GCRI · Fields across the Consortium
Spatial intelligenceObservations, models and their uncertainty in one view
Insurance and catastrophe
Insurance is where physical risk is priced. The systemic concerns are the protection gap, the share of economic losses no one has insured, and the withdrawal of cover from places where risk is rising.
The field, seen three ways.
Science and evidence
No platform yet in this field.
Governance and dialogue
No platform yet in this field.
Financial understanding
Insurance Nexus, Reinsurance and Catastrophe, Disaster Risk Finance, Actuarial and Quantitative Risk
Activity and exposure worldwide.
Night lights, population density, flood water and true-colour imagery across the world, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 4
Activity and exposure, for this page
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.
Activity and exposure, framed on World. Layers as NASA publishes them, each with its own date.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 · U.S. Geological Survey · 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
- 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). 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 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
- 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). 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 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 authority warnings.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- 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).
- 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).
- Optional layers (6 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
Protection gaps and insurability.
When hazard rises faster than incomes and risk reduction, premiums climb, cover is withdrawn and losses shift to households and public budgets. Catastrophe models, built from hazard, exposure, vulnerability and financial modules, are the shared tool; their science inputs are where GCRI's work is relevant.
Hazard to loss: the exceedance curve.
How often a given loss is exceeded, from a Gumbel hazard, a lognormal fragility and a protection standard; the area under the curve is the average annual loss. Teaching model with stated illustrative values, not a prediction.
Controls
- Typical annual hazard intensity (location)
- 1.00 intensity index
- Spread of extremes (scale)
- 0.80 intensity index
- Intensity at which half the value is lost
- 4.00 intensity index
- Dispersion of vulnerability
- 0.55
- Share of value in the hazard footprint
- 40 %
- Protection standard (return period)
- 50 years
Readouts
- Average annual loss
- 0.51 % of value
- Loss at 1 in 100 years
- 24.5 % of value
- Loss at 1 in 250 years
- 28.4 % of value
- Intensity at 1 in 100 years
- 4.68 intensity index
Numbers, methods and sources
| Return period (years) | Intensity (intensity index) | Loss (% of value) |
|---|---|---|
| 1 | 0.09 | 0.00 |
| 2 | 1.27 | 0.00 |
| 4 | 1.91 | 0.00 |
| 7 | 2.47 | 0.00 |
| 13 | 3.00 | 0.00 |
| 24 | 3.51 | 0.00 |
| 44 | 4.02 | 0.00 |
| 82 | 4.53 | 23.55 |
| 154 | 5.03 | 26.44 |
| 287 | 5.53 | 28.87 |
| 536 | 6.03 | 30.88 |
| 1,000 | 6.53 | 32.53 |
Methods
- Gumbel extreme-value hazard Gumbel (1958), Statistics of Extremes, Columbia University Press
- Lognormal fragility (vulnerability) FEMA (2003), HAZUS-MH Technical Manual
- Exceedance-probability curve and average annual loss Grossi and Kunreuther (2005), Catastrophe Modeling, Springer
- Levee effect Di Baldassarre and others (2013), Socio-hydrology, HESS 17
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualizing uncertainty about the future, Science 333
- 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:
- Rivers Natural Earth
- Urban extents Natural Earth
- Cities Natural Earth
- Earthquakes M4.5+, past week (USGS) U.S. Geological Survey · register usgs.earthquake.summary-feeds
- Rain rate, last half hour (IMERG) NASA GPM IMERG Early · register nasa.gibs.context-live-layers
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo) Open-Meteo.com (CC BY 4.0), Copernicus GloFAS · register open-meteo.public-pages
- Built-up and settlement extent, 2010 (HBASE, Landsat) CIESIN/Columbia, NASA SEDAC HBASE · register sedac.context-urban-layers
Across the six pillars, led by Nexus Consortium
- Experiments Labs at GCRI: Nexus Labs
- Built in Foundry at GCRI: Nexus Foundry
- Tested at Universe at GCRI: Nexus Universe technical office
- Codified in For finance and insurance on Nexus Standards
- Published in Reports at GCRI: Publish
- Taught in Insurance, reinsurance and protection gaps on Risk Academy
Supervisory and development references.
| Framework or body | What it governs or supplies |
|---|---|
| IAIS Insurance Core Principles | Supervision of insurers, including climate risk application papers |
| Insurance Development Forum | Public-private work on protection gaps and risk modelling |
| Global Earthquake Model and open catastrophe modelling | Open hazard and risk components |
Model insurance and catastrophe as a system. Run the cascade.
Assembled from the Nexus Standards area profile Insurance and reinsurance: 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.
Hazards
- Tropical cyclone
- Earthquake
- Ice-jam flood
- Wildfire
- Storm surge (set off downstream)
- Intense rainfall (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Dangerous surf (set off downstream)
- Widespread power outage (set off downstream)
- Mass displacement (set off downstream)
- Coastal flood (set off downstream)
- 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)
Systems and couplings
- Insurance and reinsurance
- Banking Coupling
- Development finance institutions Coupling
- Humanitarian and civil society Coupling
- Agriculture and land use Coupling
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)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)NS-14Conformance and crosswalk to external standardsNRS-F3Insurance, catastrophe risk and protection gapsNRS-H113Hazard family: Financial-system fragility (NHS-1 soc.financial-system)NRS-U17Universe platform profile: Insurance NexusNRS-H71Hazard family: Deep-time and cosmic catastrophes (NHS-1 planet.deep-time)NRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-F8Parametric and index-based risk transfer
Observation
- OECD Data Explorer (incl. Creditor Reporting System, insurance and pension statistics) (listed for reference)
- Insurance statistics (listed for reference)
- USGS earthquake GeoJSON summary feeds (listed for reference)
- Direct economic loss attributed to disasters in relation to global gross domestic product (GDP)
- Direct economic loss attributed to disasters in relation to global gross domestic product
- (a) Number of commercial bank branches per 100,000 adults and (b) number of automated teller machines (ATMs) per 100,000 adults
Example geography
- Western Europe: 152 H3 hexagons at resolution 3
- Rain rate, last half hour (IMERG), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Carbon monoxide, smoke transport (AIRS), NASA GIBS
Hazard science to balance sheet.
Hazard inputs come from Climate and Hazards and Disaster Resilience and Recovery; financial understanding sits on GRA's platforms listed below.
The methods behind the field.
- Actuarial mathematics
- Extreme value theory and tail risk
- Probability and statistics
- Climate and atmospheric science
- Artificial intelligence and machine learning
- Earth and geophysical science
- Uncertainty quantification and model validation
- Hydrology and water science
- Ocean and coastal science
- Structural and earthquake engineering
- Economics and development economics
- Decision analysis under uncertainty
- Forecasting and time-series analysis
- Financial and risk engineering
- High-performance, cloud and edge computing
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.
Why does GCRI host field gateways?
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The same subject across the Consortium.
- GRFglobalriskforum.comBusiness continuity governanceMandates, commitments and accountability
- GRAglobalriskalliance.comInsurance and public poolsExposure, loss and capital
- Nexus Standardsnexustandards.comFor finance and insuranceStandards that apply
- Risk Academyrisksacademy.comInsurance, reinsurance and protection gapsWhere it is taught
- Nexus Reportstherisk.globalDisaster Resilience and Recovery in Nexus ReportsWhere it is reported
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