Skip to main content

Evaluation of a digital echo sounder system for detection of submersed aquatic vegetation

Estuaries volume 25, pages 133–141 (2002)Cite this article

Abstract

A technique is presented for rapid detection of submersed aquatic vegetation (SAV) using a high-frequency, high-resolution digital echo sounder linked with global positioning system equipment. The acoustic reflectivity of SAV allows for detection and explicit meaqsurement of canopy geometry using a digital signal processing algorithm described here. Comparing output data from this system with physical measurements shows good detection and measurement performance over a wide range of conditions for freshwater tape grass (Vallisneria americana) and seagrasses (Thalassia testudinum, Halodule wrightii, andSyringodium filiforme) in a sandy-bottom, south Florida estuary. The range of environmental conditions for which the system can be used is defined. Based on these measured performance data and a review of existing literature, this system appears to fill a gap in the inventory of established methods for measuring the distribution and abundance of submersed macrophytes.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Literature Cited

  • Acker, W. C., J. Burczynski, J. Dawson, J. Hedgepeth, andD. Wiggins. 1999. Digital transducers: A new sonar technology.Sea Technology 40:31–35.

    Google Scholar 

  • Ackleson, S. G. andV. Klemas. 1987. Remote sensing of submerged aquatic vegetation in lower Chesapeake Bay: A comparison of Landsat MSS to TM imagery.Remote Sensing of Environment 22:235–248.

    Article  Google Scholar 

  • Andrews, D. S., D. H. Webb, and A. L. Bates. 1984. The use of aerial remote sensing in quantifying submersed aquatic macrophytes, p. 92–99.In W. M. Dennis and B. G. Isom (eds.), Ecological Assessment of Macrophyton: Collection, Use, and Meaning of Data. American Society for Testing and Materials. Special Technical Publication 843. Philadelphia, Pennsylvania.

  • Armstrong, R. A. 1993. Remote sensing of submerged vegetation canopies for biomass estimation.International Journal of Remole Sensing 14:621–627.

    Article  Google Scholar 

  • Breedlove, B. W., and W. M. Dennis. 1984. The use of small-format aerial photography in aquatic macrophyton sampling, p. 100–110.In W. M. Dennis and B. G. Isom (eds.), Ecological Assessment of Macrophyton: Collection, Use, and Meaning of Data. American Society for Testing and Materials. Special Technical Publication 843. Philadelphia, Pennsylvania.

  • Chamberlain, R. H. and P. H. Doering. 1998. Preliminary estimate of optimum freshwater inflow to the Caloosahatchee estuary: A resource based approach, p. 121–130.In S. F. Treat (ed.), Proceedings of the 1997 Charlotte Harbor Public Conference and Technical Symposium. South Florida Water Management District and Charlotte Harbor National Estuary Program, Technical Report No. 98-02. Washington, D.C.

  • Chivers, R. C., N. Emerson, andD. R. Burns. 1990. New acoustic processing for underway surveying.The Hydrographic Journal 56:9–15.

    Google Scholar 

  • Congalton, R. G. 1991. A review of assessing the accuracy of classification for remotely sensed data.Remote Sensing of Environment 37:35–46.

    Article  Google Scholar 

  • Dennis, W. M. 1984. Aquatic macrophyton sampling: An overview, p. 2–6.In W. M. Dennis and B. G. Isom (eds.), Ecological Assessment of Macrophyton: Collection, Use, and Meaning of Data. American Society for Testing and Materials. Special Technical Publication 843. Philadelphia, Pennsylvania.

  • Duarte, C. M. 1987. Use of echosounder tracing to estimate the aboveground biomass of submersed plants in lakes.Canadian Journal of Fisheries and Aquatic Science 44:732–735.

    Article  Google Scholar 

  • Duda, R. O. andP. E. Hart. 1973. Patteern Classification and Scene Analysis. John Wiley and Sons, New York.

    Google Scholar 

  • Edsall, T. A., T. E. Behrendt, G. Cholwek, J. W. Frey, G. W. Kennedy, and S. B. Smith. 1997. Use of remote-sensing techniques to survey the physical habitat of large rivers. U.S. Geological Survey, Contribution number 983 of the Great Lakes Science Center, Ann Arbor, Michigan.

