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Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models ArchiMer
Vermard, Youen; Rivot, Etienne; Mahevas, Stephanie; Marchal, Paul; Gascuel, Didier.
Recent advances in technologies have lead to a vast influx of data on movements, based on discrete recorded position of animals or fishing boats, opening new horizons for future analyses. However, most of the potential interest of tracking data depends on the ability to develop suitable modelling strategies to analyze trajectories from discrete recorded positions. A serious modelling challenge is to infer the evolution of the true position and the associated spatio-temporal distribution of behavioural states using discrete, error-prone and incomplete observations. In this paper, a Bayesian Hierarchical Model (HBM) using Hidden Markov Process (HMP) is proposed as a template for analyzing fishing boats trajectories based on data available from...
Tipo: Text Palavras-chave: Bayesian Hierarchical Models; Hidden Markov Model; State-space model; VMS; Fleet behaviour; Fishing effort.
Ano: 2010 URL: http://archimer.ifremer.fr/doc/00009/11993/9342.pdf
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