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Abstrakt
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.
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- Wersja publikacji
- Accepted albo Published Version
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Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
- Opublikowano w:
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HYDROACOUSTICS
strony 113 - 120,
ISSN: 1642-1817 - Język:
- angielski
- Rok wydania:
- 2017
- Opis bibliograficzny:
- Łubniewski Z., Sęk D.: On Algorithm Details in Multibeam Seafloor Classification// HYDROACOUSTICS. -., iss. 20 (2017), s.113-120
- Bibliografia: test
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więcej (11) mniej
- Preston, J. M.: Automated acoustic seabed classification of multibeam images of Stanton Banks. Applied Acoustics 70 (2009), 1277-1287. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- Canepa, G., Berro, C.: Characterization of seafloor geoacoustic properties from multibeam data. Proceedings of the OCEANS'06 MTS/IEEE Conference, Boston, 2006, 1-6. otwiera się w nowej karcie
- K. Siemes: Establishing a sea bottom model by applying a multi-sensor acoustic remote sensing approach. PhD thesis, Delft University of Technology, 2011.
- 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.
- 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. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- Geological chart of the Baltic Sea bottom. Państwowy Instytut Geologiczny, Warszawa, 1992. otwiera się w nowej karcie
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 101 razy