GCRI · Critical Infrastructure
Transport and mobility
Roads, rail and public transport carry people to work, school, care and safety, and carry responders and supplies in emergencies. Networks fail when links are cut by floods, landslides, heat or crashes, and when power or signalling stops. This page sets out how disruption spreads through transport networks, how network resilience is measured, and what evidence serves the transport authorities and operators responsible for them.
How the work runs.
Asset criticality register
Transport and mobility · Lifeline system A · Register v3
Critical assets
| SS-12 | Electricity | Tier 1 | Flood 1-in-100 | 21 |
| WTW-2 | Water | Tier 1 | Flood 1-in-100 | 23 |
| DX-1 | Telecom | Tier 2 | Heat | 4 |
| H-Campus | Health | Tier 1 | Earthquake | 93 |
| PN-3 | Transport | Tier 2 | Storm surge | n/a |
SS-12 dependencies
- Upstream
- Transmission L4, L7
- Downstream
- WTW-2, H-Campus, DX-1
- Restoration target
- 16 h
- Owner
- Asset owner
Dependency graph
red: SS-12 and its dependants
Restoration time by sector
Fig.Asset criticality register: example names and illustrative values, not a record or a live system.
Transport and mobility: how the risk develops.
Mobility networks, ports, rail and critical access. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Critical links carry the network
Some bridges, tunnels and road sections have no practical detour. Their loss isolates communities or forces long diversions that multiply travel time.
Hazards degrade operations
Floods close roads and rail, heat buckles rails and softens asphalt, landslides block mountain routes, and snow and ice slow everything. Each needs different design and response.
Electrified systems need power and signals
Metros, electric rail and traffic signals stop when power or signalling fails. Passengers may be stranded underground or between stations.
Disruption falls on those without options
People without cars, with disabilities or in remote areas depend on a few routes and services. Disruption cuts their access to jobs and care first.
Infrastructure exposure in Western Europe.
Night lights, population density, flood water and true-colour imagery over Western Europe, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 4
Infrastructure exposure, for this page
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.
Infrastructure exposure, framed on Western Europe.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 · U.S. Geological Survey · NASA HLS S30Sources 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
- 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.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- Observed (EO): NASA HLS S30 (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).
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
- 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 (12 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
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
Mobility keeps people connected to services in every domain.
Mobility analyses are designed for the Country Systems Risk and Resilience series. Network access is measured as travel time over real networks, not straight-line distance.
- Road closure records during events.
- Access studies with network data.
A cascade through interdependent networks.
A hazard footprint takes out co-located assets in every layer; fragmentation, dependency between layers and overload of the survivors then spread the failure. The 3D view separates the layers by depth. Teaching model with stated illustrative values, not a prediction. The map on this page shows Western Europe; the model itself is not tied to a place.
Controls
- Assets per layer
- 18
- Hazard footprint
- 8% of area
- Assets that depend on another layer
- 60%
- Spare capacity (tolerance)
- 30%
Readouts
- Assets hit by the hazard
- 9%
- Assets still working
- 17%
- Amplification of the initial damage
- 9.0 times
- Steps to settle
- 3
Numbers, methods and sources
| Step | Transport working (%) | Power working (%) | Telecoms working (%) |
|---|---|---|---|
| 0 | 94 | 94 | 83 |
| 1 | 33 | 61 | 67 |
| 2 | 28 | 11 | 39 |
| 3 | 11 | 6 | 33 |
Methods
- Interdependent networks Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464
- Overload cascades Motter and Lai (2002), Physical Review E 66
- Betweenness load Brandes (2001), Journal of Mathematical Sociology 25
- Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
- Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
- 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:
- Major roads Natural Earth
- Railways Natural Earth
- Seaports Natural Earth
- Airports Natural Earth
- Urban extents Natural Earth
- Night lights tonight, outages (VIIRS Day/Night Band) NASA/NOAA VIIRS (Suomi NPP) · register nasa.gibs.context-live-layers
- Natural events (NASA EONET) NASA EONET · register nasa.eonet.events
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Critical Infrastructure in Foundry
- Tested at Critical Infrastructure in Universe
- Codified in Energy and Critical Infrastructure in Standards
- Published in Critical Infrastructure in Reports
- Taught in Faculty of Infrastructure, Energy and Industry in Academy
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 |
|---|---|---|---|---|
| Network links without alternative route | count of links | per assessment | Network analysis | MODELLED |
| Travel time increase under link closure | percent increase | per scenario | Transport models | MODELLED |
| Weather-related closures | hours of closure by cause | annual | Road and rail operator records | OBSERVED |
| Public transport service reliability | percent of scheduled services operated | monthly | Operator performance data | OBSERVED |
| Population with access to essential services by public transport | percent within a stated travel time | per assessment | Accessibility analysis | MODELLED |
| Rail heat-related incidents | count | annual | Rail operator records | REPORTED |
Model transport and mobility as a system. Run the cascade.
