Plankton biomass estimation using multi-frequency sonar

The internship seeks to develop an acoustic classification algorithm that estimates the organism composition and density of plankton. A series of experiments have been conducted using trawl nets where a four-frequency sonar device was pointed across the net openings. The catch from each trawl survey is broken down into an estimate of the relative composition of different organisms. This internship involves relating the known catch to the corresponding acoustic measurements of that catch. Essentially, the objective of the internship is to develop an algorithm which will allow a sonar device to produce estimates of the types and densities of plankton in the part of the ocean that is being surveyed. The partner organization (Haida Salmon Restoration Corporation) would benefit from this internship by having an enhanced ability to predict salmon returns by being able to monitor the amount of food (plankton) available to the salmon. An acoustic classification algorithm would allow for plankton estimates to be conducted inexpensively using underwater robots that can operate in a wide range of weather conditions.

Intern: 
Steve Pearce
Faculty Supervisor: 
Dr. John Bird
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