  • Fonseca, M. S. andJ. S. Fisher. 1986. A comparison of canopy friction and sediment movement between four species of seagrass with seference to their ecology and restoration.Marine Ecology Progress Series 29:15–22.

    Article  Google Scholar 

  • Hundley, A. 1994. Report on the use of an acoustic method for mapping seagrass density and location. Report No. 940401. Offshore Scientific Services, New South Wales, Australia.

    Google Scholar 

  • Kemp, W. M., W. R. Boynton, R. R. Twilley, J. C. Stevenson, andL. G. Ward. 1984. Influence of submersed vascular plants on ecological processes in upper Chesapeake Bay, p. 367–394.In V. S. Kennedy (ed.), The Estuary as a Filter. Academic Press, New York.

    Google Scholar 

  • Kirkman, H. 1990. Seagrass distribution and mapping, p. 19–25.In R. C. Phillips and C. P. McRoy (eds.), Seagrass Research Methods. United Nations Educational, Scientific and Cultural Organization, Paris.

    Google Scholar 

  • Lee Long, W. J., A. J. Hundley, C. A. Roder, andL. J. McKenzie. 1998. Preliminary evaluation of an acoustic technique for mapping tropical seagrass habitats. Research Publication No. 52, Great Barrier Reef Marine Park Authority, Townsville.

    Google Scholar 

  • Logsdon, T. 1992. The NAVSTAR Global Positioning System. Van Nostrand Reinhold Press, New York.

    Google Scholar 

  • Lubbers, L., W. R. Boynton, andW. M. Kemp. 1990. Variations in structure of estuarine fish communities in relation to abundance of submersed vascular plants.Marine Ecology Progress Series 65:1–14.

    Article  Google Scholar 

  • Maceina, M. J. andJ. V. Shireman. 1980. The use of a recording fathometer for determination of distribution and biomass of hydrilla.Journal of Aquatic Plant Management 18:34–39.

    Google Scholar 

  • Maceina, M. J., J. V. Shireman, K. A. Langeland, andD. E. Canfield. 1984. Prediction of submerged plant biomass by use of a recording fathometer.Journal of Aquatic Plant Management 22:35–38.

    Google Scholar 

  • MacLennan, D. andJ. Simmonds. 1992. Fisheries acoustics. Chapman and Hall Co., New York.

    Google Scholar 

  • Macleod, R. D. andR. G. Congalton. 1998. A quantitative comparison of change-detection algorthims for monitoring eelgrass from remotely sensed data.Photogrammetric Engineering and Remote Sensing 64:207–216.

    Google Scholar 

  • Madsen, J. D. 1993. Biomass techniques for monitoring and assessing control of aquatic vegetation.Lake and Reservoir Management 7:141–154.

    Google Scholar 

  • Miner, S. P. 1993. Application of acoustic hydrosurvey technology to the mapping of eelgrass (Zostera marina) distribution in Humboldt Bay, California. Coastal Zone '93. Proceedings of the 8th Symposium on Coastal and Ocean Management, July 19–23, 1993, New Orleans, Louisiana.

  • Moreno, A., P. Siljestrom, andJ. Rey. 1998. Benthic phanerogam species recognition in side scan sonar images: Importance of the sensor direction, p. 173–178.In A. Alippi and G. B. Cannelli (eds.), Proceedings 4th European Conference on Underwater Acoustics, Rome. Italian National Research Council, Rome Italy.

    Google Scholar 

  • Murphy, L., T. Leary, andA. Williamson. 1995. Standardized seabed classification techniques.Sea Technology 36(7):15–19.

    Google Scholar 

  • Norris, J. G., S. Wyllie-Echeverria, T. Mumford, A. Baily, andT. Turner. 1997. Estimating basal area coverage of subtidal seagras beds using underwater videography.Aquatic Botany 58:269–287.

    Article  Google Scholar 

  • Orth, R. J., R. L. Ferguson, andK. D. Haddad. 1991. Monitoring seagrass distribution and abundance patterns, p. 281–300.In H. S. Bolton (ed.), Proceedings of Coastal Zone '91. American Society of Civil Engineers, New York.

