한수지 49(6), , 2016 Original Article Korean J Fish Aquat Sci 49(6), ,2016 음향산란층의식별을위한에코그램분석방법의비교 최석관 윤은아 1 * 한인우 1 오우석 1 국립수산과학원원양자원과, 1 전남

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1 한수지 49(6), , 2016 Original Article Korean J Fish Aquat Sci 49(6), ,2016 음향산란층의식별을위한에코그램분석방법의비교 최석관 윤은아 1 * 한인우 1 오우석 1 국립수산과학원원양자원과, 1 전남대학교수산과학과 Comparison of Echogram Analysis Methods for Evaluating the Sound-scattering Layer Seok-Gwan Choi, Eun-A Yoon 1 *, Inwoo Han 1 and Wooseok Oh 1 Distant Water Fisheries Resources Research Division, National Institute of Fisheries Science, Busan 46083, Korea 1 Department of Fisheries Science, Chonnam National University, Yeosu 59626, Korea This study compared the density of fish determined using three different echogram methods: the frequency-difference, time variable, and threshold modification methods. An acoustic survey was conducted off the coast of Jeju Island after sunset. Data at 38 and 120 khz frequencies were collected using a commercial fishing vessel. As a reference point, the value of MVBS kHz that distinguished fish from zooplankton using the 38 and 120 khz frequencies was set at < 2 db. The estimated density of fish along the survey line was , , and m 2 / nmi 2 using the frequency difference, time variable threshold, and threshold modification methods, respectively. The results of this study constitute basic research for estimating fish densities. Key words: Acoustic survey, Frequency difference method, Time variable threshold method, Threshold modification method 서론,,.,. (Kang et al., 2008; Hwang et al., 2004; Lee et al., 2015). (echo counting) (echo integration).,.. (Simmonds and MacLennan, 2005)..,. (Hone and Jeck, 1999), 2 (Miyashita et al., 1997; Kang, 2002; Kloser et al., 2002; McKelvey and Wilson, 2006; Kim et al., 2013; Lee et al., 2014)., (Lee et al., 2012; Hwang et al., 2015). (threshold modification), Kang et al. (2012). Korean J Fish Aquat Sci 49(6) , December 2016 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial Licens ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Received 15 November 2016; Revised 21 November 2016; Accepted 21 November 2016 *Corresponding author: Tel: Fax: address: euna7979@nate.com Copyright 2016 The Korean Society of Fisheries and Aquatic Science 856 pissn: , eissn:

2 음향산란층의식별을위한에코그램분석방법비교 khz 2,,. 음향자료수집 재료및방법. split beam 38 khz 120 khz (EK60, Simrad), 1 m khz 1 ping/s, ms, 6-7 DGPS. 음향자료분석 (Echoview V 4.7, Myriax). 150 m,., De Robertis and Higginbottom (2007) Wang et al. (2015). Fig. 1. TVT (Time varied threshold) raw data. data range bitmap (Volume Backscattering Strength, SV), SV mask (De Robertis and Higginbottom, 2007)., data range bitmap,. erosion filter 3 3, erosion filter 999 db.,. dilation filter dilation filter 7 7 data range bitmap SV mask. median 7 7 select mask median 7 7 SV Fig. 1. Flow diagram for noise removal using acoustic analyze software algorithms. data range bitmap, (Wang et al., 2015). Fig. 1 (frequency difference method), (time variable threshold method), (threshold modification method) khz 120 khz (Mean Volume Backscattering Strength, MVBS). 5 ping 1 m. data range bitmap 38 khz mask, 38 khz. (Fig. 2). (Kang, 2012). dilation filter 7 7 (Fig. 3).. 3 raw SV 80~ 30 db

3 858 최석관ㆍ윤은아ㆍ한인우ㆍ오우석 Fig. 2. Data process flow for discriminating fish using db difference method at 38 and 120 khz.,, TVT 60~-30 db. 0.5 n.mile EDSU (Elementary Distance Sampling Unit) (Nautical Area Scattering Coefficient, NASC, m 2 /n.mile 2 ). 통계분석 3, Fig. 3. Data process flow for discriminating fish using TVT method at 38 khz (Kang, 2012)., (SPSS ver. 21.0, IBM) t-test. 결과및고찰 Fig khz raw. Fig khz, 120 khz. De Robertis and Higginbottom (2007) Wang et al. (2015) Fig. 4. Comparison of noise removal and raw echograms.

