Fisheries and Aquatic Sciences

The Korean Society of Fisheries and Aquatic Science (한국수산과학회)
권호 표지
DOI QR코드

DOI QR Code

The Application of Image Processing Technology for the Analysis of Fish School Behavior: Evaluation of Fish School Behavior Response to the Approaching Vessel Using Scanning Sonar

  • Lee Yoo-Won (Department of Marine Production System Engineering, Pukyong National University) ;
  • Mukai Tohru (Laboratory of Marine Environment and Resource Sensing, Graduate School of Fisheries Sciences, Hokkaido University) ;
  • Iida Kohji (Laboratory of Marine Environment and Resource Sensing, Graduate School of Fisheries Sciences, Hokkaido University) ;
  • Hwang Doo-Jin (Department of Fisheries Science and Technology, Yosu National University) ;
  • Shin Hyeong-Il (Department of Marine Production System Engineering, Pukyong National University)
  • Published : 2002.09.01
Download PDF
⟨ Previous Next ⟩

Abstract

The response behavior of a fish school to an approaching vessel was observed using scanning sonar. The evaluation using six parameters, which signify characteristics of school shape and behavior by sonar image processing, was proposed. Ten fish schools were analyzed and among them, three fish schools were identified for their changing shape, swimming direction, and swimming speed. Moreover, by tracing fish schools on stack of sonar images, these fish schools were seen to exhibit an apparent change of school shape and behavior. Therefore, the evaluation method of fish school behavior using six characteristic parameters indicating fish school shape and behavior by sonar image processing is useful.

Keywords

References

  1. Fr$\'{e}$on, P., F. Gerlotto and O.A. Misund. 1993a. Consequences of fish behaviour for stock assessment. ICES mar. Sci. Symp., 196, 190-195
  2. Fr$\'{e}$on, P., F. Gerlotto and M. Soria. 1993b. Variability of Harensula spp. school reactions to boats or predators in shallow water. ICES mar. Sci. Symp., 196, 30-35
  3. Fr$\'{e}$on, P., F. Gerlotto and M. Soria. 1992. Changes in school structure according to external stimuli: Description and influence on acoustic assessment. Fisheries Res., 15, 45-66 https://doi.org/10.1016/0165-7836(92)90004-D
  4. Gerlotto, F., M. Soria and P. Fr$\'{e}$on. 1999. From two dimensions to three: The use of multibeam sonar for a new approach in fisheries acoustics. Can. J. Fish. Aquat. Sci., 56, 6-12 https://doi.org/10.1139/cjfas-56-1-6
  5. Hafsteinsson, M.T. and O.A. Misund. 1995. Recording the migration behaviour of fish schools by multi-beam sonar during conventional acoustic surveys. ICES J. Mar. Sci., 52, 915-924 https://doi.org/10.1006/jmsc.1995.0088
  6. Iida, K., T. Mukai and N. Horiuchi. 1998. Three dimensional analysis of distribution and shape of pelagic/mesopelagic fish school using scanning sonar. J. Mar. Acoust. Soc. Jpn., 25, 240-249 (in Japanese) https://doi.org/10.3135/jmasj.25.240
  7. Misund, O.A. 1990. Sonar observations of schooling herring: School dimensions, swimming behaviour, and avoidance of vessel and purse seine. Rapp. P.-v. R$\'{e}$un. Cons. int. Explor. Mer, 189, 135-146
  8. Misund, O.A. 1993a. Dynamics of moving masses: variability in packing density, shape, and size among herring, sprat, and saithe schools. ICES J. Mar. Sci., 50, 145-160 https://doi.org/10.1006/jmsc.1993.1016
  9. Misund, O.A. 1993b. Avoidance behaviour of herring (Clupea hareagus) and mackerel (Scomber scombrus) in purse seine capture situations, fisheries Res., 16, 179-194 https://doi.org/10.1016/0165-7836(93)90051-8
  10. Misund, O.A., A. Aglen and E. Fr$\phi$nass. 1995. Mapping the shape, size, and density of fish schools by echo integration and a high-resolution sonar. ICES J. Mar. Sci., 52, 11-20 https://doi.org/10.1016/1054-3139(95)80011-5
  11. Misund, O.A., A. Aglen, S.$\phi$. Johanessen, D. Skagen and B. Totland. 1993. Assessing the reliability of fish density estimates by monitoring the swimming behaviour of fish schools during acoustic surveys. ICES Mar. Sci. Symp., 196, 202-206
  12. Nero, R.W. and J.J. Magnuson. 1989. Characterization of patches along transects using high-resolution 70-kHz integrated acoustic data. Can. J. Fish. Aquat. Sci., 46, 2056-2064 https://doi.org/10.1139/f89-254
  13. Olsen, K. 1990. Fish behaviour and acoustic sampling. Rapp. P.-v. R$\'{e}$un. Cons. int. Explor. Mer, 189, 147-158
  14. Olsen, K., J. Angell, F. Pettersen and A. L$\phi$vik. 1983. Observed fish reactions to a surveying vessel with special reference to herring, cod, capelin and polar cod. FAO Fish. Rep., 300, 131-138
  15. Ona, E. and O. R. God$\phi$. 1990. Fish reaction to trawling noise: The significance for trawl sampling. Rapp. P.-v. R$\'{e}$eun. Cons. int. Explor. Mer, 189, 159-166
  16. Scalabrin, C. and J. Mass$\'{e}$. 1993. Acoustic detection of the spatial and temporal distribution of fish shoals in the Bay of Biscay. Aquat. Living Resour., 6, 269-283 https://doi.org/10.1051/alr:1993027
  17. Soria, M., P. Fr$\'{e}$on and F. Gerlotto. 1996. Analysis of vessel influence on spatial behaviour of fish schools using a multi-beam sonar and consequences for biomass estimates by echo-sounder. ICES J. Mar. Sci., 53, 453-458 https://doi.org/10.1006/jmsc.1996.0064
  18. Traynor, JJ., NJ. Williamson and W.A. Karp. 1990. A consi deration of the accuracy and precision of fish-abundance estimates derived from echo-integration surveys. Rapp. P.-v. R$\'{e}$un. Cons. int. Explor. Mer, 189, 101-111
  19. Weill, A., C. Scalabrin and N. Diner. 1993. MOVIES-B: an acoustic detection description software-application to shoal species' classification. Aquat. Living Resour., 6, 255-267 https://doi.org/10.1051/alr:1993026