On algorithm details in multibeam seafloor classification

• Autorzy: Łubniewski Z. , Sęk D.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

seafloor classification; multibeam sonar; sonar data processing

• Wydawca: Polskie Towarzystwo Akustyczne. Oddział Gdański
• Czasopismo: Hydroacoustics
• Rocznik: 2017
• Tom: Vol. 20
• Strony: 113--120
• Opis fizyczny: Bibliogr. 11 poz., rys., tab.

Twórcy

autor

Łubniewski Z.

• Gdańsk University of Technology Faculty of Electronics, Telecommunications and Informatics Department of Geoinformatics Gdańsk, Narutowicza 11/12, Poland

autor

Sęk D.

• Gdańsk University of Technology Faculty of Electronics, Telecommunications and Informatics Department of Geoinformatics Gdańsk, Narutowicza 11/12, Poland

Bibliografia

• [1] Preston, J. M.: Automated acoustic seabed classification of multibeam images of Stanton Banks. Applied Acoustics 70 (2009), 1277–1287.
• [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.
• [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.
• [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.
• [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.
• [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.
• [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 10th 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.
• [10] Z. Łubniewski, A. Chybicki, “Using angular dependence of multibeam echo features in seabed classification”, Proceedings of the 9th European Conference on Underwater Acoustics, Paris, 717-722, 2008.
• [11] Geological chart of the Baltic Sea bottom. Państwowy Instytut Geologiczny, Warszawa, 1992.

Uwagi

PL

Opracowanie w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).