Automatic cleaning of MultiBeam EchoSounder (MBES) bathymetric datasets is a critical issue in data processing especially with the objective of nautical charting. A number of approaches have already been investigated in order to provide solution in views of operationally reaching this still challenging problem. This paper aims at providing a comprehensive and structured overview of existing contributions in the literature. For this purpose, a taxonomy is proposed to categorize the whole set of automatic and semi-automatic methods addressing MBES data cleaning. The non-supervised algorithms that compose the majority of the methods developed in the hydrographic field, are mainly described according to both the features of the bathymetric data and the type of outliers to detect. Based on this detailed review, past and future developments are discussed in light of both implementation and test on datasets and metrics used for performances assessment.

This work aims at providing geoscientists with a new robust shape transform that performs the estimation of a smooth submarine intra-sediment shape from Multi-Beam Echo Sounders data. This shape matches a virtual geodesic interface between mobile and immobile sand, called an osculatory surface. The transform operates through only two non-optional parameters: its scale length and the corresponding degree of the local representations. Application tests addressing different tidal sandbanks are described. Applications to the osculatory tracking of two monitoring zones over fifteen years are also included.