GCRI · Space and Earth Observation

Disaster monitoring

After floods, earthquakes, fires and storms, satellites map what happened over areas responders cannot reach. Mechanisms such as the International Charter and Copernicus Emergency Management Service provide imagery and maps to authorised users. This page sets out how disaster monitoring from space works, how quickly and accurately it delivers, and what evidence serves the agencies that request and use it.

01Register

Disaster monitoring on the record.

02The question

Disaster monitoring: how the risk develops.

Flood, heat and wildfire evidence. 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

Rapid tasking and acquisition

Satellites are tasked to image affected areas as soon as possible after activation. Timing depends on orbits, cloud and the queue of requests.

Mechanism

Change detection maps impact

Comparing images before and after an event maps flood extent, burned area and damaged buildings.

Mechanism

Accuracy varies with method

Damage grading from imagery misses damage invisible from above and can confuse similar features. Field checks estimate accuracy.

Mechanism

Access depends on mechanisms

Authorised users activate the Charter or Copernicus EMS. Countries without established links may get imagery later or not at all.

03Geography

Hazards now in the Arctic.

Flood water, population density and active fires over the Arctic, from NASA GIBS. Each layer carries its own date.

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

Layers 3

Hazards now, for this page

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
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
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
Observed (clouds and overpass timing leave gaps)
Source
VIIRS NOAA-20 375 m (FIRMS) (NASA LANCE FIRMS)
Provider
NASA LANCE FIRMS
Licence
NASA open data
Vintage
daily; Satellite detection; clouds and overpass timing leave gaps
Newest at build
2026-10-13
Resolution
about 500 m grid
Uncertainty
Satellite hot-spot detections for the day shown, including gas flares and industrial heat; not a confirmed fire, an incident report or a warning.
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
Estimated
Source
GPM IMERG (NASA GES DISC)
Provider
NASA GES DISC
Licence
NASA open data
Vintage
daily; Satellite estimate, near real time
Newest at build
2026-10-12
Resolution
about 2 km grid
Uncertainty
Satellite estimate, near real time. 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

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.

Hazards now, framed on the Arctic.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 · U.S. Geological Survey · 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 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
  • 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
  • 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 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
  • 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 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.
  • Live: U.S. Geological Survey 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 (20 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
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026

04Across the domains

Disaster monitoring from space serves response across domains.

Monitoring products are designed for the Observatory Signal series. The International Charter is activated by authorised users; satellite damage estimates are labelled estimated until checked on the ground.

  • Ground validation of damage maps.
  • Activation lessons.
05Monitor

EO tasking and products.

The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.

EO tasking and products

Disaster monitoring · Flood basin AOI · Activation ACT-149

Rapid mappingGCRI · Space and Earth Observation

Passes over the area

next 5 passes

SAT-1SAT-2SAT-3SAT-4Swath over the area of interestN

Acquisitions

P-1Radarn/aProcessed
P-2Optical62Cloudy
P-3Radarn/aDownlinking
P-4Optical28Scheduled

Product chain

  1. TaskAOI
  2. Acquireradar
  3. Downlinkstation 2
  4. ProcessARD
  5. Map floodchange
  6. Validatesamples
  7. Deliveruser agency
EO tasking and products: the screen’s structure, terms and states for Disaster monitoring.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
Charter and Copernicus EMS activationscount by hazardannualActivation recordsPublished statistics
Time from activation to first maphoursper activationActivation recordsOBSERVED
Damage assessment accuracypercent agreement with field surveyper eventValidation studiesESTIMATED
Area mappedsquare kilometresper activationMap productsOBSERVED
Countries with registered authorised userscountannualCharter and UN-SPIDER recordsPublished statistics
Products delivered in open formatspercent of productsper activationProduct metadataOBSERVED
07Twin and cascade simulator

Model disaster monitoring as a system. Run the cascade.

Assembled from the Nexus Standards area profile Climate risk standards: 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

  • Sea-level rise
  • Coastal flood (set off downstream)
  • Storm surge (set off downstream)
  • High-tide flooding (set off downstream)
  • Coastal erosion (set off downstream)
  • Saltwater intrusion (set off downstream)
  • Estuary flood (set off downstream)
  • Coastal habitat squeeze (set off downstream)
  • Wetland loss (set off downstream)
  • Mangrove loss (set off downstream)
  • Groundwater flood (set off downstream)
  • Climate-driven migration and relocation (set off downstream)
  • Mass displacement (set off downstream)

Controls

  • NS-0 Constitution and principles
  • NS-1 The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-3b Dataset and product metadata profile (STAC, DCAT, PROV-O)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-14 Conformance and crosswalk to external standards
  • NRS-H65 Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)
  • NRS-H62 Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)
  • NRS-H71 Hazard family: Deep-time and cosmic catastrophes (NHS-1 planet.deep-time)
  • NRS-H79 Hazard family: Mental health crises (NHS-1 health.mental)
  • NRS-H75 Hazard family: Climate-sensitive illness (NHS-1 health.climate-sensitive)
  • NRS-H7 Hazard family: Large-scale circulation anomalies (NHS-1 atmo.climate-mode)

