GCRI · Trade and Strategic Resources
Trade corridors and chokepoints
A large share of world trade passes through a small number of straits, canals and ports. When one of them closes or slows, ships reroute around continents, freight rates and transit times rise, and shortages travel far from the event. This page sets out how chokepoints concentrate trade, how disruptions propagate, how corridor exposure is measured, and what evidence serves the governments and firms that depend on these routes.
Trade corridors and chokepoints in seven parts.
- 01The questionTrade corridors and chokepoints: how the risk develops
- 02Across the domainsChokepoints concentrate the trade that every domain relies on
- 03IndicatorsWhat is measured, and how well
- 04SourcesWhere the evidence comes from
- 05DecisionsWho decides, and what the evidence serves
- 06Core questionsWhat experts ask about corridors
- 07Mechanisms and driversWhy chokepoints concentrate risk
Trade corridors and chokepoints: how the risk develops.
Ports, straits, rail and supply corridors. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Geography concentrates routes
Shipping follows the shortest safe paths between producers and markets, which funnel through straits and canals. Alternatives exist but add distance, fuel, time and cost.
Many causes can close a route
Groundings, drought lowering canal water levels, conflict, piracy and storms have all disrupted chokepoints. The cause matters less than the duration and the capacity of alternatives.
Disruption ripples through networks
Rerouted ships arrive late and out of sequence, containers end up in the wrong places and port congestion spreads. Effects continue for weeks after the route reopens.
Costs pass to importers
Higher freight and insurance costs feed into prices of goods, with the largest effects on import-dependent and distant economies.
Activity and hazards in the Strait of Malacca.
Night lights, population density and marine heat over the Strait of Malacca, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
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
- 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
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 (clouds and sun glint leave gaps)
- Source
- MODIS Aqua ocean colour (NASA OB.DAAC)
- Provider
- NASA OB.DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite retrieval; clouds and sun glint leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 1 km grid
- Uncertainty
- Satellite estimate of chlorophyll-a near the sea surface on the day shown, an indicator of plankton and ocean productivity; not a measure of fish stocks or harmful blooms.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
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 Strait of Malacca.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
- 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
- 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
- MODIS Aqua ocean colour, NASA Ocean Biology Processing Group; distributed by the NASA Ocean Biology DAAC (OB.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
- Sea surface temperature anomaly: GHRSST MUR25, NASA JPL PO.DAAC · 12 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
- Ocean chlorophyll-a concentration: MODIS Aqua ocean colour, NASA OB.DAAC · 12 Oct 2026
Chokepoints concentrate the trade that every domain relies on.
- FoodCouplingGrain and fertiliser pass through a few straits and canals.What to watchShare of food imports through each route
- EnergyCouplingOil and liquefied gas cargoes follow the same chokepoints.What to watchRerouting time and cost
- WaterCouplingLow water in canals and rivers restricts shipping, as the Panama Canal showed in 2023 and 2024.What to watchDraught restrictions on waterways
Route disruption scenarios are designed for the Scenario and Stress-Test series. UNCTAD’s Review of Maritime Transport 2024 documents the effects of Red Sea diversions and Panama Canal restrictions on distances and costs.
- Port and canal transit records with dates.
- Rerouting cost estimates with methods.
Corridor and chokepoint monitor.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Corridor and chokepoint monitor
Trade corridors and chokepoints · Corridor A · Week 48
- Transit time21days6Alert
- Freight index1968Watch
- Vessels rerouted61this weekWatch
- Inventory cover32daysNormal
Corridors
red: disrupted
Time to recover vs time to survive
by critical input
| Fertiliser | Strait | 13 | 6 | Short |
| Fuel | Strait | 8 | 6 | Covered |
| Semiconductors | Port hub | 28 | 6 | Short |
| Grain | Corridor A | 6 | 11 | Covered |
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Transit calls through a chokepoint | vessel transits per day | daily | Satellite automatic identification system data | OBSERVED |
| Trade volume through a chokepoint | tonnes per period | weekly | Vessel tracking with cargo estimates | ESTIMATED |
| Share of a country’s trade exposed to a chokepoint | percent of trade value | annual | Trade and routing analysis | ESTIMATED |
| Additional voyage distance when rerouted | nautical miles | per route | Route modelling | MODELLED |
| Container freight rate | currency per forty-foot container | weekly | Published freight indices | REPORTED |
| Port waiting time | hours | weekly | Vessel tracking | OBSERVED |
A shock through an input-output economy.
A loss of output in one sector propagates through the technical coefficients to its suppliers and customers, and recovers at the rate you set; the coefficients are teaching values, not national accounts. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Strait of Malacca; the model itself is not tied to a place.
