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Satellite-Based Fishing Fleet Tracking: A New Foundation for Fisheries Science and Management
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DOI：10.1111/faf.70103.png)
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Abstract
En 中文
Satellite-based vessel-tracking technologies have ushered in a new era for monitoring fishing activity at scale. By combining artificial intelligence (AI) methods with remotely-sensed data, researchers can now detect, classify and analyse fishing behaviour across vast and previously unobservable ocean regions. Technological advancements in vessel tracking are rapidly reshaping fisheries science and management, enabling new insights into fleet behaviour and its effects on marine ecosystems. This review synthesizes the state of the science in AI-enabled vessel tracking and highlights its transformative potential across four core domains: stock assessment and catch reconstruction, effort controls, spatial management, and monitoring, control, and surveillance. We explore how satellite-based vessel-tracking data complement legacy systems such as logbooks and observers, while also unlocking new capabilities to track ‘dark vessels’ that are not publicly observable by other means. We also identify key scientific and institutional challenges that are priorities for advancing the scientific frontier, including: filling data gaps for small-scale fleets, resolving uncertainty in behavioural inference and vessel identities for dark fleets, integrating catch and effort reporting, expanding real-time decision support, designing cutting-edge policy instruments to manage fisheries and developing shared standards for algorithm transparency and validation. As the field matures, we propose a forward-looking agenda to ensure that fleet tracking delivers on its promise to enhance transparency, support real-time decision-making and drive more inclusive, science-based ocean governance.
Keywords:
artificial intelligence (AI)
dark fleet
fishing effort
real-time monitoring, control and surveillance
satellite-based earth observation
vessel detection
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