Automatic bathymetry retrieval from SAR images

Abstract

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.

Remote Sensing Systems for Ocean: A Review (Part 2: Active Systems)

“…There are three steps to study the bottom topography using SAR imaging systems: (1) finding the connection between the OSC and underwater topographic features; (2) accurate hydrodynamic modulation of the ocean surface variations through the OSC; and (3) creating a relationship between the microwave signal and the sea surface [246]. In [247], the gridded bathymetry information was automatically derived from SAR data. They used sea state alterations in TerraSAR-X images to extract the bathymetry in shelf areas through the shoaling effect.…”

Pan-European Satellite-Derived Coastal Bathymetry—Review, User Needs and Future Services

“…Nearshore bathymetry can also be derived with this method from SAR sensors (Bian et al, 2020), such as Sentinel-1 (Sancho et al, 2018;Wiehle and Pleskachevsky, 2018), RISAT-1 (Mishra et al, 2014) or TerraSAR-X/Tandem-X (Wiehle et al, 2019) satellites, even in areas covered by clouds.…”

Methods for Satellite Derived Bathymetry From Sentinel-2 Images: A Comparison

“…In other words, these techniques are based on the interference between the electromagnetic microwaves signal coming from the satellite with the sea surface roughness that is influenced by the seabed morphology (Cloarec et al, 2016). The obtainable depths range from -10 m to -70 m, therefore the first meters (> -10 m) cannot be achieved due to effects such as wave breaking and coastal waves reflection (Wiehle et al, 2019). This is a huge limitation for shallow water derivation also accompanied by a low geometric resolution in case of free data which can go up to 100 m (Duplančić Leder et al, 2023).…”