GCRI · Cities and Built Environment
Urban utilities
Urban utilities deliver water, sanitation, drainage, solid waste collection and energy to homes and businesses. Their reach and reliability decide public health, flood risk and the cost of living in a city, and gaps fall hardest on the poorest neighbourhoods. This page sets out how urban utility services expand, fail and recover, how coverage and quality are measured, and what evidence serves the utilities and city authorities responsible.
Urban utilities on the record.
Urban utilities: how the risk develops.
Water, waste, electricity and communications. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Networks lag behind growth
Pipes, sewers and lines follow formal development and ability to pay. New and informal areas are served by tankers, vendors, pit latrines and illegal connections, at higher cost and risk.
Drainage and waste are linked
Uncollected solid waste blocks drains and channels, turning ordinary rain into local floods. Waste collection is a flood control service as well as a sanitation service.
Tariffs and finance shape service
Utilities that cannot recover costs underinvest in maintenance and expansion. Subsidies often benefit connected, better-off households more than the unconnected poor.
Services depend on each other
Water and wastewater need electricity; drainage needs waste collection; energy systems need water for cooling. A failure in one service degrades others.
Urban signals in India.
Night lights, population density and daytime surface heat over India, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Urban signals, 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 (persistent cloud still leaves gaps)
- Source
- VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- 8-day; Satellite 8-day composite; persistent cloud still leaves gaps
- Newest at build
- 2026-09-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground over the 8 days ending on the date shown, a heat exposure indicator; not air temperature, heat index or a heat warning.
- 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 leave gaps)
- Source
- OMI Aura (NASA GES DISC)
- Provider
- NASA GES DISC
- Licence
- NASA open data
- Vintage
- daily; Satellite retrieval; clouds leave gaps
- Newest at build
- 2026-10-10
- Resolution
- about 2 km grid
- Uncertainty
- Satellite column of nitrogen dioxide in the lower atmosphere on the day shown, mostly from combustion; not a ground-level concentration or a health warning.
- 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.
Urban signals, framed on India.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 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
- 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 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).
- 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
- 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
- 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
Urban utilities carry the domains to households.
Utility studies are designed for the Global Sector Risk and Resilience series. City service indicators follow ISO 37120.
- Utility performance data.
- Outage histories.
Asset register with hazard overlay.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Asset register with hazard overlay
Urban utilities · Riverside ward · Flood 1-in-100 overlay
Hazard overlay
flood scenario on asset register
RiverFlood extentExposed asset
Exposed assets
| H-01 | Clinic | 1.1 |
| S-07 | School | 0.3 |
| E-03 | Substation | 0.7 |
| W-02 | Pump station | 0.9 |
Adaptation options
| Raise substation E-03 | 1 | Medium | Service continuity | Design |
| Retention park upstream | 7 | High | Heat, recreation | Feasibility |
| Flood-proof clinic H-01 | 1 | Low | Health access | Funded |
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 |
|---|---|---|---|---|
| Population with safely managed drinking water | percent of urban population | annual | WHO/UNICEF Joint Monitoring Programme | ESTIMATED |
| Population with safely managed sanitation | percent of urban population | annual | WHO/UNICEF Joint Monitoring Programme | ESTIMATED |
| Municipal solid waste collected | percent of waste generated | annual | SDG indicator 11.6.1 data | REPORTED |
| Hours of water supply | hours per day | monthly | Utility service records | REPORTED |
| Population with access to electricity | percent of urban population | annual | Tracking SDG 7 | ESTIMATED |
| Local flood events linked to blocked drains | count | annual | Municipal records | REPORTED |
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 India; 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
- 11%
- Assets still working
- 11%
- Amplification of the initial damage
- 8.0 times
- Steps to settle
- 3
Numbers, methods and sources
| Step | Transport working (%) | Power working (%) | Telecoms working (%) |
|---|---|---|---|
| 0 | 83 | 89 | 94 |
| 1 | 33 | 83 | 61 |
| 2 | 17 | 33 | 17 |
| 3 | 11 | 6 | 17 |
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 Cities and Built Environment in Foundry
- Tested at Cities and Built Environment in Universe
- Codified in Cities and the Built Environment in Standards
- Published in Cities and Built Environment 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 |
|---|---|---|
| WHO/UNICEF Joint Monitoring Programme | Urban and rural water, sanitation and hygiene coverage | Open, CC BY-NC-SA 3.0 IGO |
| UN-Habitat Waste Wise Cities data and SDG 11.6.1 | Municipal solid waste generation and management | Public, UN-Habitat terms (to check) |
| Tracking SDG 7 energy progress report | Access to electricity and clean cooking | Open, CC BY 3.0 IGO |
| IBNET utility benchmarking | Utility coverage, continuity and finance | Public, World Bank terms (to check) |
| Utility and municipal annual reports | Service, investment and performance data | Public records, licence per publisher |
Model urban utilities as a system. Run the cascade.
