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GCRIDisaster Resilience and RecoveryIn development
Dependencies and consequences

Dependencies and consequences

Disasters are rarely confined to the area a hazard strikes. They travel through infrastructure, supply chains, public budgets, health systems and social networks, and they interact with other hazards and crises. This page sets out the main pathways by which disaster impacts cascade, and how weak preparedness and recovery in one system raise risk in others. It describes connections; it is not a forecast.

Publisher
The Global Centre for Risk and Innovation
Field
Disaster and crisis, Climate and hazards
Status
In development
Service level
R0: information and enquiries

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

Layers 4

Hazards now, 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 flood water, population density, active fires and true-colour imagery, framed on the Philippines; every other NASA layer, live feed and forecast waits in the layer 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 EONET · GDACS · 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
  • 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
  • NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); 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.
  • Live: NASA EONET Events are indicative, not official warnings.
  • Live: GDACS (EC JRC / UN OCHA) Events are indicative, not official warnings.
  • Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer
  • Optional layers (35 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

  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Active fires and thermal anomalies, last day: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026

GeographyFor dependencies and consequences, in GCRI's spatial-intelligence reading, the map opens on flood water, population density, active fires and true-colour imagery, framed on the Philippines; every other NASA layer, live feed and forecast waits in the layer list.

STEM methods
8
Canonical methods this field applies
Topics
8
Subject pages in the field
Counterparts
10
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 Disaster Resilience and Recovery describe how disaster and crisis as well as climate and hazards connect to other systems through physical, economic, social and ecological links, and how stress travels along them toward fields such as those of Diplomacy Nexus and Climate and Nature Governance. 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: Disaster Resilience and Recovery 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 Disaster resilience.Placeholder names and illustrative values; a design, not a record or a live system.
04Pathways

How disaster impacts cascade.

Physical

Infrastructure chains

Power, water, transport, fuel and communications depend on each other. Loss of one can halt the others, and restoring them in the wrong order delays recovery.

Economic

Supply chains and budgets

Disrupted suppliers stop production elsewhere. Emergency and reconstruction costs strain public budgets and can crowd out development spending.

Social

Households and services

Displacement, lost income and interrupted schooling and healthcare can persist long after physical repair, and fall hardest on those with fewest reserves.

05Compounding

When crises overlap.

Compound and cascading events are increasingly central to the field. A heatwave during a power outage, an earthquake that triggers landslides and dam failures, a cyclone during an epidemic or a flood in a place already affected by conflict each create demands that single-hazard plans do not anticipate. Response capacity used for one event is unavailable for the next, and recovery from one shock can be interrupted by another.

Weak recovery is itself a pathway. When reconstruction rebuilds exposure, when livelihoods are not restored, or when debts taken on after one disaster limit the response to the next, risk accumulates over time. Tracking these slow pathways requires following places and households for years, not weeks.

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

How dependencies are analysed.

Cascade analysis uses decision analysis under uncertainty, operations research and geospatial analysis, with evidence from past events and exercises. Every map states its assumptions and uncertainty; see methods and uncertainty.

A dependency map describes how stress could travel. It does not predict a specific event and does not assess any individual organization.

09Questions

Questions and answers.

Is a cascade map a forecast?
No. It describes connections and possible pathways. Scenarios used in exercises are labelled as such and carry their assumptions.
Why include public finance?
Because how a government pays for response and recovery shapes how fast and how well recovery happens. The financial side is examined at Public Finance and Sovereign Debt at GRA and Disaster Risk Finance at GRA.
Where do exercises fit?
Exercises are one of the best ways to discover hidden dependencies before a real event. See Multi-hazard exercises.
Disaster Resilience and Recovery

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