Determining sediment composition of coarse riverbeds using multi-beam echo-sounder backscatter and bathymetric features

The conventional approach of mapping the composition of a riverbed by taking grab samples is expensive and time consuming. The use of acoustic remote sensing techniques provides an attractive alternative due to their high spatial coverage capabilities at limited cost. In this contribution the data acquired from a multi-beam echo-sounder (MBES) system is employed to obtain information on the sediments of the Maas River in the Netherlands, which is known for its very shallow waters and very coarse riverbed. The analysis involves two phases. In the first phase, a statistical method based on the Bayes decision rule is used. It fits the maximum allowable number of Gaussian probability density functions to the histogram of the backscatter strength at a given incident angle angle. The number of Gaussians is then the number of classes. Second, the current work assesses the classification potential of a bathymetric feature, namely the residuals with respect to a fitted surface of depth.