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Gloaguen, Pierre; Mahevas, Stephanie; Rivot, Etienne; Woillez, Mathieu; Guitton, Jerome; Vermard, Youen; Etienne, Marie-pierre. |
The understanding of the dynamics of fishing vessels is of great interest to characterize the spatial distribution of the fishing effort and to define sustainable fishing strategies. It is also a prerequisite for anticipating changes in fishermen's activity in reaction to management rules, economic context, or evolution of exploited resources. Analyzing the trajectories of individual vessels offers promising perspectives to describe the activity during fishing trips. A hidden Markov model with two behavioral states (steaming and fishing) is developed to infer the sequence of non-observed fishing vessel behavior along the vessel trajectory based on Global Positioning System (GPS) records. Conditionally to the behavior, vessel velocity is modeled with an... |
Tipo: Text |
Palavras-chave: Hidden Markov model; Vessels dynamics; RECOPESCA; Autoregressive process; Baum-Welch algorithm. |
Ano: 2015 |
URL: https://archimer.ifremer.fr/doc/00179/29049/27485.pdf |
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