An automatic and quantitative approach to the detection and tracking of acoustic scattering layers (supplemental code) Public Deposited

http://ir.library.oregonstate.edu/concern/datasets/st74cv64b

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  • Matlab code is included for detecting and tracking acoustic scattering layers from processed Echoview data. Acoustic scattering layers are ubiquitous, horizontally extensive aggregations of both vertebrate and invertebrate organisms that play key roles in oceanic ecosystems. However, currently there are no conventions or widely adaptable automatic methods for identifying these often dynamic, spatially-complex features, so it is difficult to consistently and efficiently describe and compare results. This detection method can be used to monitor changes in layer depth, width, and internal structure over time. Extensive, contiguous regions of the water column that have echo strengths above a threshold were identified as "background layers". They correspond to regions of the water column that contain scattering from diffusely distributed organisms. Often, background layers contained contiguous, horizontally extensive features of concentrated acoustic scattering we identified as "strata". These features were identified by fitting Gaussian curves to the echo envelope of each vertical column of scattering, and their boundaries were identified as the endpoints of the region containing 95% of the area under the fitted curves. These endpoints were linked horizontally to make continuous tracks. Bottom and top tracks were paired to identify features that sometimes extended horizontally for tens of kilometers. By allowing a comparable, automated approach to be used across environments, this method promotes the improved classification and characterization of acoustic scattering layers necessary for examining their role in oceanic ecosystems.
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  • Cade, David E., Benoit-Bird, Kelly J. (2014): An automatic and quantitative approach to the detection and tracking of acoustic scattering layers (supplemental code). Oregon State University. Software. http://dx.doi.org/10.7267/N96Q1V56
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