Deep Learning Applied to Satellite Imagery Reveals Untracked Ships – The Map Room

Excerpt from Fig. 2 of Paolo et al., “Satellite mapping reveals extensive industrial activity at sea,” Nature 625 (2024).

Speaking of AI-assisted global monitoring: researchers affiliated with Global Fishing Watch have revealed that the global fishing, transport and energy fleets are a lot bigger than expected. They were able to compare the locations of ships carrying AIS transponders with satellite imagery, to which deep learning was applied to classify ships. They conclude that something like three-quarters of industrial fishing vessels, and thirty percent of transport and energy vessels, go untracked. This isn’t necessarily so much about clandestine activity—in many regions ships, especially fishing boats, simply aren’t required to be tracked—but it can, among other things, reveal illegal fishing in protected areas. Results of the study were published in Nature last month. Global Fishing Watch also has an interactive map. [The Verge]

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