TAIWAN TO DEVELOP FISHING GROUND FORECATS

Taiwan turns to AI and satellites to predict where fish will gather

A new four-year project will combine decades of fishing records, satellite imagery and ocean data to help Taiwanese fishing fleets spend less time searching for fish—and potentially transform how commercial fishing is done.

TAIPEI — Taiwan is preparing to bring artificial intelligence, satellite observation and ocean science into one of its oldest industries, launching a new system designed to forecast where productive fishing grounds are likely to form.

The project, scheduled to begin in 2027, will combine historical catch records with satellite imagery and oceanographic data—including sea temperature, ocean color and seawater acidity—to identify environmental patterns associated with fish distribution. Taiwan News reported the plan based on reports from CNA and UDN.

The goal is straightforward: help fishermen find productive waters before they spend large amounts of time and fuel searching for them.

From experience to data-driven fishing

For decades, fishing-ground selection has depended heavily on the experience of captains and crews. Taiwan's Fisheries Agency says the country possesses extensive historical fishery data across the western and central Pacific, providing a potentially valuable foundation for predictive models.

Under the planned system, researchers will compare historical catches with satellite and ocean conditions to identify recurring relationships between environmental changes and fish locations.

The initial information is expected to be made available primarily to Taiwanese fishing fleets, although officials have indicated that the technology could eventually be offered commercially to international users if the data and forecasting system meet market requirements.

The project comes as Taiwan's fishing industry faces mounting pressure

The push toward predictive fishing comes at a difficult time for the industry.

Taiwan's fishing output was about NT$96.5 billion (US$3.05 billion) in 2025, according to figures cited by Taiwan News. Agriculture Minister Chen Chun-ji has also put the broader value of the fishing-related industry chain at roughly NT$350 billion.

UDN reported that officials are increasingly concerned about the combined effects of extreme weather, declining marine resources and an aging fishing workforce. The newspaper said the government plans to spend about NT$100 million a year for four years on the research effort.

That means the project is about more than simply finding fish faster. It is also an attempt to make fishing operations more efficient as climate and ocean conditions become harder to predict.

Taiwan has already experimented with fishing forecasts

The idea is not entirely new.

Taiwan's Fisheries Research Institute has previously worked on fishing-condition prediction using environmental information. One project aimed to help squid fishermen identify productive fishing areas, with the potential to reduce search time, fuel consumption and carbon emissions.

International research has likewise demonstrated that satellite observations and environmental variables can be used to model potential fishing zones. Scientific studies have examined factors such as sea-surface temperature, ocean productivity and other environmental conditions to estimate where particular species are more likely to concentrate.

The new Taiwanese initiative, however, seeks to scale this concept by combining large historical catch datasets, satellite imagery and multiple ocean variables with AI-based analysis.

Pacific cooperation could expand the system

Taiwan also sees potential for cooperation beyond its own fishing fleets.

Taiwan News reported that Agriculture Ministry officials have discussed possible cooperation with Australia and Pacific island countries, while the wider project is intended to use Taiwan's extensive western and central Pacific fishery data.

That could eventually give the technology a wider regional role, particularly as Pacific fisheries confront changing ocean conditions and increasing pressure on marine resources.

But officials have not said that AI will be able to pinpoint fish with absolute certainty. The system is intended to identify probable fishing grounds based on patterns in historical and environmental data—a forecast, rather than a guarantee of a catch.

Why this matters

If successful, the technology could change a fundamental part of commercial fishing: the search itself.

A more accurate forecast could mean fewer hours spent looking for productive waters, lower fuel consumption and potentially more efficient fishing operations.

For an industry facing higher operating pressures and increasingly unpredictable marine conditions, that could prove to be one of Taiwan's most important experiments in applying AI outside the technology sector.

And the bigger question is no longer whether satellites can see changes in the ocean.

It is whether AI can turn those changes into a reliable map of where the fish will be next.

WWC ONE MEDIA G.A