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GCRICritical InfrastructureIn development
Dependencies and consequences

Dependencies and consequences

Lifelines are coupled to each other and to wider economic, social and ecological systems. This page, part of Critical Infrastructure at The Global Centre for Risk and Innovation (GCRI), sets out the kinds of dependency that link infrastructure systems, how stress travels along them and why consequences often appear far from the original failure. It explains the framework the platform uses to describe dependencies, and the limits of any dependency map.

Publisher
The Global Centre for Risk and Innovation
Field
Critical infrastructure, Cities and built environment
Status
In development
Service level
R0: information and enquiries

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

Layers 3

Infrastructure exposure, 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 dependencies and consequences, in GCRI's spatial-intelligence reading, the map opens on night lights, true-colour imagery and population density with true colour from NASA GIBS, framed on Western Europe; 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 · Copernicus Sentinel-2 L2A · NASA HLS S30Sources 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 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
  • 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
  • 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
  • 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
  • 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): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer
  • 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).
  • Optional layers (14 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
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 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 cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026

STEM methods
12
Canonical methods this field applies
Topics
9
Subject pages in the field
Counterparts
3
Platforms in shared fields at GCRI, GRF and GRA
Report series
2
Nexus Reports series it contributes to
01In brief

The short answer.

Dependencies and consequences in Critical Infrastructure describe how critical infrastructure as well as cities and built environment connect to other systems through physical, economic, social and ecological links, and how stress travels along them toward fields such as those of Disaster and Crisis Governance and Development Finance Nexus. Every dependency map states its assumptions, data and uncertainty; it describes connections, not a forecast.

02Canvas

One field, three institutions.

Canvas · one field, three institutionsDesign, not a record
One field, three institutions: Critical Infrastructure and its counterpartsGCRI studies the field as science, GRF governs and convenes it, GRA builds shared financial understanding; the Nexus Universe tests work across them and the competent authorities decide. Design of the arrangement, not a record.

Fig.How GCRI, GRF and GRA share one field while the authorities decide. Design, not a record.

03Console

Field overview, in outline.

The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.

Field overview: the screen's structure, terms and states for Critical infrastructure.Placeholder names and illustrative values; a design, not a record or a live system.
04Kinds of dependency

Four ways systems are linked.

Physical

Material flows

One system's output is another's input: electricity to pumps, fuel to generators, water to cooling systems.

Cyber

Information flows

Control, metering and coordination depend on communications and shared software.

Geographic

Shared location

Assets in the same corridor, floodplain or building fail together under one hazard.

Logical

Rules and markets

Contracts, regulations and market rules couple systems without any physical link.

This four-part distinction is widely used in infrastructure research. Real dependencies often combine several kinds at once.

05How stress travels

From failure to consequence.

Cascades follow recognizable patterns. A common-cause failure strikes several systems at once, as when a flood inundates co-located substations and telecommunications exchanges. An escalating failure worsens a disruption in another system, as when a power loss outlasts the fuel supply of backup generators. A cascading failure passes directly from one system to the next. Restoration can also be blocked by dependencies, because repair needs power, communications and transport that are themselves disrupted.

The consequences extend beyond infrastructure. Loss of service halts production and trade, stretches public budgets and insurance, interrupts health care and education, and falls hardest on people with the least capacity to cope. Ecological effects follow when wastewater treatment or industrial safety systems fail. These pathways are examined in interdependency and cascade.

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
InterdependencyA two-way dependency between infrastructures, such as power needing telecoms for control while telecoms need power to run.
Cascading riskRisk that a failure in one system or component triggers failures in others that depend on it.
Compound eventTwo or more hazards or drivers occurring together or in sequence whose joint impact exceeds what either would cause alone, such as drought followed by intense rain; IPCC assessments use the term.
Dependency mappingTracing the people, processes, technology, facilities and suppliers a service relies on.
08Method and limits

How dependencies are analysed.

Dependency analysis uses network science and contagion, systems engineering and optimization and operations research, from input-output and network-flow models to agent-based simulation. Every map states its data, assumptions and uncertainty. No map is complete: many dependencies are undocumented, commercially confidential or discovered only in failure, and a dependency map describes how stress could travel, never a forecast of what will happen. Methods are set out on methods and uncertainty.

09Questions

Questions and answers.

Is a dependency map a forecast?
No. It describes how systems are connected and how stress could travel. Scenarios built on it are labelled as such, with their assumptions.
Why are dependencies hard to observe?
Many sit in contracts, shared corridors or assumptions about backup durations, and appear only when systems fail together.
Are specific facilities mapped publicly?
No. Methods are published at a level that supports understanding without disclosing security-sensitive details.
Critical Infrastructure

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