On Algorithm Details in Multibeam Seafloor Classification - Publication - Bridge of Knowledge

Search

On Algorithm Details in Multibeam Seafloor Classification

Abstract

Remote sensing of the seafloor constitutes an important topic in exploration, management, protection and other investigations of the marine environment. In the paper, a combined approach to seafloor characterisation is presented. It relies on calculation of several descriptors related to seabed type using three different types of multibeam sonar data obtained during seafloor sensing, viz.: 1) the grey-level sonar images (echograms) of the 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 proposed methodology has been tested using field data records acquired from several bottom types in the Southern Baltic Sea. Using the examples of particular parameters, the influence on the specific manner and details regarding their calculation, i.e. the size of the applied current local window to a sonar image, on the obtained classification performance, is discussed.

Cite as

Full text

download paper
downloaded 18 times
Publication version
Accepted or Published Version
License
Creative Commons: CC-BY-NC-SA open in new tab

Keywords

Details

Category:
Articles
Type:
artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Published in:
HYDROACOUSTICS pages 113 - 120,
ISSN: 1642-1817
Language:
English
Publication year:
2017
Bibliographic description:
Łubniewski Z., Sęk D.: On Algorithm Details in Multibeam Seafloor Classification// HYDROACOUSTICS. -., iss. 20 (2017), s.113-120
Bibliography: test
  1. Preston, J. M.: Automated acoustic seabed classification of multibeam images of Stanton Banks. Applied Acoustics 70 (2009), 1277-1287. open in new tab
  2. Hellequin, L., Boucher, J.-M., Lurton, X.: Processing of high-frequency multibeam echo sounder data for seafloor characterization. IEEE Journal of Oceanic Engineering 28(1) (2003), 78-89. open in new tab
  3. Amiri-Simkooei, A. R., Snellen, M., Simons, D. G.: Riverbed sediment classification using multi-beam echo-sounder backscatter data. Journal of the Acoustic Society of America 126 (4) (2009), 1724-1738. open in new tab
  4. Siemes, K., Snellen, M., Simons, D. G., Hermand, J.-P.: Using MBES backscatter strength measurements for assessing a shallow water soft sediment environment. Proceedings of the IEEE OCEANS Conference, Bremen, 2009. open in new tab
  5. D. Stephens, M. Diesing: A Comparison of Supervised Classification Methods for the Prediction of Substrate Type Using Multibeam Acoustic and Legacy Grain-Size Data. PLoS One, 9(4): e93950, 2014. Published online 2014 Apr 3, doi: 10.1371/journal.pone.0093950. open in new tab
  6. Canepa, G., Berro, C.: Characterization of seafloor geoacoustic properties from multibeam data. Proceedings of the OCEANS'06 MTS/IEEE Conference, Boston, 2006, 1-6. open in new tab
  7. K. Siemes: Establishing a sea bottom model by applying a multi-sensor acoustic remote sensing approach. PhD thesis, Delft University of Technology, 2011.
  8. Z. Łubniewski, A. Stepnowski, A. Chybicki, "Seafloor characterisation combined approach using multibeam sonar echo signal processing and image analysis", Proceedings of the 10 th European Conference on Underwater Acoustics, Istanbul, 131-137, 2010.
  9. A. Stepnowski, Z. Łubniewski, "Combined Method of Multibeam Sonar Signal Processing and Image Analysis for Seafloor Classification", Proceedings of the 2011 Symposium on Ocean Electronics, Kochi, 63-69, 2011. open in new tab
  10. Z. Łubniewski, A. Chybicki, "Using angular dependence of multibeam echo features in seabed classification", Proceedings of the 9 th European Conference on Underwater Acoustics, Paris, 717-722, 2008. open in new tab
  11. Geological chart of the Baltic Sea bottom. Państwowy Instytut Geologiczny, Warszawa, 1992. open in new tab
Verified by:
Gdańsk University of Technology

seen 101 times

Recommended for you

Meta Tags