Automatic bathymetry retrieval from SAR images

Bathymetry, the topography of the sea floor, is in high demand due to the increase in offshore constructions like wind parks. It is also an important dataset for climate change modelling, when sea level rises and changes in circulation currents are to be simulated. The retrieval of accurate bathymetry data is a cost-intensive task usually requiring a survey vessel charting the respective area. However, bathymetry can also be retrieved remotely using data from Earth observation satellites. The main point of this study is the development of a processor that allows the automatic derivation of gridded bathymetry information from spaceborne Synthetic Aperture Radar (SAR) data. Observations of sea state modifications in SAR images are used to derive the bathymetry in shelf areas using the shoaling effect, which causes wavelengths to become shorter when reaching shallower waters. The water depth is derived using the dispersion relation for surface water waves, which requires wavelength and wave period as input parameters. While the wavelength can be directly retrieved from the SAR image, for the peak period additional information and procedures are required, e.g. local measurements or complex SAR data. A method for automatically deriving the wave period for swell waves in SAR images was developed and tested in this paper. It uses depth data from public databases as initial values which are compared to derived depths iterating through possible peak periods along the calculation grid; the peak period resulting in a minimal root-mean-square deviation is then used for bathymetry calculation. The bathymetry derived from a TerraSAR-X acquisition of the Channel Islands is presented; the resulting peak wave period of 11.3 s fits well to nearby in situ measurement data.