Stock Assessment

Stock assessments are critical for the management of marine and freshwater resources, and Echoview® was originally designed for this purpose in close collaboration with the world's leading fisheries research institutes. Echoview supports the most commonly used fisheries echosounder and sonar data formats, and provides an unrivalled wealth of powerful yet easy-to-use tools, algorithms and operators for quantitative acoustics.

As the industry standard, Echoview allows you to:

  • Explore and calibrate your data
  • Account for noise and other artifacts
  • Define distance/time/ping-based cells
  • Detect aggregations (schools detection) and/or single echoes (single target detection)
  • Track single echoes (fish tracking)
  • Define the bottom depth
  • Partition and filter your data any way you choose
  • Classify your data (e.g. species identification) either manually and/or based on user-defined rules (e.g. multifrequency dB difference, school characteristics)
  • Characterize your processed data (both on-screen and in export files) from an extensive range of analysis variables (e.g. mean Sv, NASC, number of targets, bottom depth etc.)

Echosounder data from a Norwegian fjord showing a 5km-long school of herring in the upper 150 m of the water column and dispersed (single) fish targets below (click to enlarge)

Case Study:

Species identification in the Black Sea using multifrequency echosounder data

Client
Dr. Serdar Sakinan and Dr. Ali Cemal Gücü - Middle East Technical University in Turkey


“Echoview and in particular the variety of tools that its virtual echogram module offers, turned the complex processing sequences into, fast, simple and easy to handle steps.”

Dr. Serdar Sakinan


Background
Automated species identification via the classification of backscatter measurements from echosounders and sonars “remains the ‘Holy Grail’ to acoustic researchers” (Horne 2000). The lack of physical samples is a well-known shortcoming of acoustic data and presents researchers with a data-processing challenge.

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