Increasing the accessibility of acoustic data through global access and imagery
Author(s) -
Carrie C. Wall,
J. Michael Jech,
S. J. McLean
Publication year - 2016
Publication title -
ices journal of marine science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.348
H-Index - 117
eISSN - 1095-9289
pISSN - 1054-3139
DOI - 10.1093/icesjms/fsw014
Subject(s) - sonar , seabed , computer science , water column , raw data , bathymetry , data collection , remote sensing , column (typography) , environmental science , oceanography , geography , geology , telecommunications , artificial intelligence , statistics , mathematics , frame (networking) , programming language
The National Oceanographic and Atmospheric Administration (NOAA) uses water column sonar data to assess physical and biological characteristics from the ocean surface to the seabed. Acoustic surveys produce large volumes of data that can deliver valuable information beyond their original collection purpose if the data are properly managed, discoverable, and accessible to the public. NOAA's National Centers for Environmental Information, in partnership with NOAA's National Marine Fisheries Service and the University of Colorado, have created a national archive for water column sonar data to help achieve these goals. Through these efforts, over 21 TB of sonar data are now publicly available. Raw sonar files are difficult to interpret due to their size, complexity, and proprietary format. In order for users to understand the quality and composition of large volumes of archived data more easily, several visualization products were explored. Three processing methods were applied to multifrequency single-beam data (Simrad EK60) collected off the US northwest coast between 2007 and 2013. One method illustrates these complex data in a single image using a novel colour scale [multifrequency single-beam imaging (MFSBI)], another examines the nautical area scattering coefficients between two frequencies (ΔNASC), and the third indices the data into acoustic classifications [multifrequency indicator (MFI)]. The ability to apply the algorithms efficiently to multiyear datasets was explored. MFSBI proved effective at conveying the composition of the data and was easily adaptable to automated processing. ΔNASC, which required manual seabed corrections, illustrated a generalized pattern for changes in the water column across the shelf. MFI provided an empirically based statistical approach but will require more effort in the near term to evaluate and assess the accuracy and precision of each classification. Overall, spatio-temporal patterns of the acoustic backscatter identified large interannual variations in composition with the continental shelf break often playing a key role in attracting biological assemblages.
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