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A hidden Markov model approach for determining vessel activity from vessel monitoring system data.

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Peel, D. and Good, N.M. (2011) A hidden Markov model approach for determining vessel activity from vessel monitoring system data. Canadian Journal of Fisheries and Aquatic Sciences, 68 (7). pp. 1252-1264.

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Article Link: http://dx.doi.org/10.1139/f2011-055

Publisher URL: http://www.nrcresearchpress.com


Many fisheries worldwide have adopted vessel monitoring systems (VMS) for compliance purposes. An added benefit of these systems is that they collect a large amount of data on vessel locations at very fine spatial and temporal scales. This data can provide a wealth of information for stock assessment, research, and management. However, since most VMS implementations record vessel location at set time intervals with no regard to vessel activity, some methodology is required to determine which data records correspond to fishing activity. This paper describes a probabilistic approach, based on hidden Markov models (HMMs), to determine vessel activity. A HMM provides a natural framework for the problem and, by definition, models the intrinsic temporal correlation of the data. The paper describes the general approach that was developed and presents an example of this approach applied to the Queensland trawl fishery off the coast of eastern Australia. Finally, a simulation experiment is presented that compares the misallocation rates of the HMM approach with other approaches.

Item Type:Article
Corporate Creators:Department of Employment, Economic Development & Innovations (DEEDI), Agri-Science, Fisheries and Aquaculture
Business groups:Animal Science
Additional Information: © Copyright 2011 Canadian Science Publishing
Keywords:Spatial-distribution; commercial catch; fishing effort; trawl fishery; Australia; intensity.
Subjects:Aquaculture and Fisheries > Fisheries > Fishery resources
Aquaculture and Fisheries > Fisheries > Fishery technology
Live Archive:24 Nov 2011 07:10
Last Modified:03 Sep 2021 16:49

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