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Surficial Sediment Classification using Backscattered Amplitude Imagery of Multibeam Echo Sounder(300 kHz)  

Park, Yo-Sup (UST21)
Lee, Sin-Je (UST21)
Seo, Won-Jin (UST21)
Gong, Gee-Soo (Petroleum & Marine Resources Research division, Korea institute of Geoscience and Mineral Resources)
Han, Hyuk-Soo (Department of Oceanography, Chungnam National University)
Park, Soo-Chul (Department of Oceanography, Chungnam National University)
Publication Information
Economic and Environmental Geology / v.41, no.6, 2008 , pp. 747-761 More about this Journal
Abstract
In order to experiment the acoustic remote classification of seabed sediment, we achieved ground-truth data(i.e. video and grab samples, etc.) and developed post-processing for automatic classification procedure on the basis of 300 kHz MultiBeam Echo Sounder(MBES) backscattering data, which was acquired using KONGBERG Simrad EM3000 at Sock-Cho Port, East Sea of South Korea. Sonar signal and its classification performance were identified with geo-referenced video imagery with the aid of GIS (Geographic Information System). The depth range of research site was from 5 m to 22.7 m, and the backscattering amplitude showed from -36dB to -15dB. The mean grain sizes of sediment from equi-distanced sampling site(50 m interval) varied from 2.86$(\phi)$ to 0.88(\phi). To acquire the main feature for the seabed classification from backscattering amplitude of MBES, we evaluated the correlation factors between the backscattering amplitude and properties of sediment samples. The performance of seabed remote classification proposed was evaluated with comparing the correlation of human expert segmentation to automatic algorithm results. The cross-model perception error ratio on automatic classification algorithm shows 8.95% at rocky bottoms, and 2.06% at the area representing low mean grain size.
Keywords
multibeam; backscatter; GIS; grain size; classification;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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1 Claudio Lo Iacono,, Eulalia Gracia, Susana Diez, Graziella Bozzano, Ximena Moreno, Juanjo Danobeitia and Belen Alonso (2007) Seafloor characterization and backscatter variability of the Almeria Margin(Alboran Sea, SW Mediterranean) based on high-resolution acoustic data, Marine Geology, doi:10.1016/j.margeo.2007.11.004. (In press)
2 Cutter, G.R. Jr., Rzhanov, Y. and Mayer, L.A. (2003) Automated segmentation of seafloor bathymetry from multibeam echosounder data using local Fourier histogram texture features. Journal of Experimental Marine Biology and Ecology, v. 285-286, p. 355-370   DOI   ScienceOn
3 Roberts, J.M., Brown, C.J., Long, D.C. and Bates, R. (2005) Acoustic mapping using a multibeam echosounder reveals cold-water coral reefs and surrounding habitats, Coral Reef, v. 24, p. 654-669   DOI
4 06Kong, G.S., Kim, S.P., Park, Y.S., Min, G.H., Kim, J.U. and Park, S.C. (2006) Correlation of Simrad EM950 (95 kHz) Multibeam Backscatter Strength with Surficial Sediment Properties in the Sand Ridge of the Eastern Yellow Sea, Econ. Environ. Geol., v. 39, p. 719-738   과학기술학회마을
5 Medialdea, T., Somoza L., Leon R., M. Farran, Ercill G., Maestro A., Casas D.,. Llave E., Hernandez-Molina F.J., Fernandez-Pug M.C., and Alonso B. (2007) Multibeam backscatter as a tool for sea-floor characterization and identification of oil spills in the Galicia Bank, Mar. Geol, v. 249, p. 93-107   DOI   ScienceOn
6 Oliveira Jr. A. M. and Hughes Clarke, J. E. (2007) Recovering wide angular sector multibeam backscatter to facilitate seafloor classification, United States Hydrographic Conference Norfolk, VA, May
