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GCRI · Global challenges

Industry, resources and trade

Industry depends on critical minerals, energy, chemicals and components, moved through ports, corridors and logistics networks few countries control alone. Concentration in extraction, processing or shipping turns a local disruption into a global shortage. Industrial development also brings capability and jobs. The Global Centre for Risk and Innovation (GCRI) studies inputs, production, logistics and industry as one system of dependencies. Part of global challenges.

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01Contents

Industry, resources and trade in seven parts.

In this dossier7 parts
  1. 01The challengeProduction depends on inputs and routes with few alternatives
  2. 02Measures of concentrationHow supply concentration and disruption exposure are measured
  3. 03Methods and limitsHow disruption is modelled, and what trade data cannot show
  4. 04GCRI’s partEvidence on dependence and capability, for the authorities and firms that decide
  5. 05How GCRI approaches itMapping concentration and testing alternatives
  6. 06Where to go nextPlatforms, chapters and counterparts
  7. 07SourcesWhere this page’s references lead
02The challenge

Production depends on inputs and routes with few alternatives.

Efficiency has often meant concentration: fewer suppliers, leaner inventories and longer routes. That lowers cost in normal times and raises exposure when a link breaks.

Inputs

Critical minerals and materials

Batteries, grids, electronics and medicines rely on materials whose extraction or processing is concentrated in few places.

Logistics

Ports, straits and corridors

A blocked strait, a congested port or a disrupted rail corridor delays goods far from the point of failure.

Industry

Development and safety

New industrial capacity brings jobs and process risk, from chemical safety to pollution.

03Geography

Activity and hazards worldwide.

Night lights and population density across the world, from NASA GIBS. Each layer carries its own date.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 2

Activity and hazards, for this page

About this layer
Evidence
Observed
Source
VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
Provider
NASA LAADS DAAC
Licence
NASA open data
Vintage
daily; Satellite radiance, corrected for moonlight and atmosphere
Newest at build
2026-10-12
Resolution
about 500 m grid
Uncertainty
Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Estimated
Source
Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
Provider
NASA SEDAC (CIESIN, Columbia University)
Licence
CC BY 4.0
Vintage
null; Census-based estimate, static (2020)
Resolution
about 1 km grid
Uncertainty
Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed (clouds leave gaps)
Source
VIIRS Global Flood Product (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite detection; clouds leave gaps
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed
Source
VIIRS NOAA-20 corrected reflectance (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite image
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Modelled (latest year GIBS publishes)
Source
MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
Provider
NASA LP DAAC
Licence
NASA open data
Vintage
yearly; Satellite classification; latest year GIBS publishes
Newest at build
2024-01-01
Resolution
about 500 m grid
Uncertainty
Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed
Source
GHRSST MUR25 (NASA JPL PO.DAAC)
Provider
NASA JPL PO.DAAC
Licence
NASA open data
Vintage
daily; Satellite analysis
Newest at build
2026-10-12
Resolution
about 2 km grid
Uncertainty
Satellite analysis of how far sea temperature departs from its usual value for the date shown; a marine heat indicator, not a coral bleaching alert.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

Activity and hazards, framed on the world.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERTSources and licences

  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • GHRSST Level 4 MUR analyses, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Live: NASA EONET Events are indicative, not authority warnings.
  • Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
  • Optional layers (7 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Sea surface temperature anomaly: GHRSST MUR25, NASA JPL PO.DAAC · 12 Oct 2026

04Measures of concentration

How supply concentration and disruption exposure are measured.

MeasureWhat it showsUnit and source
Producer and processor sharesHow much of world mining or refining of a material happens in each countryShare of world output by mass; USGS Mineral Commodity Summaries, IEA Global Critical Minerals Outlook
Herfindahl-Hirschman index of supplyConcentration of a country’s imports or of world supplySum of squared shares, from zero to one; UN Comtrade
Import dependenceNet imports relative to apparent consumptionRatio of net imports to consumption, by mass or value
Trade in value addedWhere value in a final product is created along the chainCurrency of a stated year; OECD Trade in Value Added
Chokepoint exposureShare of a country’s trade routed through a strait, canal or portTonnes or value through each route; UNCTAD maritime data
Inventory coverHow long stocks last if supply stopsDays of consumption held

The IEA’s Global Critical Minerals Outlook 2025 and the USGS Mineral Commodity Summaries 2025 both document that refining of several transition minerals is more concentrated than their mining. UNCTAD’s Review of Maritime Transport 2024 records how diversions around the Red Sea and low water in the Panama Canal lengthened routes and raised costs.

05Twin and cascade simulator

Model industry, resources and trade as a system. Run the cascade.

