GCRI · Disaster Resilience and Recovery

Geospatial methods for disasters

Geospatial information systems locate hazard, exposure, vulnerability and capacity on the map. In this field they support risk mapping, damage assessment and the coordination of preparedness, response and recovery across agencies.

02Application

What geospatial information systems does here.

Geospatial information systems capture, store, analyse and present location-referenced data. They provide the common spatial frame for combining hazard, exposure and vulnerability information. In disaster and crisis and climate and hazards, geospatial analysis identifies where hazards overlap critical assets and vulnerable populations. It supports location-based planning across infrastructure, health and finance. The canonical description is on the STEM Commons.

Exposure mapping

Buildings, population, infrastructure and facilities are mapped and overlaid with hazard zones to show what is exposed.

Rapid damage assessment

Satellite and drone imagery is compared before and after events to grade building damage, with field checks to estimate accuracy.

Common operational data

Agencies agree on shared administrative boundaries, place names and baseline layers so that their data can be combined during response.

03Geography

Earth observation in the Philippines.

Population density, land cover and flood water over the Philippines, from NASA GIBS. Each layer carries its own date.

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

Layers 3

Earth observation, for this page

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
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
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
Observed (clouds leave gaps)
Source
MODIS Terra EVI (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite index; clouds leave gaps
Newest at build
2026-10-13
Resolution
about 250 m grid
Uncertainty
Satellite vegetation index for the 8 days to the date shown, a habitat condition indicator; not a measure of species or biodiversity.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
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
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

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.

Earth observation, framed on the Philippines.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
  • 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
  • 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
  • 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).
  • Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
  • 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 (11 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
  • 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
  • Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026

04Data

What the method consumes.

Datasets and records used by geospatial information systems on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.

DataRoleLabel
OpenStreetMapBuildings and roadsOBSERVED
Global Human Settlement LayerBuilt-up area and populationESTIMATED
Common operational datasets on HDXShared boundaries and baselinesPublished statistics
Copernicus EMS mappingDamage gradingOBSERVED
05Monitor

Spatial model.

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

Spatial model: the screen’s structure, terms and states for Disaster resilience.Example names and illustrative values; a design, not a record or a live system.
06Validation

How results are checked.

Positional and attribute accuracy are checked against surveyed control points and reference datasets. Topology rules and metadata standards ensure consistency.

CheckHow it is done
Positional accuracyLayers are checked against reference data
Damage grading accuracyRemote damage grades are compared with field surveys
Boundary and code consistencyDatasets use agreed boundaries and place codes

Errors in projection, scale and data currency propagate through analysis. Aggregation to administrative units can mask local variation.

07Twin and cascade simulator

Model geospatial methods for disasters as a system. Run the cascade.

Assembled from the Nexus Standards area profile Compound and cascading hazard 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

Controls

  • NS-0 Constitution and principles
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NRS-H61 Hazard family: Cascading failure (NHS-1 sys.cascade)
  • NRS-H62 Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)
  • NRS-H60 Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)
  • NRS-H94 Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)
  • NRS-H107 Hazard family: Digital infrastructure concentration and monoculture (NHS-1 tech.digital-concentration)
  • NRS-H7 Hazard family: Large-scale circulation anomalies (NHS-1 atmo.climate-mode)

Observation

  • Copernicus EMS rapid mapping activations (listed for reference)
  • OpenStreetMap planet and replication (listed for reference)
  • ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
  • Direct economic loss attributed to disasters in relation to global GDP
  • Number of disruptions to basic services attributed to disasters

Example geography

  • Bangladesh: 134 hexagonal cells
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Carbon monoxide, smoke transport (AIRS), NASA GIBS
  • Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
09Methods and evidence

How geospatial methods for disasters 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.

Uncertainty bands

How far the outlook for geospatial methods for disasters could spread, shown as ranges rather than a single line.

Now+5+10+15+20+25+30 yhighlowvery likely rangelikely range
Central estimate
median of the ensemble
Ranges
likely and very likely, in IPCC calibrated language
Ensemble
members, scenarios and initial conditions stated
Read with
the sensitivity of the result to each input
Illustrative ensemble spread on an index scale; the form follows IPCC uncertainty guidance. Not a projection.
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
10Stewardship

Who maintains the method.

Space and Earth Observation stewards geospatial information systems for the Consortium and reviews how it is applied across platforms.

11Process

How the process runs.

Process

Geospatial methods for disasters: Layers to published map

Layers enter with their rights, are aligned, analysed and checked for uncertainty, then released after public-safe review; a map is a governed spatial claim.

  1. 01 Data

    1. 01Source layers with their rightsDataset · NXS-GRX (canonical data, provenance and risk)Spatial views of The Global Risks Index (NXS-GRX) products sit under the boundary licence gate. Rights classification sets how a layer may be used.
  2. 02 Harmonise

    1. 02Coordinate reference and boundary versionRecord · NXS-EOP (earth observation and digital twins)The area of interest preserves its coordinate reference system, polygon validity and observation support. Boundary versions are kept.
    2. 03Harmonise units, variables and timeStepUnit metadata, conversion records and transformation logs are required. Alignment is an evidence event, not hidden preprocessing.
  3. 03 Analyse and check

    1. 04Analyse with a recorded processing recipeModel · GIS teamA processing recipe records parameters, calibration, inputs and output lineage. The analysis methods are named in each product’s own record.
    2. 05Spatial uncertainty checkGateSpatial uncertainty is recorded and affects downstream use. A high-uncertainty polygon may suit internal review, not public-safe release.
  4. 04 Publish

    1. 06Spatial metadata bundleRecordThe bundle records boundary type, jurisdiction, geometry version, projection, resolution, source, time window, uncertainty and access class.
    2. 07Public-safe release of the mapDecisionThe output record names the redactions, uncertainty and public-safe reviewer. A map is a governed spatial claim, never merely a picture.

Spatio-temporal intelligence · Data protocols: semantic, jurisdictional and temporal intelligence · NXS-EOPDesigned programme process, not a record of operation. No cycle has run and every programme is at service level R0. A gate is a programme decision, never a public-authority approval, certification or deployment authorisation. The pages cited are design doctrine.

13Questions

Questions and answers.

What are the limits of geospatial information systems in this field?
Errors in projection, scale and data currency propagate through analysis. Aggregation to administrative units can mask local variation.
How are results checked?
Positional and attribute accuracy are checked against surveyed control points and reference datasets. Topology rules and metadata standards ensure consistency.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
ReportsContribute

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Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

GCRIDisaster Resilience and RecoveryCountry Systems Risk and ResilienceEvidence Brief
Disaster Resilience and Recovery

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