A Semiautomated Approach to Estimating Fish Size, Abundance, and Behavior from Dual-Frequency Identification Sonar (DIDSON) Data

Abstract We present a semiautomated analytical approach incorporating both image and acoustic processing techniques to apply to dual-frequency identification sonar (DIDSON) data. Our objectives were (1) to develop a standardized analysis pathway in order to reduce the effort associated with counting, measuring, and tracking fish targets; and (2) to empirically obtain estimates of basic target information (e.g., size, abundance, speed, and direction of travel). Analyses were conducted on DIDSON data collected at three different locations (the Kenai River, Alaska; Mobile River, Alabama; and Port Fourchon, Louisiana) with different equipment and deployment configurations. We developed an efficient postprocessing approach that can be applied to a variety of data sets, independent of user and deployment method. For two of the three data sets analyzed, the estimates of fish abundance derived from DIDSON analyses were not significantly different from the manual counts of DIDSON files. The analyses produced estim...

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