Global Fishing Watch: Illegal Fishing Detection

The Challenge

Illegal, unreported, and unregulated (IUU) fishing costs the global economy $23 billion annually and threatens marine ecosystems worldwide. Overfishing has depleted 90% of large fish populations since 1950. Traditional monitoring relies on human observers on boats (expensive and dangerous) or occasional patrol vessels (easily evaded). The ocean is vast—covering 71% of Earth's surface—making comprehensive surveillance seemingly impossible. Protected marine areas are frequently violated with little chance of detection or enforcement.

The AI Solution: Global Fishing Watch

Technology: AI-powered vessel tracking and behavior analysis system

Developed by: Collaboration between Google, Oceana, and SkyTruth (non-profit organizations)

How it works:

• Tracks vessels using Automatic Identification System (AIS) transponders (required on commercial fishing vessels)
• AI analyzes vessel movement patterns to identify fishing behavior
• Detects suspicious activities: vessels in protected areas, unauthorized night fishing, trans-shipment (transferring illegal catch between vessels), turning off transponders in fishing zones
• Uses satellite imagery to detect "dark vessels" (boats with transponders disabled)
• Machine learning distinguishes fishing vessels from cargo ships, cruise ships, and other marine traffic
• Provides public transparency—anyone can view global fishing activity online

Coverage:

• Monitors 65,000+ commercial fishing vessels globally
• Tracks 300+ million vessel position points daily
• Covers all major fishing regions and marine protected areas
• Data available publicly since 2012

Real-World Impact

Ocean Conservation:

• Protected marine areas now have 24/7 AI surveillance
• Coral reefs and sensitive habitats guarded from illegal trawling
• Fish stocks monitored to prevent overfishing
• Identification of illegal fishing in exclusive economic zones (EEZ)

Enforcement and Accountability:

• Coast guard and naval patrols directed to suspicious vessels
• Evidence provided for prosecution of illegal fishing operations
• Insurance companies and port authorities informed of violations
• Consumer pressure on companies buying from illegal sources

Scientific Research:

• Unprecedented data on global fishing effort and patterns
• Identifies hotspots of fishing pressure
• Tracks how fishing responds to regulations and marine protection
• Studies impact of fishing on marine ecosystems

Economic Benefits:

• Protects legitimate fishers from unfair competition
• Preserves fish stocks for sustainable harvest
• Reduces costs of monitoring and enforcement
• Supports coastal communities dependent on fishing

Notable Success Stories:

• Exposed massive illegal fishing operation in West African waters (2022)
• Helped Palau enforce its marine sanctuary (saved tuna populations)
• Identified Chinese fishing fleet operating illegally near Galápagos Islands (2020)
• Documented decline in Somali piracy through vessel tracking patterns
• Assisted Peru in protecting anchovy fishery worth $2 billion annually

The Data Behind the AI

Input Sources:

• AIS transponder data: GPS location, vessel speed, direction broadcast every few seconds
• Satellite imagery: Optical and radar imaging to detect vessels without active transponders
• Vessel databases: Ship registrations, fishing licenses, vessel characteristics
• Bathymetry (ocean depth): Fish at specific depths, influencing fishing locations
• Sea surface temperature: Fish populations follow temperature patterns
• Historical fishing patterns: Seasonal migrations, traditional fishing grounds
• Marine protected area boundaries: GPS coordinates of no-fishing zones

AI Training:

• Fed millions of vessel track segments labeled as "fishing" or "not fishing"
• Learned movement patterns characteristic of different fishing methods:
• Trawling: Slow, steady movement in straight or curved lines
• Long-lining: Vessel stops periodically to deploy/retrieve lines
• Purse seining: Vessel circles rapidly to encircle school of fish
• Drifting: Stationary or slow drift with nets deployed
• Identified evasion behaviors: transponder gaps, suspicious routes, meeting other vessels at sea
• Trained on thousands of confirmed illegal fishing incidents

Machine Learning Approach:

• Convolutional Neural Networks analyze vessel movement sequences
• Behavior classification: Distinguishes fishing from transit or other activities
• Anomaly detection: Flags unusual patterns for investigation
• Satellite image analysis: Computer vision identifies vessels in radar and optical imagery
• Network analysis: Identifies connections between suspected illegal vessels
• Real-time processing: Continuous monitoring and alert generation

Critical Thinking Questions

For Your Group Discussion:

1. Evasion Tactics: Illegal fishing operators can simply turn off their AIS transponders. How does the system counter this? What other evasion methods might criminals try? How can AI adapt?

1. False Positives: What if legitimate fishing vessels are incorrectly flagged as suspicious? What are the consequences? How should enforcement agencies verify AI alerts before taking action?

1. Sovereignty Issues: Fishing in another country's waters is illegal, but monitoring raises questions about international waters and jurisdiction. Who has the right to monitor and enforce fishing regulations? What role should global vs. local authorities play?