Assembled from the Nexus Standards area profile Supply chain and trade risk: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.

Hazards

  • Dam failure
  • River flood (set off downstream)
  • Flash flood (set off downstream)
  • Mass displacement (set off downstream)
  • Widespread power outage (set off downstream)
  • Water supply shortfall (set off downstream)

Controls

  • NS-0 Constitution and principles
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-12 Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)
  • NRS-H60 Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)
  • NRS-X4 Trade, transport and supply chains risk
  • NRS-H89 Hazard family: Transport network disruption (NHS-1 infra.mobility)
  • NRS-K38 Domain pack profile: Supply chain trade (DOMAIN-038)
  • NRS-H43 Hazard family: Livestock and aquaculture epizootics (NHS-1 health.animal-health)
  • NRS-M10 Method fabric: Markets, trade and supply chains

Observation

  • IMF PortWatch port activity and chokepoint disruptions (listed for reference)
  • Global Supply Chain Pressure Index (listed for reference)
  • OECD Data Explorer (SDMX API) (listed for reference)
  • World Bank Open Data and World Development Indicators API (listed for reference)
  • Developing countries’ and least developed countries’ share of global exports
  • Passenger and freight volumes, by mode of transport

Example geography

  • The Strait of Malacca: 227 hexagonal cells
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
  • Rain rate, last half hour (IMERG), NASA GIBS
  • Surface soil moisture (SMAP), NASA GIBS
06Methods and limits

How disruption is modelled, and what trade data cannot show.

MethodUseLimit
Multi-regional input-output modelsHow a shortage in one sector and country reaches othersSector aggregation hides specific materials and firms; tables lag several years
Network models of firm-level supplyHidden single suppliers below the first tierFirm-level data are proprietary and rarely complete
Route and port simulationDelay and cost when a chokepoint closesDepends on assumptions about rerouting capacity and behaviour
Material flow analysisStocks and flows of a material across its life, including recyclingCoefficients uncertain for new technologies

Trade statistics record declared flows between countries, not the ownership, processing location or end use of a material, and mirror statistics from exporters and importers often disagree. Analyses report both and say which was used.

07GCRI’s part

Evidence on dependence and capability, for the authorities and firms that decide.

GCRI studies supply dependence, industrial capability and process safety as research, and helps ministries test diversification, stockholding and recycling options. It gives no sourcing or investment advice, and precompetitive studies are designed so that no firm’s confidential information reaches a competitor. Field work sits with the Trade and Strategic Resources platform and the Advanced Industry and Robotics platform.

Findings are designed for the Strategic Systems series and the Global Sector Risk and Resilience series; datasets used would carry metadata under NS-3b of the proposed Nexus Standards. Useful contributions: material flow data for a country, port and corridor disruption records, and process safety lessons from new industrial sites.

08How GCRI approaches it

Mapping concentration and testing alternatives.

  1. 01

    Trace dependencies

    Supply networks from input to product using network science and optimisation and operations research.

  2. 02

    Find concentration

    Points where a single source, route or processor carries a large share of supply.

  3. 03

    Test disruption

    Scenarios for route closures and input shortages, labelled as scenario evidence.

  4. 04

    Inform industrial choices

    Evidence on capability, diversification and process safety for ministries and operators that decide.

09Where to go next

Platforms, chapters and counterparts.

Field work runs through the Trade and Strategic Resources platform and its critical minerals and materials chapter, and the Advanced Industry and Robotics platform and its industrial and chemical safety chapter. See the trade, resources and supply chains field gateway, geopolitical and geoeconomic risk, and The Global Risks Forum (GRF) on corporate and supply chain governance.

Precompetitive work is designed so that competitors’ confidential information is not exchanged.

10Sources

Where this page’s references lead.

The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.

11Questions

Questions and answers.

Does GCRI advise companies on sourcing?
No. GCRI publishes evidence on dependencies and runs studies with operators under agreed terms. Sourcing and investment decisions stay with the firms and authorities concerned.
Can an industry association join a study?
Enterprises and associations can explore a sector programme through the Work with GCRI routes. The first outcome is a work scope, permitted data exchange and evaluation terms.
How is commercially sensitive data protected?
Through agreed data terms. Public outputs show aggregated or permitted results, and no participant’s confidential information is shared with competitors.
Why is industrial safety part of this page?
Because industrial development changes local risk. Process safety, pollution and worker protection are part of whether new capacity strengthens or weakens a community.
Is diversification always the answer?
Not always. Diversification has costs and its own risks. GCRI sets out the trade-offs between cost, redundancy, stockholding and alternative routes, so decision-makers can choose with evidence.
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