Mapping Bathymetry from Multi-source Remote Sensing Images: a Case Study in the Beilun Estuary, Guangxi, China

This article examines several major bathymetry mapping methods and describes an experimental procedure of determining seabed bathymetry from multi-source passive remote sensing data. Issues to be addressed include how to deal with less desirable spectral data quality and the absence of in-situ water depth measurements. A case study was presented using DigitalGlobe QuickBird and Landsat-7 ETM+ multispectral images of different dates and spatial resolutions to determine water depth for the Beilun Estuary, China. The preliminary results have led to three findings. First, it was feasible to use the tidal water line derived from the nearinfrared bands as a good approximation of water surface when observed tidal data is absent. Second, the reflectance ratio transform model developed by Stumpf et al. was proven suitable for spectrally-based water depth estimation when in-situ data is absent. Finally, the data quality problem caused by thin clouds could be effectively removed by fusing remote sensing images of two different sources.