Using principal component analysis and canonical discriminant analysis for multibeam seafloor characterisation data

pp. 123-130, vol. 15, 2012

Zbigniew Łubniewski
Gdańsk University of Technology, Department of Geoinformatics, Gdansk, Poland

Andrzej Stepnowski
Gdansk University of Technology, Department of Geoinformatics, Gdansk, Poland

Key words: 2D and 3D model of the seabed surface; bathymetry; multibeam data

Abstract: The paper presents the seafloor characterisation based on multibeam sonar data. It relies on using the integrated model and description of three types of multibeam data obtained during seafloor sensing: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive sonar beams. The classification is performed by utilisation of several statistical methods applied for analysis of a set of seafloor descriptors derived from multibeam data. In the paper, the use of Principal Component Analysis (PCA), as well as Canonical Discriminant Analysis (CDA) for reduction of the seafloor parameter space dimension is presented along with the obtained results. In addition, the use of the open source World Wind Java SDK tool for implementation of imaging and mapping of seafloor multibeam data, integrated with other elements of a scene and overlaid on rich background data, is also shown.

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© Polish Acoustical Society - Gdansk Department, Polish Academy of Sciences. This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported. (CC BY-NC-SA 3.0)