Observation

  • ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
  • CMIP6 climate projections (Copernicus Climate Data Store) (listed for reference)
  • NGFS Scenario Explorer (listed for reference)
  • INFORM Risk Index (listed for reference)
  • Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population
  • Total greenhouse gas emissions per year
  • Direct economic loss attributed to disasters in relation to global GDP

Example geography

  • Pacific Island states: 150 hexagonal cells
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
  • Rain rate, last half hour (IMERG), NASA GIBS
  • Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
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
International Charter Space and Major Disasters activationsActivations and productsPublic summaries, Charter terms
Copernicus Emergency Management Service rapid mappingMaps and vector data for activationsFree, Copernicus terms
UN-SPIDER Knowledge PortalGuidance and recommended practices for space-based disaster informationPublic, UN terms of use
Sentinel AsiaRegional disaster imagery for the Asia-PacificPublic, terms to check
NASA Disasters ProgramProducts and data for disaster responseOpen, NASA data policy
09Methods and evidence

How disaster monitoring 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.

Earth observation chain

How a satellite or sensor record becomes evidence on disaster monitoring, and where each step adds uncertainty.

  1. 01 · Acquireorbit, sensor and revisitUncertainty: gaps from cloud and orbit
  2. 02 · Calibrateradiometric and geometricUncertainty: sensor drift
  3. 03 · Correctatmosphere and terrainUncertainty: aerosol and slope assumptions
  4. 04 · Retrieve or classifythe variable or the classUncertainty: model and training error
  5. 05 · Validateagainst ground truthUncertainty: sample design and size
  6. 06 · Publishwith error bars and lineageUncertainty: stated, never hidden
Processing chain in the CEOS Analysis Ready Data sense; each step records its uncertainty before a figure is drawn. A generic structure, not results.
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
10Decisions

Who decides, and what the evidence serves.

Space and Earth Observation 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
Civil protection authoritiesWhen and how to activate space-based mappingActivation guidance; timeline evidence
Space agencies and service providersHow to speed delivery and improve accuracyTimeline and accuracy reviews
Regional organisationsHow to ensure all countries can access imageryAccess gap evidence

Outputs this topic produces

  • Activation timeline analyses
  • Damage mapping accuracy reviews
  • Guidance on requesting and using space imagery
  • Evidence notes on access gaps
11Core questions

What experts ask.

Disaster scientists ask what satellites can show in time to make a difference.

  • How quickly after an event can reliable maps of flooding, fire or damage be produced?
  • Which sensors work in the conditions of the event, such as cloud during floods or smoke during fires?
  • How accurate are rapid maps, and how should their uncertainty be communicated to responders?
  • How can satellite data support preparedness and recovery, not only response?
  • How is satellite evidence combined with ground reports and local knowledge?
12Mechanisms and drivers

Timing, conditions and accuracy.

Different hazards suit different sensors. Floods often occur under cloud, so radar is essential for mapping inundation; thermal sensors detect active fires and hotspots; optical imagery maps burn scars and damage once skies clear; thermal data maps land surface temperature during heatwaves. Rapid-mapping arrangements can task satellites and deliver maps within hours to days, but satellite revisit times, processing and cloud cover set limits on how quickly evidence arrives.

Rapid maps trade accuracy for speed. Flood maps can miss water under vegetation or in dense urban areas; damage assessment from imagery can confuse undamaged roofs with damaged buildings. Responders benefit most when maps state their source, time and confidence, and when they are updated as better data arrives.

13Methods and data

How the evidence is built, and where it stops.

  1. 01

    Rapid mapping

    Fast processing of post-event imagery using Earth observation and geospatial information systems. Early products may be revised substantially.

  2. 02

    Change detection

    Comparing before and after images. Requires suitable pre-event images and careful co-registration.

  3. 03

    Active fire and heat products

    Thermal detection of fires and surface temperature. Small fires and fires under canopy can be missed.

  4. 04

    Damage assessment

    Interpreting building and infrastructure damage, with spatial statistics for sampling. Accuracy varies with image resolution and building type.

15Where 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.

16Questions

Questions and answers.

What is the International Charter Space and Major Disasters?
An agreement among space agencies to provide satellite data free of charge to authorised users in countries affected by major disasters.
How fast can satellites map a disaster?
Often within days, depending on satellite passes, cloud cover and processing. Radar can image through cloud, helping in floods and storms.
How accurate is satellite damage mapping?
Accuracy varies. Imagery shows roofs and visible destruction well but misses internal and partial damage, so field validation is needed.
How quickly can a flood map be produced?
It depends on when a satellite passes, the sensor and processing time. Arrangements exist to speed this up, but the first map may arrive hours to days after the event.
Why might a rapid map miss flooded areas?
Water under vegetation, in narrow streets or in shadow can be invisible to some sensors. Maps should state these limits.
Does the platform produce rapid maps for emergencies?
No. It studies methods and evidence quality. Rapid mapping is carried out by agencies and services with that operational mandate.
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