theory and geophysical model function. The NRCS profile is then simulated by the microwave scattering imaging model. Both the surface currents and winds are adjusted by using the dichotomy method step by step to make the M4S-simulated NRCS profiles approach those observed by SAR. Then, the surface currents and the wind speeds are retrieved when a best fit between simulated signals and the SAR image appears. Finally, water depths are derived using the Navier-Stokes equation and finite difference method with the best estimated currents and the surface winds. The method is tested on two SAR images of the Taiwan Shoal. Results show that the simulated shallow water NRCS profile is in good agreement with those measured by SAR with the correlation coefficient as high as 85%. In addition, when water depths retrieved from the SAR image are compared with in situ measurements, both the root mean square and relative error are less than 3.0 m and 6.5%, respectively, indicating that SAR images are useful for shallow water depth retrieval and suggesting that the proposed method in this paper is convergent and applicable.