Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning
Published 2016 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning
Authors
Keywords
-
Journal
PLoS One
Volume 11, Issue 7, Pages e0158248
Publisher
Public Library of Science (PLoS)
Online
2016-07-02
DOI
10.1371/journal.pone.0158248
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Ending hide and seek at sea
- (2016) Douglas J. McCauley et al. SCIENCE
- solaR: Solar Radiation and Photovoltaic Systems withR
- (2015) Oscar Perpiñán Journal of Statistical Software
- Mapping Fishing Effort through AIS Data
- (2015) Fabrizio Natale et al. PLoS One
- Deriving high-resolution spatiotemporal fishing effort of large-scale longline fishery from vessel monitoring system (VMS) data and validated by observer data
- (2014) Shui-Kai Chang et al. CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES
- Using hidden Markov models to infer vessel activities in the snow crab (Chionoecetes opilio) fixed gear fishery and their application to catch standardization
- (2014) Colin Charles et al. CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES
- Global Priorities for Marine Biodiversity Conservation
- (2014) Elizabeth R. Selig et al. PLoS One
- Vessel Pattern Knowledge Discovery from AIS Data: A Framework for Anomaly Detection and Route Prediction
- (2013) Giuliana Pallotta et al. Entropy
- Effects of a large-scale and offshore marine protected area on the demersal fish assemblage in the Southwest Atlantic
- (2012) D. Alemany et al. ICES JOURNAL OF MARINE SCIENCE
- Satellite AIS – Developing Technology or Existing Capability?
- (2012) J. Carson-Jackson JOURNAL OF NAVIGATION
- Mapping species richness and human impact drivers to inform global pelagic conservation prioritisation
- (2011) Rowan Trebilco et al. BIOLOGICAL CONSERVATION
- A hidden Markov model approach for determining vessel activity from vessel monitoring system data
- (2011) David Peel et al. CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES
- Fishing activity of tuna purse seiners estimated from vessel monitoring system (VMS) data
- (2011) Nicolas Bez et al. CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES
- Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models
- (2010) Youen Vermard et al. ECOLOGICAL MODELLING
- A pioneer validation of a state-space model of vessel trajectories (VMS) with observers’ data
- (2010) E. Walker et al. ECOLOGICAL MODELLING
- Developing reliable, repeatable, and accessible methods to provide high-resolution estimates of fishing-effort distributions from vessel monitoring system (VMS) data
- (2010) J. Lee et al. ICES JOURNAL OF MARINE SCIENCE
- Integrating vessel monitoring systems (VMS) data with daily catch data from logbooks to explore the spatial distribution of catch and effort at high resolution
- (2010) H. Gerritsen et al. ICES JOURNAL OF MARINE SCIENCE
- Satellite-based vessel Automatic Identification System: A feasibility and performance analysis
- (2010) Miguel A. Cervera et al. INTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS AND NETWORKING
- A Global Map of Human Impact on Marine Ecosystems
- (2008) Benjamin S. Halpern et al. SCIENCE
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search