GCRI · Cities and Built Environment
Urban growth and land
Cities grow outward and upward, and the land they grow onto decides much of their future risk, cost and emissions. Expansion onto floodplains, steep slopes and coasts locks in exposure for generations, while sprawl raises the cost of services and travel. This page sets out how urban growth happens, how it is measured consistently across countries, and what evidence serves the planners and governments who shape it.
Urban growth and land on the record.
Urban growth and land: how the risk develops.
Settlement expansion and land use. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Expansion outpaces planning
Population and income growth drive demand for land faster than plans, infrastructure and titling can follow. Growth then happens first and services arrive later, if at all.
Cheap land is often hazardous land
Floodplains, wetlands and unstable slopes are left vacant because they are risky, which makes them affordable. Settlement there converts hazard into risk.
Density shapes cost and exposure
Compact growth reduces travel and service costs per person but concentrates exposure. Sprawl spreads exposure and raises infrastructure cost. Both need planning for hazards.
Urban form lasts for centuries
Street patterns, plot sizes and trunk infrastructure, once built, are very hard to change. Decisions taken during rapid growth fix risk and efficiency for the long term.
Urban signals in India.
Population density, night lights 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
- 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
- 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
- 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
- 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 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
- 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
Where cities grow decides future exposure in every domain.
- WaterCouplingGrowth on floodplains and drained wetlands raises flood risk.What to watchNew settlement in flood zones
- BiodiversityCouplingUrban expansion converts farmland and habitat.What to watchLand converted per year
- FoodCouplingPeri-urban farmland feeds cities and is lost first.What to watchPeri-urban cropland change
Growth analyses are designed for the Country Systems Risk and Resilience series. The Degree of Urbanisation (adopted by the UN Statistical Commission in 2020) and the Global Human Settlement Layer make cities comparable.
- Local land-use change records.
- Planning permission data.
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 growth and land · Riverside ward · Flood 1-in-100 overlay
Hazard overlay
flood scenario on asset register
RiverFlood extentExposed asset
Exposed assets
| H-01 | Clinic | 0.3 |
| S-07 | School | 0.5 |
| E-03 | Substation | 1.4 |
| W-02 | Pump station | 1.3 |
Adaptation options
| Raise substation E-03 | 1 | Medium | Service continuity | Design |
| Retention park upstream | 13 | 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 |
|---|---|---|---|---|
| Ratio of land consumption rate to population growth rate | ratio | per assessment period | SDG indicator 11.3.1 methods | ESTIMATED |
| Built-up area | square kilometres | per epoch | Satellite built-up area products | OBSERVED |
| Urban population density | people per square kilometre of built-up area | per census | Population grids and built-up area | ESTIMATED |
| New built-up area in hazard zones | hectares | per epoch | Built-up area overlaid on hazard maps | ESTIMATED |
| Population by degree of urbanisation class | people | per census | Degree of Urbanisation classification | Published statistics |
| Land with approved plans before development | percent of new built-up area | per assessment | Planning 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
- 13%
- Assets still working
- 44%
- Amplification of the initial damage
- 4.3 times
- Steps to settle
- 2
Numbers, methods and sources
| Step | Transport working (%) | Power working (%) | Telecoms working (%) |
|---|---|---|---|
| 0 | 94 | 83 | 83 |
| 1 | 50 | 67 | 39 |
| 2 | 44 | 61 | 28 |
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 |
|---|---|---|
| Global Human Settlement Layer (European Commission JRC) | Built-up area, population and settlement classes over several epochs | Open, CC BY 4.0 |
| UN DESA World Urbanization Prospects | Urban and city population estimates and projections | Open, CC BY 3.0 IGO |
| UN-Habitat Urban Indicators Database | SDG 11 indicator data for cities and countries | Public, UN-Habitat terms (to check) |
| ESA WorldCover | Global land cover at ten-metre resolution | Open, CC BY 4.0 |
| Atlas of Urban Expansion (NYU Marron Institute) | Expansion, density and layout for a global sample of cities | Licence to check |
Model urban growth and land 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 |
|---|---|---|
| City and regional planning authorities | Where to direct growth and which land to protect | Expansion and hazard overlays; plan coverage |
| National ministries of urban development | How to support planned expansion and trunk infrastructure | Growth projections; density profiles |
| National statistics offices | How to classify urban and rural areas consistently | Degree of Urbanisation results |
Outputs this topic produces
- Urban expansion analyses with hazard overlays
- Degree of Urbanisation classifications for national statistics
- Density and land-use efficiency profiles by city
- Evidence notes for planning ahead of growth
How urban growth and land 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 growth and land: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What experts ask.
- 01
Where is growth happening?
Which areas are being built on, how fast, at what density and with what access to services.
- 02
What land is being converted?
How much farmland, wetland, forest and floodplain is lost to development and what functions disappear with it.
- 03
Who decides land use?
How plans, markets, customary tenure and informal occupation interact.
- 04
What does growth cost?
How density and pattern affect the cost of roads, pipes, transport and emergency services.
What drives the risk.
Urban land often expands faster than urban population, so average densities fall and the fringe sprawls. Low-density growth raises the per-person cost of infrastructure and makes public transport harder to sustain. Very high density without services creates its own risks, from fire spread to overcrowding.
Land markets push growth towards cheaper land, which is often cheaper because it is hazardous or unserviced. Where planning is weak or slow, settlement precedes infrastructure, and retrofitting services later is costly and causes disruption.
Land conversion removes natural functions. Wetlands and floodplains store water; vegetation cools; soils absorb rainfall. Sealing them raises flood peaks and heat downstream and nearby.
How evidence is gathered, and where it stops.
| Method or data | What it shows | Its limit |
|---|---|---|
| Satellite land-cover series | Built-up expansion over time | Classification errors at the urban edge |
| Cadastre and planning records | Legal land use and tenure | Incomplete where tenure is informal or customary |
| Hazard overlays | Growth in exposed zones | Hazard maps can be outdated or coarse |
| Density and service models | Infrastructure cost of growth patterns | Depend on cost assumptions |
How it is studied, and what the methods cannot say.
- 01Geospatial information systemsUrban exposure databases · Community mapping · Hazard overlay for planningApplied here
- 02Spatial statistics and geostatisticsSmall-area estimation · Spatial clustering of disadvantage · Interpolating urban temperatureApplied here
- 03Earth and geophysical scienceSeismic microzonation · Urban subsidence monitoring · Landslide hazard on urban slopesApplied here
- 04Social and behavioural scienceHousing and tenure surveys · Participatory planning research · Displacement studiesApplied 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 the Degree of Urbanisation?
Why does urban sprawl matter for risk?
How is urban expansion measured?
Is compact growth always safer?
Can satellite data show informal growth?
Does the platform recommend where cities should grow?
Contribute evidence from this page.
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