Controls
- Sector hit first (position in the list)
- 0
- Size of the shock
- 30% of its output
- Duration of the shock
- 30 days
- Recovery rate
- 0.08 per day
- Days simulated
- 180 days
Readouts
- Output lost over the run
- 0.44% of a year’s output
- Total over direct (multiplier)
- 1.53 times
- Most affected other sector
- Transport and ports
- Its peak inoperability
- 2.5%
Numbers, methods and sources
| Sector | Peak inoperability (%) | Output weight (%) |
|---|---|---|
| Agriculture | 29.38 | 9.9 |
| Energy | 0.85 | 19.8 |
| Manufacturing | 2.31 | 10.4 |
| Transport and ports | 2.48 | 17.0 |
| Trade | 1.66 | 21.4 |
| Services | 0.32 | 21.4 |
Methods
- Input-output analysis Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press
- Inoperability input-output model Haimes and Jiang (2001), Journal of Infrastructure Systems 7
- Dynamic inoperability and recovery Lian and Haimes (2006), Systems Engineering 9
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Seaports Natural Earth
- Maritime chokepoints Nexus (named straits and canals at their published coordinates)
- Railways Natural Earth
- Major roads Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Trade and Strategic Resources in Foundry
- Tested at Trade and Strategic Resources in Universe
- Codified in Industry, Trade and Supply Chains in Standards
- Published in Trade and Strategic Resources in Reports
- Taught in Faculty of Finance and Economics in Academy
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| IMF PortWatch | Port and chokepoint activity estimated from satellite vessel tracking | Public, IMF terms (to check) |
| UNCTAD Review of Maritime Transport and UNCTADstat | Maritime trade, fleet and port statistics | Public, UNCTAD terms (to check) |
| UN Comtrade | Bilateral trade by product and partner | Free access with limits, UN terms |
| Suez Canal Authority and Panama Canal Authority statistics | Published transits and tonnage | Public records, terms per authority |
| World Bank and UNCTAD studies on chokepoint disruption | Analysis of rerouting and costs | Licence per publication |
Model trade corridors and chokepoints 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)
Systems and couplings
- Supply chain and trade risk
- Food security and nutrition risk Cascade
- Oceans and coasts risk standards Exposure
- Geopolitical and security risk Common driver
- Cyber and digital risk standards Cascade
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-12Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)NRS-H60Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)NRS-X4Trade, transport and supply chains riskNRS-H89Hazard family: Transport network disruption (NHS-1 infra.mobility)NRS-K38Domain pack profile: Supply chain trade (DOMAIN-038)NRS-H43Hazard family: Livestock and aquaculture epizootics (NHS-1 health.animal-health)NRS-M10Method 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
Who decides, and what the evidence serves.
Trade and Strategic Resources prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Ministries of trade and transport | How exposed national trade is to each chokepoint and what alternatives exist | Exposure profiles; rerouting scenarios |
| Importers and shippers | How to plan inventory and routes around chokepoint risk | Disruption timelines; freight evidence |
| Port authorities | What capacity to plan for diverted traffic | Rerouting scenarios |
Outputs this topic produces
- Chokepoint exposure profiles by country and product
- Rerouting scenarios with distance and time added
- Disruption timelines reconstructed from vessel data
- Evidence notes for trade and transport ministries
How trade corridors and chokepoints is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
System model
The couplings between the systems in trade corridors and chokepoints: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What experts ask about corridors.
- Which corridors carry flows that have no practical alternative in the short term?
- What hazards, such as storms, drought, conflict or cyber incidents, threaten each corridor?
- How much spare capacity do alternative routes, ports and modes have?
- How long does it take for a closure to affect prices, inventories and production?
- Which countries and sectors are most exposed to each chokepoint?
Why chokepoints concentrate risk.
Geography and economics both favour concentration. Straits and canals shorten journeys dramatically; large ports gain scale economies and attract more services; and container shipping is organised around hub-and-spoke networks. The result is a system in which a few nodes and links carry a disproportionate share of traffic.
When a chokepoint is disrupted, the direct effect is delay and rerouting. Indirect effects follow: vessels and containers end up in the wrong places, freight rates rise, schedules break down, and ports on alternative routes become congested. Recovery can take much longer than the disruption itself because the network needs time to rebalance.
Physical climate risk is increasingly relevant. Drought can lower water levels in canals and rivers, limiting vessel draft; storms and sea-level rise affect port operations; and heat can affect rail and road infrastructure.
Methods and their limits.
- 01
Trade corridor GIS
Spatial mapping of routes, ports and hazard exposure using geospatial information systems. Accuracy depends on the quality of route and asset data.
- 02
Vessel tracking data
Automatic identification system records of ship movements. Coverage gaps and deliberate signal switching limit completeness.
- 03
Network models
Graph models of shipping and rail networks using network science to test the effect of removing nodes. They simplify operational behaviour.
- 04
Transport capacity analysis
Engineering assessment of port, rail and road throughput using transport engineering. Capacity under stress is hard to observe in advance.
Models show which disruptions would matter most, not when they will occur. Data on cargo values and contents are often commercially confidential.
How it is studied, and what the methods cannot say.
- 01Network science and contagionTrade network centrality · Multi-tier dependency mapping · Disruption propagationApplied here
- 02Geospatial information systemsFacility hazard overlays · Sourcing region deforestation · Corridor mappingApplied here
- 03Optimisation and operations researchRerouting under chokepoint closure · Strategic stock sizing · Sourcing portfolio designApplied here
- 04EconometricsPrice transmission · Effects of trade measures · Disruption impacts on outputApplied here
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.
Questions and answers.
What is a maritime chokepoint?
Why do disruptions last after a route reopens?
How is chokepoint traffic measured?
Does the platform rank chokepoints by danger?
Are land routes included?
Can I contribute route or port data?
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