Mapping Risk from Space: A New Lens on Critical Mineral Supply Chains

Highlights

• Cambridge researchers built a "Google Maps for mineral risk" combining satellite imagery, ESG mapping, transport modeling, and displacement data to predict supply chain disruptions in real-time.
• The study reveals transport routes—not mines—are often the biggest vulnerability, with southern African corridors to Mozambique ports facing repeated cyclone, flood, and conflict risks.
• Using satellite data and a Critical Mineral Dashboard, governments and companies can now quantify ESG risks and identify where disruptions will physically occur before they impact global markets.

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A March 2026 briefing (opens in a new tab) led by Alexey Noskov, PhD (opens in a new tab), at the University of Cambridge Department of Engineering (opens in a new tab), alongside collaborators Gretel Cuevas Verdin (opens in a new tab), Jonathan Cullen, and André Cabrera Serrenho (opens in a new tab), introduces a new way to understand critical mineral supply chains—using satellites, mapping tools, and real-world disruption data. The study shows that supply risks are not just geopolitical or economic, but physical and local: roads flood, mines expand unpredictably, and transport routes pass through conflict zones. By combining satellite monitoring, ESG (environmental, social, governance) indicators, and transport modeling into a single digital dashboard, the researchers demonstrate how governments and companies can better predict and manage disruptions—particularly in fast-growing regions like southern Africa.

How the Study Works (Explained Simply)

Think of this as Google Maps for mineral risk—but far more advanced.

The researchers built a system that combines four key tools:

• Satellite imagery: Tracks mine growth and activity in near real time
• ESG mapping: Measures local risks like population density, infrastructure, and environmental stress
• Transport modeling: Identifies key roads, railways, and alternative routes
• Displacement data: Uses records of people forced to move (due to disasters or conflict) as a signal of disruption risk

All of this feeds into an interactive platform called the Critical Mineral Dashboard, allowing users to “see” where supply chains are most vulnerable.

What the Study Found

1. You Can Track Mining Activity from Space

Satellite data showed a strong link between mine expansion and production levels.

For example, at a copper mine in Zambia, increases in mine size closely matched increases in output (see Figure on page 4).

Translation: You don’t need to wait for company reports—you can independently monitor production trends.

2. Supply Chains Break at Weak Links—Not Just Borders

The study found that transport routes—not mines—are often the biggest risk.

In southern Africa:

• Lithium and rare earth exports rely on a few key corridors to ports in Mozambique
• These routes pass through areas prone to cyclones, flooding, and conflict

Some road segments near the port of Beira repeatedly face disruption, while others remain intact even during floods (see analysis and imagery on pages 9–10).

Translation: The biggest risk isn’t always the mine—it’s getting the material out.

3. “ESG Risk” Can Be Mapped, Not Just Reported

The study introduces a practical way to measure ESG risk using a 10 km “Local Impact Area” around each mine.

It tracks:

• Population density
• Roads and infrastructure
• Access to schools and healthcare

Lower scores indicate higher risk of social conflict or environmental damage.

Translation: ESG is no longer just a narrative—it can be quantified and compared.

4. Past Disasters Predict Future Disruptions

One of the most novel ideas: using internal displacement data (people forced to move due to disasters or conflict) as a proxy for supply chain risk.

If people have repeatedly fled an area, the infrastructure there is likely fragile.

Translation: Where disruption has happened before, it will likely happen again.

Study Limitations (What to Watch Out For)

• Data gaps: Satellite and displacement data can be incomplete or delayed
• Proxy assumptions: Using displacement as a risk indicator is insightful—but indirect
• Regional focus: Case studies center on southern Africa, so results may not fully generalize
• Technical complexity: While the dashboard simplifies use, underlying models still require expertise

In short, the system is powerful—but not perfect.

Why This Matters

This study reframes how we think about supply chains.

Instead of asking “Which country controls supply?”, it asks:

“Where will the next disruption physically occur?”

Implications:

• Governments can prioritize infrastructure investment in high-risk corridors
• Companies can diversify routes and suppliers more intelligently
• Investors gain early warning signals of disruption

It also reinforces a key _Rare Earth Exchanges_™ theme:

Supply chains fail locally—but impact globally.

What Comes Next

The logical next steps:

• Expand this framework globally (Latin America, Southeast Asia, Africa)
• Integrate real-time data feeds (weather, conflict alerts)
• Link directly to pricing models and commodity markets

Conclusion

This Cambridge-led study offers a powerful shift—from abstract risk to mapped, measurable vulnerability. It shows that the future of critical mineral security will not be decided only in boardrooms or capitals, but on roads, rivers, and railways—many of them fragile, exposed, and now visible from space.

REEx Reflection

The next generation of supply chain intelligence won’t just analyze markets—it will map reality.