Skip to content

GCRI · Cities and Built Environment

Green blue infrastructure

Parks, street trees, green roofs, wetlands, rivers and ponds are green and blue infrastructure: they cool streets, absorb and slow stormwater, clean air and water, support biodiversity and improve wellbeing. Their benefits depend on design, location and maintenance, and are often unequally shared. This page sets out how they work, how their performance is measured, and what evidence serves the city authorities and communities that plan and care for them.

01Register

Green blue infrastructure on the record.

02The question

Green blue infrastructure: how the risk develops.

Nature-based urban interventions. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

Shade and evaporation cool

Trees shade surfaces and people, and vegetation and water cool air through evaporation. The cooling is strongest in and next to green and blue spaces and fades with distance.

Mechanism

Soil and plants hold water

Permeable ground, rain gardens, swales and wetlands store and infiltrate rainwater, reducing runoff peaks. Their capacity is limited in very large storms and when soils are saturated.

Mechanism

Benefits are unequally shared

Wealthier neighbourhoods often have more trees and parks. New green investment can raise property values and displace residents unless housing is protected.

Mechanism

Living assets need care

Trees take years to grow and die without watering and maintenance. Green infrastructure performs only as long as it is managed, which needs budgets and skills.

03Geography

Infrastructure exposure in India.

Night lights, population density and flood water 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

Infrastructure exposure, 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 (clouds leave gaps)
Source
VIIRS Global Flood Product (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite detection; clouds leave gaps
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite detection; clouds leave gaps. 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
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
MODIS Terra EVI (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite index; clouds leave gaps
Newest at build
2026-10-13
Resolution
about 250 m grid
Uncertainty
Satellite vegetation index for the 8 days to the date shown, a habitat condition indicator; not a measure of species or biodiversity.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map

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 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-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
  • 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).
  • 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

04Across the domains

Green and blue infrastructure couples nature to urban water, heat and health.

Evaluations are designed for the Evidence Brief series. The IUCN Global Standard for Nature-based Solutions (2020) sets design and verification criteria.

  • Monitoring of green infrastructure performance.
  • Maintenance and cost records.
05Monitor

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.

Urban heat console: the screen’s structure, terms and states for Green blue infrastructure.Example names and illustrative values; a design, not a record or a live system.
06Indicators

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.

IndicatorUnitCadenceSource typeLabel
Share of built-up area that is open space for public usepercentper assessmentSDG indicator 11.7.1 methodsESTIMATED
Tree canopy coverpercent of areaper assessmentAerial and satellite imageryOBSERVED
Population within walking distance of green spacepercent of populationper assessmentAccessibility analysisMODELLED
Impervious surface coverpercent of areaper assessmentSatellite land coverOBSERVED
Stormwater retained by green infrastructurecubic metres per design stormper projectHydrological modelling and monitoringMODELLED
Street trees planted and survivingcount and survival percentannualMunicipal tree inventoriesREPORTED
07Simulator

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
19%
Assets still working
44%
Amplification of the initial damage
3.0 times
Steps to settle
3
Numbers, methods and sources
StepTransport working (%)Power working (%)Telecoms working (%)
0897878
1785633
2675022
3675017

Methods

  1. Interdependent networks Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464
  2. Overload cascades Motter and Lai (2002), Physical Review E 66
  3. Betweenness load Brandes (2001), Journal of Mathematical Sociology 25
  4. Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
  5. Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
  6. Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
  7. 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
A cascade through interdependent networks. Illustrative teaching model: it runs on the values set by the controls, not on measured data. 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).
08Sources

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.

SourceWhat it givesLicence class
ESA WorldCover and Copernicus land monitoring productsLand cover and imperviousnessOpen, CC BY 4.0 and Copernicus terms
Municipal tree inventoriesLocation, species and condition of street treesOpen data where published, licence per city
UN-Habitat SDG 11.7.1 dataPublic open space in citiesPublic, UN-Habitat terms (to check)
IUCN Global Standard for Nature-based SolutionsCriteria for designing and assessing nature-based solutionsPublic, IUCN terms
Urban hydrology monitoring studiesMeasured performance of rain gardens, swales and green roofsLicence per publication
09Twin and cascade simulator

