The data we publish reflects performance on real fishing trips, not lab tests. Our model combines oceanographic data with field observations to generate actionable predictions.
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SPATIAL RESOLUTION
0.05° · ~5 km × 5 km per cell
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TIME HORIZON
Up to 14 days ahead
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UPDATE FREQUENCY
Daily · maps updated every day
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REGIONAL COVERAGE
NE Atlantic · Grand Sole · Mediterranean
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TRAINING DATA
Thousands of validated commercial trips
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VALIDATION
Multi-year prospective test, no data leakage
Validated performance on real fishing trips
Validated on years the model never saw during training. The zones the model marks as best consistently catch significantly more than those it marks as worst.
Top 10% vs Bottom 10%
1.70× CPUE ratio
prospective test
Active zones > 0.63
60% accuracy
trips 2022–2026
Winning months
22 out of 33
temporal test
// Pipeline
01
Oceanographic data
Bottom and surface temperature, chlorophyll, oxygen, nitrate, salinity and depth. Sources: Copernicus Marine Service, EMODnet.
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Validated fishing data
Thousands of real commercial trips with verified catches, covering multiple years and regions of the NE Atlantic.
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Habitat suitability
Static habitat suitability mask for Merluccius merluccius from EMODnet, at 0.05° resolution.
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Predictive CPUE model
Machine learning model trained on oceanographic variables and fishing data. Validated prospectively: the zones the model prioritizes consistently catch more than those it discards, in most analyzed months.