Scientific collaboration to support a sustainable ocean
Advances in machine learning and satellite technologies can transform human management of the ocean, but taking advantage of these technologies requires effective partnerships and an interdisciplinary team.
At Global Fishing Watch, we connect machine learning experts with leaders in the scientific community to produce new datasets, publish impactful research and empower others to use our data.
Our collaborations contribute to discoveries and solutions critical to marine conservation, global economics and human welfare. These partnerships help us better understand the role commercial fishing plays in the physical, biological, economic and political factors of the ocean and ensures that we are addressing the most urgent ocean challenges.
Results generated from these collaborations can be found on our publications page.
Resources
In this video, research partners Kristina Boerder of Dalhousie University and Quentin Hanich of the University of Wollongong, speak to the value of Global Fishing Watch data to support research into pressing questions in fisheries research.
Research Partners
Recent Work
New Horizons for Peru’s Squid Fishery
Peruvian vessel monitoring system is shining a light on the large artisanal squid fleet in the Southeast Pacific Ocean, Peru’s second most important fishery. Peru recognizes the value of transparency to improve the monitoring and
Transparent Ocean Data Can Drive Digital Innovation to Reveal Human Activity at Sea
Global Fishing Watch partners with the Food and Agriculture Organization of the United Nations in Decade of Ocean Science to bring digital innovation to fisheries monitoring Commercial fishing is vital to the food security, livelihoods
A Call for Collaboration to Tackle Forced Labor in Fishing
Satellite technology can offer cost-effective solutions to ocean governance, but stakeholders must work together to be successful Forced labor is used in fishing fleets around the world—a fact that is becoming known all too well.
Systematic Data Analysis Reveals False Vessel Tracks
Analysis of tracking data from automatic identification system broadcasts reveals vessel locations have been simulated for a number of ships, including military vessels. This false information could compromise vessel safety, decrease confidence in a crucial