Model green blue infrastructure 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)

Controls

  • NS-0 Constitution and principles
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-5 Figure, map and visualisation standard (with the UI/UX kit)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NRS-X5 Cities and built environment risk
  • NRS-H91 Hazard family: Urban and building-stock stress (NHS-1 infra.urban)
  • NRS-H113 Hazard family: Financial-system fragility (NHS-1 soc.financial-system)
  • NRS-K7 Domain pack profile: Cities urban (DOMAIN-007)
  • NRS-H31 Hazard family: Persistent and bioaccumulative substances (NHS-1 poll.persistent)
  • NRS-H34 Hazard 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
10Decisions

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 decidesThe questionEvidence this page serves
City parks and environment departmentsWhere to plant trees and create green space firstEquity maps; heat and canopy evidence
Stormwater and drainage authoritiesWhere green infrastructure can reduce flooding and by how muchPerformance assessments
Housing and planning authoritiesHow to green neighbourhoods without displacing residentsEquity and housing evidence

Outputs this topic produces

  • Canopy and green space equity maps
  • Stormwater performance assessments for green infrastructure
  • Cooling evidence from satellite and sensor data
  • Maintenance and survival tracking methods
11Methods and evidence

How green blue infrastructure 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 green blue infrastructure: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−++CitiesCritical infrastructureSocietyCommunitiesEconomyR reinforcingB balancing
Causal loop diagram from the page’s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
12Core questions

What experts ask.

  1. 01

    What does each intervention deliver?

    Cooling, flood storage, water quality, biodiversity and health benefits, and how they vary with design and scale.

  2. 02

    How reliable is it?

    How performance changes with drought, maintenance and extreme events beyond design.

  3. 03

    Who benefits?

    Whether green space is distributed fairly or raises land values and displaces residents.

  4. 04

    How does it combine with grey infrastructure?

    Where hybrid designs outperform either approach alone.

13Mechanisms

What drives the risk.

Vegetation cools through shade and evaporation. Permeable surfaces and wetlands slow and store runoff, reducing flood peaks. Soils and plants filter pollutants. These effects are real but depend on species, water availability, maintenance and the size and connection of green areas.

Nature-based measures have different risk profiles from engineered ones. They may take years to mature, can fail in drought or disease, and their capacity in extreme events is harder to specify. They also deliver co-benefits engineered systems do not.

Greening can raise property values and rents, a process sometimes called green gentrification, which can displace the residents it was meant to help.

Climate change alters the baseline. Species chosen today must cope with tomorrow’s heat and drought, and urban trees under water stress cool less. Design therefore needs to plan for irrigation, species diversity and replacement over decades.

14Methods and limits

How evidence is gathered, and where it stops.

Method or dataWhat it showsIts limit
Field monitoringMeasured cooling or runoff reductionSite-specific; hard to generalise
Hydrological modelsFlood storage under design stormsUncertain for extremes beyond calibration
Remote sensing of vegetationCanopy cover and changeDoes not show condition or function
Social surveysUse, perceived benefit and equitySelf-report limits
16Where this page’s references

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.

17Questions

Questions and answers.

What is green infrastructure?
A network of natural and semi-natural areas and features, such as parks, trees, green roofs and wetlands, planned to deliver services like cooling, stormwater management and recreation.
Can trees reduce urban heat?
Yes, through shade and evaporation, mostly in and near the canopy. The effect depends on species, density, water availability and street layout.
What is a nature-based solution?
An action that protects, manages or restores ecosystems to address a societal challenge while benefiting people and biodiversity, as defined by IUCN and UNEA.
Can green infrastructure replace drains and flood defences?
Sometimes in part, rarely in full. Evidence generally supports combining nature-based and engineered measures.
How long before benefits appear?
It varies. Permeable surfaces work at once; tree canopy may take years to mature. Plans should state the time profile.
Who maintains it?
Maintenance is a decision for owners and authorities. Without it, performance declines, so research treats maintenance as part of the design.
ReportsContribute

Contribute evidence from this page.

Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

GCRICities and Built EnvironmentGlobal Sector Risk and ResilienceEvidence Brief
Cities and Built Environment

Bring a method, a dataset or a question.

Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.