GCRI · Cities and Built Environment
Buildings and heat
Cities are hotter than their surroundings, and their buildings decide how much of that heat reaches the people inside. Dark surfaces, dense construction, little shade and waste heat raise urban temperatures, while poorly insulated or unventilated homes trap heat at night. This page sets out how urban heat develops, how it is measured inside and out, and what evidence serves the health, housing and city authorities that respond to it.
Buildings and heat on the record.
Buildings and heat: how the risk develops.
Building performance and urban heat. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
The urban heat island
Paved and built surfaces absorb sunlight and release it slowly, while less vegetation means less evaporative cooling. Cities stay warmer than rural areas, especially at night.
Indoor heat follows the building
Insulation, orientation, glazing, ventilation, thermal mass and roof colour set indoor temperatures. Top-floor flats and lightweight roofs can be much hotter than outside air.
Exposure is unequal
Older people, those with chronic illness, outdoor workers and people in poor housing face the greatest risk. Hot neighbourhoods often have fewer trees and poorer housing.
Cooling raises demand
Air conditioning protects health but raises electricity demand and waste heat. Peak demand during heatwaves can strain grids, and those who cannot afford cooling remain exposed.
Climate signals in India.
Daytime surface heat, population density and night-time 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
Climate signals, for this page
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
- 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 at night, when lack of cooling matters for health; not air temperature 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
- 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
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.
Climate 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 · NASA JPL OPERA DIST-ALERT · NASA AIRSSources 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 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
- 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
- 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
- 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
- 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).
- Observed (EO): NASA AIRS. 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 (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change 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 (22 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
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 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, night, 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
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
Buildings are where heat meets people.
Building heat studies are designed for the Country Quarterly series. UNEP’s Global Cooling Watch (2023) and WMO and WHO heat-health guidance (2015) frame the evidence.
- Indoor temperature monitoring data.
- Evaluations of passive cooling.
Urban heat console.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
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 |
|---|---|---|---|---|
| Land surface temperature | degrees Celsius | per satellite overpass | Satellite thermal imagery | OBSERVED |
| Air temperature difference urban to rural | degrees Celsius | hourly | Urban and reference weather stations | OBSERVED |
| Indoor temperature in monitored dwellings | degrees Celsius | hourly | Indoor sensors | OBSERVED |
| Tree canopy cover | percent of area | per assessment | Aerial and satellite imagery | OBSERVED |
| Heat-related excess mortality | deaths above expected | per heat season | Mortality statistics and models | ESTIMATED |
| Households with access to cooling | percent of households | per survey | Household surveys | REPORTED |
Model buildings and heat 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
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 |
|---|---|---|
| Landsat Collection 2 surface temperature (USGS) | Land surface temperature at thirty-metre resolution | Public domain, US government data |
| ECOSTRESS (NASA) | Land surface temperature at different times of day | Open, NASA data policy |
| Copernicus Urban Atlas and street tree layer | Urban land use and trees for European cities | Free, Copernicus terms |
| WHO and WMO heat-health guidance | Heat-health action planning and warning systems | Public, WHO and WMO terms of use |
| IEA cooling and buildings data | Cooling demand and appliance ownership | Licence per dataset (to check) |
Coupled risk, applied response.
The sectors heatwave touches and how strongly they depend on each other: what a study has to observe and model together.
Choose a context
Sectors · HeatwaveStress
Pillars · HeatwaveKPI
In this contextDependence or handoff, heavier is strongerOutside this context
Programme yearAll phases
Context
Heatwave
Cooling demand peaks the grid while rivers warm; heat stress fills hospitals and wilts crops.
W · E · I · F · H · B
Risk
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.43 share of total
Hover a corner, a line or a row to trace it across both sides.
Route
Applied to heatwave
L · F · U · S · R · A
Response
- Pillars
- 4 of 6
- Handoffs
- 10 of 18
- Loops
- 5 closed
Expected value
- What is at stake
- –no published benchmark
- Return on resilience
- –no published benchmark
- Avoided loss
- 1,190deaths avoided a yearHess et al., J. Environ. Public Health, 2018
Hover a pillar, a line or a row to read how it is applied.
A: a teaching cascade (shock 0.6, gain 0.35, four rounds) over teaching values for a typical city-region, not measurements. B: illustrative applications and the KPI each pillar answers for; values are published benchmarks, cited, not forecasts. Open events: NASA EONET, live.
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 governments | Where to plant trees, add shade and cool surfaces first | Heat maps; canopy cover; vulnerability profiles |
| Public health agencies | Who to reach and when during heatwaves | Vulnerability profiles; excess mortality evidence |
| Building regulators and housing agencies | Which standards and retrofits prevent indoor overheating | Indoor overheating assessments |
Outputs this topic produces
- Urban heat maps combining satellite, station and sensor evidence
- Indoor overheating assessments for housing types
- Heat vulnerability profiles by neighbourhood
- Evidence notes for heat-health action plans
How buildings and heat 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 buildings and heat: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What experts ask.
- 01
Where is heat most dangerous?
Which neighbourhoods and building types reach the highest indoor and outdoor temperatures.
- 02
Who is most at risk?
Older people, people living alone, those with chronic illness, outdoor workers and residents of top-floor or poorly ventilated homes.
- 03
What reduces indoor heat?
The effect of shading, insulation, ventilation, reflective surfaces and thermal mass.
- 04
How does cooling affect the grid?
How rising air-conditioning demand interacts with power supply during heatwaves.
What drives the risk.
The urban heat island arises because built surfaces absorb and store solar energy and release it slowly, vegetation and evaporation are reduced, and vehicles, industry and cooling equipment add waste heat. Night-time warmth is particularly harmful because bodies cannot recover.
Indoor conditions depend on design. Lightweight roofs, large unshaded glazing and poor ventilation can make homes hotter than outdoors. Insulation helps or harms depending on climate and ventilation. Mechanical cooling protects occupants but raises electricity demand and adds heat outside.
Heat risk is social. Isolation, poverty and illness turn high temperatures into deaths, which is why public health and housing must be considered together.
How evidence is gathered, and where it stops.
| Method or data | What it shows | Its limit |
|---|---|---|
| Thermal satellite imagery | Surface temperature patterns | Surface is not air or indoor temperature |
| Street and indoor sensors | Actual temperatures people experience | Sparse networks, calibration needs |
| Building energy simulation | Performance of design options | Depends on occupant behaviour assumptions |
| Health records | Heat-related illness and mortality | Under-recording and attribution limits |
How it is studied, and what the methods cannot say.
- 01Energy generation, storage and grid technologyBuilding energy and overheating · Rooftop solar potential · Energy poverty mappingApplied here
- 02Sensors, IoT and observation networksLow-cost air and heat sensors · Drain and flood sensors · Privacy in urban sensingApplied here
- 03Spatial statistics and geostatisticsSmall-area estimation · Spatial clustering of disadvantage · Interpolating urban temperatureApplied here
- 04Water and environmental engineeringUrban drainage design · Sanitation for unserved areas · Waste and drainage linksApplied here
- 05Social 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 urban heat island?
Why is land surface temperature different from air temperature?
How can buildings stay cooler?
Is air conditioning the answer to urban heat?
Does the platform issue heat warnings?
Why does night-time temperature matter?
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