The 75% that vanished: what satellites found when they stopped trusting AIS
In January 2024 a landmark study mapped two petabytes of satellite radar and found that roughly three-quarters of the world's industrial fishing vessels never appear in public tracking. It is the single clearest proof that AIS alone is not enough.
For: Government, analysts, ESG, science
Every so often a single result reorganises how a field sees itself. For maritime analytics, that result arrived in January 2024, in the pages of Nature: a map showing that most of the industrial activity on the ocean had been invisible the whole time.
The finding
A team led by Global Fishing Watch, with academic partners, processed roughly two petabytes of satellite imagery collected between 2017 and 2021 and applied deep learning to it. The headline is stark: around 72-76% of the world’s industrial fishing vessels do not appear in public tracking, and more than a quarter of transport and energy vessel activity is likewise absent from public AIS.
Roughly three-quarters. The system the world had quietly come to treat as its picture of maritime activity was, for industrial fishing, showing about a quarter of the truth.
The study also mapped what had been hidden: concentrations of untracked fishing off parts of Asia and Africa, and the rapid offshore build-out of energy infrastructure, including wind. It is the most complete map of human activity at sea ever assembled — and it exists only because the researchers stopped assuming AIS told the whole story.
How you find a ship that isn’t broadcasting
The method is the point. AIS is a cooperative sensor: it works only when a vessel chooses to broadcast. To see the vessels that do not, the study leaned on a non-cooperative one — synthetic aperture radar (SAR) from the Copernicus Sentinel-1 satellites.
SAR is active radar: it supplies its own illumination, so it images the sea surface in any weather, day or night, and it detects a steel hull whether or not that hull is broadcasting anything. Cross-reference the radar detections against AIS, and the gap between them is the dark fleet: every vessel that shows up in the imagery but not in the transponder data.
Deep-learning models did the heavy lifting at scale — detecting vessels in the radar scenes, classifying them, and distinguishing fishing from transport and energy activity across five years of global coverage. This is precisely the AIS-gap-to-SAR fusion we describe in how to detect a vessel that has turned off its AIS, executed at planetary scale.
Why it is the canonical result
We cite this study more than any other, because it settles an argument. Anyone selling maritime intelligence has to answer one question: is your picture the real one, or just the cooperative one? Before 2024, that was a debate. After it, it is a measured fact — AIS alone misses the majority of industrial fishing vessels — and any analysis, any enforcement regime, any sustainability claim built on AIS by itself is quietly working from a minority of the data.
The implications run straight through everything else on this site:
- For enforcement and fisheries agencies, it means IUU fishing — an estimated tens of billions of dollars a year in losses — is mostly happening out of sight of the primary tool used to police it. Closing that gap is the core of maritime domain awareness.
- For sanctions and risk, it confirms that a determined vessel can stay dark, and that catching it requires fusion, not faith in the transponder — the same logic behind shadow-fleet detection.
- For anyone modelling the ocean economy, it means the baseline was wrong, and the corrected baseline is only visible through fused sensing.
The takeaway
The study’s lasting contribution is not a number, though the number is memorable. It is a discipline: treat AIS as one input, not the truth. The ocean is far busier than the transponders admit, and the busy parts are disproportionately the ones that do not want to be seen. Reading them requires fusing cooperative and non-cooperative data — which is, in one sentence, the whole reason an AI-native, fusion-first approach exists.
Three-quarters of the fishing fleet was hiding in plain sight. It took a change of instrument to notice.
Sources: Paolo et al., “Satellite mapping reveals extensive industrial activity at sea,” Nature (January 2024); Global Fishing Watch press materials and SAR detection releases (Jan 2024); Copernicus Sentinel-1 documentation. Figures as reported by the study.
Frequently asked
What did the 2024 Nature study on dark fishing vessels find? +
Published in Nature in January 2024 by Global Fishing Watch and partners, the study analysed about two petabytes of satellite imagery from 2017-2021 with machine learning and found that roughly 72-76% of the world's industrial fishing vessels are not publicly tracked, and that more than a quarter of transport and energy vessel activity is also absent from public AIS. It is the most complete map to date of industrial activity at sea.
How did the study find vessels that were not broadcasting AIS? +
By using synthetic aperture radar (SAR) from the Copernicus Sentinel-1 satellites, which detects vessel hulls directly in any weather, day or night, regardless of whether a transponder is on. Cross-referencing radar detections with AIS revealed the "dark" vessels present in the imagery but absent from public tracking, and deep-learning models classified them and mapped their activity globally.
Why does dark fishing matter? +
Because you cannot manage what you cannot see. Illegal, unreported and unregulated (IUU) fishing depletes stocks, undercuts legal fishers and costs an estimated tens of billions of dollars a year. If most industrial fishing vessels are invisible to public tracking, then policy, enforcement and sustainability efforts built on AIS alone are working from a fraction of the real picture.