The interactive map shows a near real-time view of the fishing patterns of individual vessels and fleets. The team used machine learning technology to analyze 22 billion messages publicly broadcasted from vessels’ AIS positions from 2012 to 2016.


Based on vessel movement patterns, the Global Fishing Watch algorithm identified more than 70,000 commercial fishing vessels, the sizes and engine powers of these vessels, what type of fishing they engaged in, and when and where they fished down to the hour and kilometer.

More than 40 million hours of fishing activity was observed in 2016, and while most nations appeared to fish within their own exclusive economic zones, China, Spain, Taiwan, Japan and South Korea accounted for 85% of the observed fishing on the high seas.

The team also discovered that when and where fishing happens are tied more to politics and culture than to natural cycles such as fish migrations and marine food production.

Christopher Costello, a professor at UCSB’s Bren School of Environmental Science & Management, said:

Our analysis demonstrated that policies, cultures and economics play a huge role in driving fishing behavior.