Determining depth from remotely-sensed images

Remotely-sensed images can provide synoptic or nearly synoptic data for large areas of the sea surface. Photographic and, more recently, radar measurement techniques can resolve the pattern of waves on the water surface and can provide a very dense sampling of kinematical variables of interest, ranging from a complete picture of the wave phase (in the case of single photographs) to horizontal velocity components at the water surface resulting from wind, tides, or waves (in the case of advanced radar techniques). When applied in the coastal zone, these images contain surface waves that are propagating over a complex bottom bathymetry and current field, and that are affected by a combination of shoaling, refraction, diffraction and nonlinear processes. This paper examines two methods to determine bathymetry from surface elevation information. The first is to examine the ability of linear dispersion relationship models to determine bathymetry, in cases with refraction and diffraction, and the second, based on lagged correlation method (and several images), is more generally useful for application.