Assembled from the Nexus Standards area profile Cities and the built environment: 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
- Ice-jam flood
- Earthquake
- Dam failure
- Aftershock sequence (set off downstream)
- Fault surface rupture (set off downstream)
- Soil liquefaction (set off downstream)
- Slope slide (set off downstream)
- Rockfall (set off downstream)
- Tsunami (set off downstream)
- Building collapse (set off downstream)
- Widespread power outage (set off downstream)
- Water supply failure (set off downstream)
- Mass displacement (set off downstream)
- Disaster and conflict debris (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Turbidity current (set off downstream)
- Seismically and structurally vulnerable stock (set off downstream)
Systems and couplings
- Cities and the built environment
- Construction and real estate Coupling
- Water utilities and basins Coupling
- Public sector and government Coupling
- Energy utilities and grids Coupling
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-5Figure, map and visualisation standard (with the UI/UX kit)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-X5Cities and built environment riskNRS-H91Hazard family: Urban and building-stock stress (NHS-1 infra.urban)NRS-H113Hazard family: Financial-system fragility (NHS-1 soc.financial-system)NRS-K7Domain pack profile: Cities urban (DOMAIN-007)NRS-H31Hazard family: Persistent and bioaccumulative substances (NHS-1 poll.persistent)NRS-H34Hazard family: Waste and residue failures (NHS-1 poll.waste)
Observation
- Global Human Settlement Layer (listed for reference)
- WorldPop gridded population (listed for reference)
- Overture Maps buildings theme (listed for reference)
- OpenStreetMap (listed for reference)
- World Development Indicators (listed for reference)
- Direct economic loss in relation to global GDP, damage to critical infrastructure and number of disruptions to basic services, attributed to disasters
- Proportion of local governments that adopt and implement local disaster risk reduction strategies in line with national strategies
- Proportion of urban population living in slums, informal settlements or inadequate housing
- Percentage of local governments that adopt and implement local disaster risk reduction strategies in line with national strategies
Example geography
- India: 65 hexagonal cells
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
Who decides, and what the evidence serves.
Cities and Built Environment 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 |
|---|---|---|
| Utilities | Where to extend networks and how to prioritise maintenance | Coverage maps; performance profiles |
| City governments | How to organise waste collection and drainage maintenance | Drainage and waste assessments; flood records |
| Regulators | Which tariffs and service obligations to set | Performance and finance profiles |
Outputs this topic produces
- Service coverage maps by neighbourhood and provider type
- Drainage and waste interaction assessments
- Utility performance and finance profiles
- Evidence notes on extending service to unserved areas
How urban utilities 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 utilities: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What experts ask.
- 01
Who is served, and how well?
Coverage, reliability, quality and affordability of each service across neighbourhoods.
- 02
How do utilities depend on each other?
Which failures in one service stop another, and how quickly.
- 03
How do hazards affect utilities?
Flooding of substations and treatment works, heat stress on networks, drought limits on supply.
- 04
What keeps services running?
Backup power, storage, redundancy, mutual aid and restoration priorities.
What drives the risk.
Utility networks share space and dependencies. Water pumping and treatment, wastewater lifting and telecommunications all need electricity; electricity generation often needs cooling water; control systems need communications. A long outage therefore spreads from one service to all.
Ageing assets and underinvestment raise everyday failure rates, which reduces the capacity to absorb hazards. Leakage, intermittent supply and blocked drains are chronic in many cities.
Solid waste is often overlooked. Uncollected waste blocks drains, worsening floods, and burns or decomposes into health hazards.
Digitalisation adds a new layer. Smart meters, remote control and shared cloud services improve efficiency but create common points of failure and cyber exposure across services that once failed separately. Restoration also competes for the same crews, fuel and spare parts, so priorities set in advance matter.
How evidence is gathered, and where it stops.
| Method or data | What it shows | Its limit |
|---|---|---|
| Utility performance data | Coverage, outages and quality | Often confidential or inconsistent |
| Asset and network maps | Location and connection of assets | Incomplete for older or informal networks |
| Dependency models | How failures spread | Rely on assumed backup durations |
| Household surveys | Service as experienced | Self-report and sampling limits |
How it is studied, and what the methods cannot say.
- 01Water and environmental engineeringUrban drainage design · Sanitation for unserved areas · Waste and drainage linksApplied here
- 02Geospatial information systemsUrban exposure databases · Community mapping · Hazard overlay for planningApplied here
- 03Spatial statistics and geostatisticsSmall-area estimation · Spatial clustering of disadvantage · Interpolating urban temperatureApplied here
- 04Energy generation, storage and grid technologyBuilding energy and overheating · Rooftop solar potential · Energy poverty mappingApplied here
- 05Sensors, IoT and observation networksLow-cost air and heat sensors · Drain and flood sensors · Privacy in urban 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 safely managed drinking water?
Why does waste collection affect flooding?
Who serves areas without networks?
Is this the same as the Critical Infrastructure platform?
Does the platform assess utility operators?
Why include solid waste?
Contribute evidence from this page.
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