Assembled from the Nexus Standards area profile Critical infrastructure and critical entities: 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
- Critical infrastructure and critical entities
- Energy risk standards Dependency
- Space weather, spectrum and timing risk standards Common-mode dependency
- Compound and cascading hazard standards Cascade
- Cyber resilience and digital operational resilience Common driver
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)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-H94Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)NRS-H107Hazard family: Digital infrastructure concentration and monoculture (NHS-1 tech.digital-concentration)NRS-K31Domain pack profile: Cyber national resilience (DOMAIN-031)NRS-K36Domain pack profile: Critical infrastructure (DOMAIN-036)NRS-K48Domain pack profile: Financial system resilience (DOMAIN-048)
Observation
- OpenStreetMap planet and replication (listed for reference)
- Global Power Plant Database (listed for reference)
- NASA Black Marble night-time lights (VNP46) (listed for reference)
- Global Human Settlement Layer (listed for reference)
- Damage to critical infrastructure attributed to disasters
- Number of disruptions to basic services attributed to disasters
- Proportion of the rural population who live within 2 km of an all-season road
Example geography
- Europe: 113 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
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 |
|---|---|---|
| OpenStreetMap road and rail networks | Network geometry for routing and accessibility | Open, ODbL |
| GTFS public transport feeds | Published schedules and stops from transport agencies | Open, licence per agency |
| National road and rail operator performance statistics | Closures, delays and reliability | Public records, licence per operator |
| Global Roads Inventory Project (GRIP) | Global road network dataset | Open, licence to check |
| Copernicus and national flood hazard maps | Hazard exposure of transport links | Terms per source |
How transport and mobility 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 transport and mobility: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
Who decides, and what the evidence serves.
Critical Infrastructure 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 |
|---|---|---|
| Transport ministries and road authorities | Which links to strengthen or duplicate | Critical link analyses; hazard exposure |
| Public transport operators | How to keep essential services running in disruptions | Reliability data; accessibility analyses |
| Emergency planners | Which routes responders and evacuees depend on | Critical links; travel time under closure |
Outputs this topic produces
- Critical link analyses for road and rail networks
- Accessibility analyses of essential services under disruption
- Hazard exposure assessments of transport networks
- Evidence notes for transport resilience plans
What experts ask.
- Which communities lose access to essential services when a single route fails?
- How do public transport, roads and active travel substitute for each other in a disruption?
- How do signalling, ticketing and traffic management depend on power and communications?
- How quickly can emergency services reach people when networks are degraded?
- How does electrification of transport change dependence on the grid?
Drivers and failure pathways.
Mobility networks are vulnerable at bridges, tunnels, junctions and single access roads. When these fail, travel times can increase sharply or communities can be cut off. Rail and metro systems depend on electricity for traction and signalling; road networks depend on traffic signals and fuel distribution. A widespread power outage can paralyse a city's movement even if no transport asset is damaged.
Access is unequal. People without cars, older residents and those on the edges of networks are most affected by disruption. The shift to electric vehicles and electrified public transport reduces some risks while increasing dependence on the grid and on charging infrastructure.
The chapter is set out on the transport and mobility chapter, and freight nodes are covered in transport and logistics nodes.
How it is studied.
- 01
Accessibility analysis
Network models from urban and transport engineering measure travel times to essential services before and during disruption.
- 02
Vulnerability ranking
Methods from network science and contagion identify links whose loss causes the greatest loss of access.
- 03
Emergency access modelling
Simulation from optimisation and operations research tests response times when routes are blocked.
- 04
Limits
Travel behaviour changes in crises in ways that models capture poorly. Network data may not reflect informal routes, and access measures depend on which services are counted as essential.
How it is studied, and what the methods cannot say.
- 01Urban and transport engineeringNetwork criticality · Climate-resilient design · Disruption operationsApplied here
- 02Network science and contagionCritical node and link analysis · Interdependent network models · Redundancy assessmentApplied here
- 03Optimisation and operations researchResilience investment portfolios · Restoration scheduling · Network design under uncertaintyApplied here
- 04Structural and earthquake engineeringFragility of infrastructure components · Retrofit of critical structures · Post-event inspectionApplied here
- 05Sensors, IoT and observation networksStructural health monitoring · Leak and pressure monitoring · Grid sensingApplied 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 critical link?
How does heat affect railways?
What is GTFS?
How does this topic relate to the chapter?
Does the platform plan transport networks?
Why does electrification matter for resilience?
Who reviews coverage of this topic?
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