1. Economic Impact: Illegal fishing provides income to poor communities in some regions. How do we balance conservation with economic needs of coastal populations? Can AI help find sustainable alternatives?

1. Technology Arms Race: As monitoring improves, illegal operators develop new evasion methods. How can AI stay ahead? Is this an endless game of cat-and-mouse?

1. Public Data: Global Fishing Watch makes all data publicly available. What are the benefits and risks of transparency? Could this information be misused?

1. Small-Scale Fishing: This system focuses on large commercial vessels. How can we monitor small boats that may also engage in illegal fishing without creating unfair burden on artisanal fishers?

1. Climate Change Connection: How does overfishing interact with climate change impacts on oceans? Can sustainable fishing help ocean ecosystems adapt to warming waters?

Your Analysis Task

Complete the following for your case study presentation:

Summary (2-3 sentences):

Key Data & Methods:

• What data does the AI analyze?  

• How was the AI trained?  

• What makes this approach better than traditional methods?  

Environmental Problem Addressed:

Real-World Impact:

• Marine ecosystems protected:  

• Enforcement improvements:  

• Economic benefits:  

Limitations or Concerns:

Climate Change Connection:

One Question for Class Discussion:

Real-World Scenario

Galápagos Islands Marine Reserve - August 2020

Initial Detection:

• Global Fishing Watch AI detected 260 Chinese fishing vessels near edge of Galápagos Marine Reserve
• Vessels were technically in international waters but extremely close to protected zone
• AI identified suspicious behavior: coordinated movement, some transponder gaps, timing coincided with tuna migration

AI Analysis:

• Tracked vessels' origins (primarily from Chinese ports 6,000 miles away)
• Calculated fishing effort: estimated 73 million hours of fishing time in region
• Predicted impact on tuna, sharks, and other species that migrate between Galápagos and international waters
• Identified several vessels that briefly entered protected waters (illegal)

Response:

• Ecuador deployed naval patrols guided by AI tracking
• Global media coverage created diplomatic pressure
• Several vessels photographed and verified
• International outcry led to fishing fleet dispersal

Long-term Impact:

• Ecuador expanded marine reserve by 60,000 square kilometers
• Increased international cooperation on high-seas fishing regulation
• China improved fishing fleet oversight in response to exposure
• Galápagos populations of sharks and tuna showing recovery

Data Victory:

• Previous illegal fishing went undetected due to vast ocean area
• AI surveillance made the invisible visible
• Public data access enabled NGOs, media, and citizens to hold governments accountable
• Demonstrated power of transparency in ocean conservation

Additional Resources

Learn More:

• Global Fishing Watch interactive map: globalfishingwatch.org
• Oceana: Illegal Fishing Reports
• UN FAO: State of World Fisheries and Aquaculture
• National Geographic: "The Last Fish" (documentary)

Related AI Applications:

• Whale tracking to prevent ship strikes
• Coral reef health monitoring via satellite
• Microplastic pollution mapping
• Ocean temperature and acidification monitoring
• Invasive species tracking in marine ecosystems

Key Fishing Methods the AI Recognizes:

• Trawling: Dragging nets along ocean floor (destructive to habitats)
• Purse Seining: Encircling schools of fish with nets
• Long-lining: Setting lines with thousands of baited hooks
• Driftnetting: Large nets that drift with currents
• Pole and Line: Traditional, sustainable method

The Numbers

Global Fishing Industry:

• 4.6 million fishing vessels worldwide
• 59.6 million people employed in fishing and aquaculture
• 179 million tons of fish caught annually
• 35% of fish stocks overfished (up from 10% in 1974)

Illegal Fishing:

• $23 billion stolen from global economy annually
• 26 million tons of fish caught illegally each year (15% of global catch)
• 90% of large fish (tuna, marlin, shark) gone since 1950
• One-third of seafood sold may come from illegal sources

Conservation Impact:

• 8% of oceans currently protected (goal: 30% by 2030)
• AI monitoring makes protection enforcement possible
• Areas with strong enforcement show 400% increase in fish populations

Vocabulary

AIS (Automatic Identification System): GPS transponder required on commercial vessels that broadcasts location

IUU Fishing: Illegal, Unreported, and Unregulated fishing

EEZ (Exclusive Economic Zone): Ocean area extending 200 miles from coast where country has fishing rights

Trans-shipment: Transferring catch from fishing vessel to cargo ship at sea (often used to hide illegal catches)

Marine Protected Area (MPA): Region where fishing and other harmful activities are restricted or banned

Dark Vessel: Ship that has turned off its AIS transponder to hide its location and activities

© 2025 Evolve AI Institute LLC. May be reproduced for educational purposes.

Lesson 6: AI in Climate Science | Case Study 4 of 6