    Google Scholar 

  • Sabol, B., and J. Burczinski. 1998. Digital echo sounder system for characterizing vegetation in shallow-water environments, p. 165–171.In A. Alippi and G. B. Cannelli (eds.), Proceedings 4th European Conference on Underwater Acoustics, Rome.

  • Sabol, B., E. McCarthy, andK. Rocha. 1997. Hydroacoustic basis for detection and characterization of eelgrass, p. I-679–I-693,In Proceedings of Fourth Conference on Remote Sensing for Marine and Coastal Environments, Orlando, Florida, 17–19 March 1997. Environmental Research Institute of Michigan. Ann Arbor, Michigan.

    Google Scholar 

  • Sabol, B. andR. E. Melton. 1996. Development of an automated system for detection and mapping of submersed aquatic vegetation with hydroacoustic and global positioning system technologies; Report 1: The Submersed Aquatic Vegetation Early Warning System (SAVEWS)—System description and user's guide (Version 1.0). Joint Agency Guntersville Project Aquatic Plant Management, TVA/WR-95-00. Tennessee Valley Authority, Knoxville, Tennessee.

    Google Scholar 

  • Sabol, B., R. E. Melton, and R. L. Kasul. 1998. Method and apparatus for hydroacoustic detection of submersed aquatic vegetation. Patent No. 5,805,525 U. S. Patent Office, Washington, D.C.

  • Spencer, D. F. andG. G. Ksander. 1998. Using videotaped transects to estimate submersed plant abundance in Fall River, California.Journal of Aquatic Plant Management 36:130–137.

    Google Scholar 

  • Spratt, J. D. 1989. The distribution and density of eelgrass,Zostera marina, in Tomales Bay, California.California Fish and Game 75:204–212.

    Google Scholar 

  • Thayer, G. W., W. J. Kenworthy, and M. S. Fonseca. 1984. The ecology of eelgrass meadows of the Atlantic Coast: A community profile. U.S. Fish and Wildlife Service Report No. FWSOBS-84/02. Washington, D.C.

  • Thomas, G. L., D. A. Marino, R. E. Thorne, andG. B. Pauley. 1984. An evaluation of fisheries sonar techniques as a tool for measuring aquatic macrophyte biomass, p. 153–157.In Proceedings 19th Annual Meeting, Aquatic Plant Control Research Program. Miscellaneous Paper A-85-4 U.S. Army Engineer Waterways Experiment Station. Vicksburg, Mississippi.

    Google Scholar 

  • Thomas, G. L., S. I. Thiesfield, S. A. Bonar, R. N. Crittenden, andG. B. Pauley. 1990. Distribution of submergent plant bed biovolume using acoustic range information.Canadian Journal of Fisheries and Aquatic Science 47:805–812.

    Article  Google Scholar 

  • Zhang, X. 1998. On the estimation of biomass of submersed vegetation using Landsat thematic mapper (TM) imagery: A case study of the Honghu Lake, PR China.International Journal of Remote Sensing 19:11–20.

    Article  Google Scholar 

  • Zieman, J. C. and R. T. Zieman. 1989. The ecology of the seagrass 0209 meadows of the west coast of Florida: A community profile. U.S. Fish and Wildlife Service Biological Report 85(7.25), 0209 023 Washington, D.C.

Download references

Author information

Authors and Affiliations

  1. U.S. Army Engineer Research and Development Center, 3909 Halls Ferry Road, 39180, Vicksburg, Mississippi

    Bruce M. Sabol & R. Eddie Melton

  2. South Florida Water Management District, 3301 Gun Club Road, 33406, West Palm Beach, Florida

    Robert Chamberlain, Peter Doering & Kathy Haunert

Authors
  1. Bruce M. Sabol
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. Eddie Melton
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Robert Chamberlain
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Peter Doering
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kathy Haunert
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bruce M. Sabol.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Sabol, B.M., Eddie Melton, R., Chamberlain, R. et al. Evaluation of a digital echo sounder system for detection of submersed aquatic vegetation. Estuaries 25, 133–141 (2002). https://doi.org/10.1007/BF02696057

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02696057

Keywords

  • Global Position System
  • False Detection
  • Submerse Aquatic Vegetation
  • Thalassia Testudinum
  • Charlotte Harbor