4 음향산란층의식별을위한에코그램분석방법비교 859 Fig. 5. The db-difference of section of only zooplankton and mixed zooplankton and fish using 38 and 120 khz..,,.,. Park et al. (2015) Lee et al. (2015), SV 1 db..,. Fig khz 38 khz Fig. 6. Range of db difference to identify zooplankton and fish db, 10 db

5 860 최석관ㆍ윤은아ㆍ한인우ㆍ오우석 Fig. 7. Exampled of echograms to identify zooplankton and fish using MVBS method. Fig. 8. Correlation relationship of mean NASC (m 2 /nmi 2 ) by transect lines using frequency difference method, time variable threshold method, and threshold modification method.. 14~18 db, 2 db 10 db. Fig. 6. MVBS kHz 2 db., MVBS kHz <2 db, 38 khz (Fig. 6). Fig. 7,,.,, Fig m 2 /nmi 2, m 2 /nmi 2, m 2 /nmi 2. T-, (P>0.05), (P>0.05), (P<0.05). SV SV (Target strength, TS). SV TS, TS SV,

6 음향산란층의식별을위한에코그램분석방법비교 861 SV.. 사사 2016 (R ),,. References De Robertis A and Higginbottom I A post-processing technique to estimate the signal-to noise ratio and remove echosounder background noise. ICES J Mar Sci 64, Horne JK and Jech JM Multi-frequency estimates of fish abundance: constraints of rather high frequencies. ICES J Mar Sci 56, jmsc Hwang BK, Lee YW, Jo HS, Oh JK and Kang MH Visual census and hydro-acoustic survey of demersal fish aggregations in Ulju small scale marine ranching area (MRA), Korea. J Kor Soc Fish Technol 51, org/ /ksft Hwang DJ, Park JS and Lee YW Estimation of fish school abundance by using an echo sounder in an artificial reef area. J Kor Fish Soc 37, org/ /kfas Kang DH, Im YJ, Lee CW, Yoo JT and Myoung JG Hydroacoustic survey of spatio-temporal distribution of demersal fish aggregations near the west coast of Jeju island, Korea. Ocean and Polar Research 30, org/ /opr Kang MH Acoustic method for discriminating plankton from fish in Lake Dom Helvecio of Brazil using a time varied threshold. J Kor Soc Fish Tech 48, dx.doi.org/ /ksft Kang, MH. Furusawa M and Miyashita K Effective and accurate use of difference in mean volume backscattering strength to identify fish and plankton. ICES J Mar Sci 59, Kim JI, Hwang BK, Lee YW, Lee KH, Shin HO and Lim JN Application of hydro-acoustic survey technique for abundance estimation of juvenile cod (Gadus macrocephalus) in Jinhae bay, Korea. J Kor Soc Fish Tech 49, Lee HB, Choi SG, Lee KH, Lee JB, Lee JH and Choi JH A study on noise removal technique for acoustic data from a fishing boat. J Kor Soc Fish Technol 51, dx.doi.org/ /ksft Lee HB, Kang DH, Im YJ and Lee KH Distribution and abundance of Japanese anchovy Engraulis japonicus and other fishes in Asan Bay, Korea, estimated hydroacoustic survey. Korean J Fish Aquat Sci 47, org/ /kfas Lee HB, Seo YI, Oh TY, Choi JH, Jo HS and Choi KH Distribution of Demersal Fish Based on a Combined Acoustic and Trawl Survey during Day and Night in Costal of the South Sea, Korea. Korea J Fish Aquat Sci 48, Lee JB, Oh TY, Yeon IJ, Kim BY, Shin HO, Hwang BK, Lee KH and Lee YW Estimation of demersal fish biomass using hydroacoustic and catch data in the marine ranching area (MRA) of Jeju. J Kor Soc Fish Tech 48, McKelvey DR and Wilson CD Discriminant classification of fish and zooplankton backscattering at 38 and 120 khz. Transact American Fish Soc 135, dx.doi.org/ /t Miyashita, K, Aoki I, Seno K, Taki K and Ogishima T Acoustic identification of isada krill, Euphausia pacifica Hansen, off the Sanriku coast, north-eastern Japan. Fish Oceanogr 6, Park JS, Lee JH, Kim DN, Park YG, Jang CS, Park BS and Kang MH Efficient eliminating methods of noises imbedded acoustic signals. J Kor Soc Fish Technol 51, /ksft Simmonds J and MacLennan D Fisheries acoustic theory and practice. Blackwell Science, Oxford, Wang X, Zhao X, and Zhang J A noise removal algorithm for acoustic data with strong interference based on post-processing techniques. CCAMLR SG-ASAM-15/02: 11pp.

422 이형빈ㆍ윤상철ㆍ임양재ㆍ김정년ㆍ김맹진ㆍ최광호. ( ) (Simmonds and McLennan, 2002). (Von Szalay et al., 2007; Zwolinski et al., 2012; Kang et al., 2015)..,,.. 재료및방법 2016

422 이형빈ㆍ윤상철ㆍ임양재ㆍ김정년ㆍ김맹진ㆍ최광호. ( ) (Simmonds and McLennan, 2002). (Von Szalay et al., 2007; Zwolinski et al., 2012; Kang et al., 2015)..,,.. 재료및방법 2016 한수지 50(4), 421-428, 2017 Original Article Korean J Fish Aquat Sci 50(4),421-428,2017 음향기법을이용한동계독도주변해역매오징어 (Watasenia scintillans) 및기타어군의분포및현존량산정 이형빈 * 윤상철 1 임양재 2 김정년 2 김맹진 최광호 국립수산과학원서해수산연구소, 1 국립수산과학원독도연구센터,