A preliminary study on seabed classification using a scientific echosounder
1
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Acoustics are increasingly regarded as a remote-sensing tool that provides the basis for classifying and mapping ocean resources including seabed classification. It has long been understood that details about the character of the seabed (roughness, sediment type, grain-size distribution, porosity, and material density) are embedded in the acoustical echoes from the seabed. This study developed a sophisticated yet easy-to-use technique to discriminate seabed characteristics using a split beam echosounder. Acoustic survey was conducted in Tongyeong waters, South Korea in June 2018, and the verification of acoustic seabed classification was made by the Van Veen grab sampler. The acoustic scattering signals extracted the seabed hardness and roughness components as well as various seabed features. The seabed features were selected using the principal component analysis, and the seabed classification was performed by the K-means clustering. As a result, three seabed types such as sand, mud, and shell were discriminated. This preliminary study presented feasible application of a sounder to classify the seabed substrates. It can be further developed for characterizing marine habitats on a variety of spatial scales and studying the ecological characteristic of fishes near the habitats.
Abstract
Acoustics are increasingly regarded as a remote-sensing tool that provides the basis for classifying and mapping ocean resources including seabed classification. It has long been understood that details about the character of the seabed (roughness, sediment type, grain-size distribution, porosity, and material density) are embedded in the acoustical echoes from the seabed. This study developed a sophisticated yet easy-to-use technique to discriminate seabed characteristics using a split beam echosounder. Acoustic survey was conducted in Tongyeong waters, South Korea in June 2018, and the verification of acoustic seabed classification was made by the Van Veen grab sampler. The acoustic scattering signals extracted the seabed hardness and roughness components as well as various seabed features. The seabed features were selected using the principal component analysis, and the seabed classification was performed by the K-means clustering. As a result, three seabed types such as sand, mud, and shell were discriminated. This preliminary study presented feasible application of a sounder to classify the seabed substrates. It can be further developed for characterizing marine habitats on a variety of spatial scales and studying the ecological characteristic of fishes near the habitats.
참고문헌 (25)
- Ali R. Amiri-Simkooei, "Principal Component Analysis of Single-Beam Echo-Sounder Signal Features for Seafloor Classification", IEEE Journal of Oceanic Engineering, 36(2), pp.259~272 (2011), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- Anderson JT, "Acoustic seabed classification of marine physical and biological landscapes", ICES Coop Res Rep, 286, pp.1~183 (2007)
- Berthold T, "Seabed sediment classification of side-scan sonar data using convolutional neural networks", IEEE Sym Ser on Comp Int, pp.1~8 (2017)
- K.B. Briggs, "Fine-scale sedimentary structure: implications for acoustic remote sensing", Marine Geology, 182(1-2), pp.141~159 (2002), Elsevier BV[DOI]
- Chang JK, "Seabed classification using the K-L(Karhunen-Love)transform of chirp acoustic profiling data : an effective approach to geoacoustic modeling", J Kor Soc Oce, 3(3), pp.158~164 (1998)
- J.S. Collier, "Correlation of sidescan backscatter with grain size distribution of surficial seabed sediments", Marine Geology, 214(4), pp.431~449 (2005), Elsevier BV[DOI]
- "Help file 9.0.18 for Echoview" (2018)[URL]
- Fauziyah, "Measurement and analysis of acoustic backscattering strength for characteristics of seafloor substrate in Indian Ocean WPP 572-573", IOP Conf Ser Earth Environ Sci, 162, pp.12~24 (2018)[DOI]
- Rosa Freitas, "Acoustic seabed classification of marine habitats: studies in the western coastal-shelf area of Portugal", ICES Journal of Marine Science, 60(3), pp.599~608 (2003), Oxford University Press (OUP)[DOI]
- John A. Goff, "Seabed characterization on the New Jersey middle and outer shelf: correlatability and spatial variability of seafloor sediment properties", Marine Geology, 209(1-4), pp.147~172 (2004), Elsevier BV[DOI]
- L.J. Hamilton, "Acoustic seabed segmentation for echosounders through direct statistical clustering of seabed echoes", Continental Shelf Research, 31(19-20), pp.2000~2011 (2011), Elsevier BV[DOI]
- Heald GJ, "An analysis of the 1st and 2nd backscatter for seabed classification", Proc. 3rd Eur Conf on Und Acoust, 2, pp.649~654 (1996)
- Katsnelson B, "Lowfrequency sound propagation and substrate characterization in Lake Kinnerat", Proc Ins Acoust, 37(1), pp.102~109 (2015)
- 김길영, "측심기의 음향반사 특성을 이용한 해저퇴적물의 원격분류: 부산 수영만의 예비결과", 한국수산과학회지, 35(3), pp.273~281 (2002), 한국수산과학회
- Lee GH, "The acoustic diversity of the seabed based on the similarity index computed from chirp seismic data", ICES J Mar Sci, 66, pp.227~236 (2009)[DOI]
- Pierre Legendre, "Rapid Communication", Communication RapideAcoustic seabed classification: improved statistical method, 2002, pp.59(7), 1085~1089[DOI]
- Lied TT, "SEABEC-a single beam echosounder, seabed classification system", MTS, Techno-Ocean 4, pp.2004, 4[DOI]
- I MACDONALD, "Thermal and visual time-series at a seafloor gas hydrate deposit on the Gulf of Mexico slope", Earth and Planetary Science Letters, 233(1-2), pp.45~59 (2005), Elsevier BV[DOI]
- Acoustic techniques for seabed classification, "Penrose JD", Coop Res Centre, 1~118, pp.Tech Rep 32 (2005)
- Daniel Rodríguez-Pérez, "A pulse-length correction to improve energy-based seabed classification in coastal areas", Continental Shelf Research, 77, pp.1~13 (2014), Elsevier BV[DOI]
- Dick G. Simons, "A Multivariate Correlation Analysis of High- Frequency Bottom Backscattering Strength Measurements With Geotechnical Parameters", IEEE Journal of Oceanic Engineering, 32(3), pp.640~650 (2007), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- Dick G. Simons, "A Bayesian approach to seafloor classification using multi-beam echo-sounder backscatter data", Applied Acoustics, 70(10), pp.1258~1268 (2009), Elsevier BV[DOI]
- Siwabessy J, "Seabed habitat classification", Shallow Survey '99. Int Conf on High Res Surveys in Shallow Water, pp.1~81 (1999)
- Jarosław Tęgowski, "Acoustical classification of the bottom sediments in the southern Baltic Sea", Quaternary International, 130(1), pp.153~161 (2005), Elsevier BV[DOI]
- Claudia Wienberg, "Acoustic seabed classification in a coastal environment (outer Weser Estuary, German Bight)—a new approach to monitor dredging and dredge spoil disposal", Continental Shelf Research, 25(9), pp.1143~1156 (2005), Elsevier BV[DOI]