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GCRICities and Built EnvironmentIn development
Methods and uncertainty

Methods and uncertainty

The methods Cities and Built Environment relies on, the assumptions they carry and the limits of what they can show.

Publisher
The Global Centre for Risk and Innovation
Field
Cities and built environment, Critical infrastructure, Society and human development
Canvas · draft to published versionDesign, not a record
Methods and uncertainty: systematic evidence synthesisA question is framed with its owner and a protocol registered; records are searched, screened and checked for eligibility by two reviewers; data are extracted, synthesised and graded for certainty before a brief is written. Design of the process, not a record of a run.

Fig.How a finding is reviewed before it is published. Design, not a record.

01In brief

The short answer.

The Cities and Built Environment methods page sets out the methods the platform relies on, among them structural and earthquake engineering, urban and transport engineering, and geospatial information systems, with their assumptions, validation and limits. Each analysis lists its assumptions and data, reports ranges and confidence beside central estimates, is checked against observations or other models, and states what it cannot show.

02Geography

Urban signals in India.

For methods and uncertainty, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, night lights and land cover with true colour from NASA GIBS, framed on India; 3 further NASA layers wait in the list.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Urban signals, for this page

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.

For methods and uncertainty, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, night lights and land cover with true colour from NASA GIBS, framed on India; 3 further NASA layers wait in the list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA HLS S30 · Copernicus Sentinel-2 L2ASources 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 H3 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 H3 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 H3 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 H3 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 H3 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 H3 cells where shown (modified). CC BY 4.0
  • 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 H3 cells where shown (modified). 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 H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 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.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer
  • Optional layers (17 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

  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • 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
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026

04Method register

Each method, its role in this field and how it is checked.

05Uncertainty

Where uncertainty in urban analysis comes from, and how it is shown.

SourceWhy it matters hereHow it is reported
Built-up extentProducts differ in definition and resolutionProduct named, accuracy stated
Building inventoriesAttributes such as construction type are often inferredInferred attributes labelled
Urban climateHeat varies street by streetResolution of heat products stated
Population at night and dayExposure differs by time of dayBoth shown where available

City-level indicators follow ISO 37120 and 37123 definitions where cities report them.

06Uncertainty

How uncertainty is reported.

  1. 01

    State assumptions

    Each analysis lists its assumptions and the data it depends on.

  2. 02

    Quantify where possible

    Ranges and confidence are reported alongside central estimates.

  3. 03

    Validate and compare

    Models are checked against observations and, where possible, against other models.

  4. 04

    Publish limits

    What an analysis cannot show is stated beside what it can.

07Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

TermDefinition
Uncertainty quantificationCharacterising and propagating the uncertainties in a model to state confidence in its outputs.
Sensitivity analysisRepeating an analysis under different assumptions to show how much the result depends on them.
Model validationComparing model predictions with independent observations to judge fitness for a stated use.
Structural and earthquake engineeringStructural and earthquake engineering designs buildings, bridges and other structures to carry loads safely, including those from earthquakes, wind and floods.
09Questions

Questions and answers.

Are the methods open?
Method descriptions are public on the STEM Commons. Code and data follow their own licences and access terms, listed in the source register.
Cities and Built Environment

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