GCRI · Critical Infrastructure
Urban assets and housing
Buildings, bridges, schools and public facilities make up most of the value at risk in a city and most of the deaths in earthquakes and many storms. Their safety depends on design codes, construction quality, maintenance and the condition of older stock. This page sets out how built assets fail, how their condition and vulnerability are assessed, and what evidence serves the authorities and owners responsible for them.
Urban assets and housing on the record.
Urban assets and housing: how the risk develops.
Buildings, heat and climate exposures. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Older stock predates modern codes
Buildings designed before current codes, or built without engineering, carry most of the vulnerability. Retrofit is costly and slow, so the old stock remains for decades.
Codes work only when enforced
Building codes reduce risk where plans are checked and construction is inspected. Informal construction and weak enforcement leave new buildings as vulnerable as old ones.
Deterioration reduces capacity
Corrosion, water damage, alterations and lack of maintenance weaken structures over time. Bridges and public buildings without regular inspection lose safety margins unseen.
Occupancy sets the consequence
Schools, hospitals and dense housing hold many people at once. The same structural failure has far greater consequences where occupancy is high.
Urban signals in Western Europe.
Population density, night lights, daytime surface heat 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
Urban signals, 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.
Urban signals, 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
- 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 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
- 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
- OMI nitrogen dioxide (Aura) and OMPS aerosol index (Suomi NPP), NASA; distributed by the NASA GES DISC; 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).
- Air quality forecast, 5 days, PM2.5 (CAMS via Open-Meteo): Contains modified Copernicus Atmosphere Monitoring Service information 2026.
- Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
- 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 (16 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
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 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
- Nitrogen dioxide, lower atmosphere column: OMI Aura, NASA GES DISC · 10 Oct 2026
Buildings decide who is exposed when hazards strike.
- HealthCouplingHousing quality drives heat and cold exposure.What to watchIndoor temperature in heat episodes
- EnergyCouplingBuilding efficiency sets heating and cooling demand.What to watchEnergy performance of housing
- WaterCouplingLocation on floodplains sets flood exposure.What to watchHomes in flood zones
Building stock analyses are designed for the Country Systems Risk and Resilience series. Structural design follows national codes such as the Eurocodes, and seismic performance methods include FEMA P-58.
- Building inventories with structural types.
- Post-event damage surveys.
Asset criticality register.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Asset criticality register
Urban assets and housing · Lifeline system A · Register v5
Critical assets
| SS-12 | Electricity | Tier 1 | Flood 1-in-100 | 14 |
| WTW-2 | Water | Tier 1 | Flood 1-in-100 | 12 |
| DX-1 | Telecom | Tier 2 | Heat | 6 |
| H-Campus | Health | Tier 1 | Earthquake | 77 |
| 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
- 19 h
- Owner
- Asset owner
Dependency graph
red: SS-12 and its dependants
Restoration time by sector
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 |
|---|---|---|---|---|
| Buildings by construction type and age | count by class | per inventory update | Building inventories and cadastres | Published statistics |
| Schools assessed for hazard safety | percent of schools | annual | School safety programmes | REPORTED |
| Bridges in poor condition | percent of inspected bridges | annual | Bridge inspection records | OBSERVED |
| Building permits with structural review | percent of permits | annual | Local permit records | REPORTED |
| Buildings retrofitted | count per year | annual | Retrofit programme records | REPORTED |
| Population in high-vulnerability building classes | people | per assessment | Exposure models | MODELLED |
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
- 19%
- Assets still working
- 35%
- Amplification of the initial damage
- 3.5 times
- Steps to settle
- 3
Numbers, methods and sources
| Step | Transport working (%) | Power working (%) | Telecoms working (%) |
|---|---|---|---|
| 0 | 83 | 89 | 72 |
| 1 | 33 | 72 | 44 |
| 2 | 33 | 33 | 44 |
| 3 | 33 | 28 | 44 |
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
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 |
|---|---|---|
| Global Earthquake Model exposure and vulnerability models | Building exposure and fragility by class | CC BY-NC-SA 4.0 for public models (to check) |
| Global Human Settlement Layer (JRC) | Built-up area, building height and settlement classification | Open, CC BY 4.0 |
| OpenStreetMap building footprints | Building outlines and some attributes | Open, ODbL |
| National bridge inventories | Bridge condition ratings, such as the US National Bridge Inventory | Public records, licence per government |
| Comprehensive School Safety Framework resources | School safety assessment approaches | Public, terms per publisher (to check) |
Model urban assets and housing 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
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 |
|---|---|---|
| Building regulators and local governments | Which code changes and enforcement to prioritise | Permit review records; vulnerability profiles |
| Ministries of education and public works | Which schools and public buildings to retrofit first | Safety screening; occupancy and hazard evidence |
| Road and bridge agencies | Which bridges to inspect, repair or replace | Condition summaries |
Outputs this topic produces
- Building exposure and vulnerability profiles by construction class
- School and public building safety screening methods
- Bridge condition evidence summaries
- Retrofit prioritisation frameworks
How urban assets and housing 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 urban assets and housing: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What experts ask.
- Which building types and neighbourhoods are most exposed to heat, flood and structural damage?
- How does loss of power or water make homes unsafe, particularly for older or unwell people?
- How do building codes and their enforcement shape damage in hazard events?
- How quickly can people return to homes after a disaster, and what delays reconstruction?
- How do urban heat islands and land use change alter exposure?
Drivers and failure pathways.
Urban exposure is concentrated and uneven. Dense areas place many people and assets in the same hazard footprint, and informal or older housing often offers less protection. Heat is a growing concern: buildings with poor ventilation, high thermal mass in hot climates or no cooling can become dangerous, and loss of power during a heatwave removes the protection that air conditioning provides. Urban heat islands, created by paved surfaces and limited vegetation, raise temperatures further.
Flooding damages buildings and contents and makes homes uninhabitable, while earthquakes test structural design. In each case, housing recovery depends on lifeline restoration, construction capacity, insurance and finance. Displacement can last long after utilities return, with social and economic effects that extend for years.
Urban form and planning are studied with Cities and Built Environment.
How it is studied.
- 01
Exposure and vulnerability mapping
Building inventories combined with hazard models, drawing on structural and earthquake engineering, estimate likely damage.
- 02
Thermal performance analysis
Building physics models assess indoor temperatures during heatwaves with and without power.
- 03
Recovery analysis
Studies of past events trace how long housing recovery took and what constrained it.
- 04
Limits
Building inventories are often incomplete, especially for informal settlements. Damage models carry wide uncertainty, and social factors in recovery are hard to quantify.
How it is studied, and what the methods cannot say.
- 01Structural and earthquake engineeringFragility of infrastructure components · Retrofit of critical structures · Post-event inspectionApplied here
- 02Sensors, IoT and observation networksStructural health monitoring · Leak and pressure monitoring · Grid sensingApplied here
- 03Reliability and resilience engineeringResilience metrics for lifelines · Reliability analysis of networks · Restoration planningApplied here
- 04Space systems and satellite servicesTiming dependency review · Satellite backup communications · Asset monitoring from spaceApplied 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.
Why do older buildings matter most?
What is a seismic retrofit?
What is an exposure model?
Why include housing in critical infrastructure?
Does the platform assess individual buildings?
Is heat really an infrastructure problem?
Who reviews coverage of this topic?
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