7 Luciano Fonsenca and Larry Mayer (2007) Remote estimation of surficial seafloor properties through the application Angular Range Analysis to multibeam sonar data, Mar Geophys Res., v. 28, p. 119-126   DOI
8 Ingram, R.L. (1971) Sieve analysis. In : Procedures in sedimentary Petrology, editied by Carver, R.E. Willey- Inter Science, New York, p. 49-67
9 Intelmann, S.S., Cutter, G.R. and Beaudoin, J.D. (2007) Automated, objective texture segementation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast. Marine Sanctuaries Conservation Series MSD-07-05. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Sanctuary Program, Silver Spring, MD. 31p
10 Hughes Clarke, J.E., Mayer, L.A. and Wells, D. (1996) Shallow-water imaging multibeam sonars: A new tool for investigating seafloor processes in the coastal zone and on the continental shelf. Marine Geophysical Researches, Vol. 18, p. 607-629   DOI
11 Lee, J.H., Yoon, K.S., La, H.S. and Na, J.Y. (2004) Distribution of Seagrass(Zostera marina) Beds and High Frequency Backscattering Characteristics by Photosynthesis, J. Acoust. Soc. Kor., v. 23, p. 562-569   과학기술학회마을
12 Beyer, A., Charkraboty, B. and Schenke, H.W. (2007) Seafloor classification of the mound and channel provinces of the Porcupine Seabight: and application of the multibeam angular backscatter data, Int J Earth Sci (Geol Rundsch). v. 96, p. 11-20   DOI
13 Park, C., Seong, W., Gerstoft, P. and Siderius, M. (2003) Time-domain geoacoustic inversion of high-frequency chirp signal from simple towed system, IEEE J. Oceanic Eng., Vol. 28, p. 468-478   DOI   ScienceOn
14 Hamilton, E.L., Shumway, G., Menard, H.W. and Shipek, C.J. (1956) Acoustic and physical properties of shallow- water sediments off San Diego. J. Acoust. Soc. Am. v. 28, p. 1-15   DOI
15 Chakraborty, B. and Kodagali, V.N. (2004) Characterizing Indian Ocean manganese nodule-bearing seafloor using multi-beam angular backscatter, Geo-Marine Letters, v. 24, p. 8-13   DOI
16 L.J. Hamilton (2005) A bibliography of acoustic seabed classification, Cooperative Research Centre for Coastal Zone, Estuary & Waterway Management, Technical Report No.27
17 Dietmar R., Muller, R. and Sian Eagles (2007) Mapping Seabed Geology by Ground-Truthed Textural Image/ Neural Network Classification of Acoustic Backscatter Mosaics, Math Geol. v. 39, p. 575-592   DOI
18 Joe Breman, Dawn Wright, and Patrick N. Halpin (2002) The Inception of the ArcGIS Marine Data Model, Marine Geography, GIS for the Oceans and Seas, ESRI press, p. 3-10
19 La, H.S., Yoon, K.S. and Na, J.Y. (2005) Characteristics of High Frequency Backscattering Strength by Zostera Marina(Seagrass) Bed, J. Acoust. Soc. Kor., v. 24, p. 97-102   과학기술학회마을
20 KORDI (1991) A study of the Acoustic Characteristics of the Sediments of the Korean Seas(III), BSPG00075- 229-5
21 Kim, G.Y., Kim, D.C., Kim, Y.E., Lee, K.H., Park, S.C., Park, J.W. and Seo, Y.K. (2002) Remote Seabed Classification Based on the Characteristics of the Acoustic Response of Echo Sounder:Preliminary Result of the Suyoung Bay, Busan, J. Korean Fish. Soc., v. 35, p. 273-282
22 Cho, J.S., Yoon, K.S., Park, S.S., Na, J.Y., Suk, D.W. and Joo, J.Y. (2004) Seafloor Classification Using Fuzzy Logic, J. Acoust. Soc. Kor., 23(4), p. 296-302   과학기술학회마을
23 Folk, R.L. and Ward, W.C. (1957) Brazos River bar: A study in the significance of grain size parameters. J. Sediment. Preol., v. 27, p. 3-26   DOI
24 Gary Cholwek, John Bonde, Xing Li, Carl Richards and Karen Yin (2000) Processing Roxann sonar data to improve its categorization of lake bed surficial substrates, Marine Geophysical Researches, v. 21, p. 409- 421   DOI   ScienceOn