GCRI · Science and methods
Spatial intelligenceObservations, models and their uncertainty in one view
Earth observation
Satellites, aircraft, drones and ground sensors observe floods, crops, forests, coasts, cities and infrastructure more often and more widely than ever. Earth observation is strong evidence when its sensors, processing and limits are understood, and misleading when they are not. The Global Centre for Risk and Innovation (GCRI) makes every map and change estimate checkable, with its uncertainty stated. Part of science and methods.
The working screen for earth observation.
Country programme console
Earth observation · Country programme A · Month 5 · Example interface, not a record
Programme
- Formationdossier
- National Deskstaffed
- National Modelbuild
- Portfoliooptions
- Annual missiontest
- Reportedition
System coupling
dependency strength, 0 to 100
Placeholder strengths a National Model replaces with estimates.
Evidence ledger
| Reservoir storage | OBSERVED | National Desk |
| Hydropower output | MODELLED | Technical office |
| Grid stress | SCENARIO | Technical office |
| Hospital continuity | ESTIMATED | Health ministry |
GCRI · Country programme consoleCountry programme console, in outline: domain structure with placeholder names and illustrative values, not a record.
Different instruments answer different questions.
No single sensor sees everything. Choosing the right instrument, or combining several, is the first decision in any Earth-observation study, and the choice is recorded with the result.
| Sensor type | Good for | Limits |
|---|---|---|
| Optical multispectral | Land cover, vegetation, water extent | Clouds and darkness block the view |
| Synthetic aperture radar | Flood mapping through cloud, ground movement | Harder to interpret, sensitive to terrain and surface |
| Thermal | Heat, fire, water temperature | Coarser resolution for many missions |
| Ground sensors | Calibration, continuous local measurement | Sparse coverage, maintenance needs |
Earth observation worldwide.
True-colour imagery and land cover 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 2
Earth observation, 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.
Earth observation, 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 · 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 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
- GHRSST Level 4 MUR analyses, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.DAAC); 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.
- 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).
- 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
- 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
- Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026
- Snow cover: VIIRS NOAA-20 NDSI, NASA LANCE · 13 Oct 2026
- Sea ice concentration: GHRSST MUR, NASA JPL PO.DAAC · 12 Oct 2026
The public missions most risk work draws on, and what each measures.
| Mission or system | What it measures | Notes on use |
|---|---|---|
| Copernicus Sentinel-1 (radar) | Surface backscatter through cloud; flood extent; ground deformation by interferometry | Sentinel-1C launched in December 2024, restoring two-satellite coverage |
| Copernicus Sentinel-2 (optical) | Land cover, vegetation condition, water extent at 10 to 60 metres | Clouds limit use in wet seasons and the tropics |
| Landsat 8 and 9 | Optical and thermal imagery with a record back to 1972 through earlier missions | Collection 2 processing makes the long record more consistent |
| SWOT (NASA and CNES, launched 2022) | Water surface elevation of rivers and lakes | Accuracy falls on narrow rivers; useful where gauges are missing |
| NISAR (NASA and ISRO, launched 2025) | L-band and S-band radar for deformation, biomass and soil moisture | New mission; products and validation still maturing |
| International Charter Space and Major Disasters | Rapid tasking of member agencies' satellites after a major disaster | Activated by authorised users; products carry the providers' terms |
Model earth observation as a system. Run the cascade.
Assembled from the Nexus Standards area profile Global and systemic risk: 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
- Dam failure
- Financial contagion
- River flood (set off downstream)
- Flash flood (set off downstream)
- Mass displacement (set off downstream)
- Widespread power outage (set off downstream)
- Water supply shortfall (set off downstream)
- Sovereign debt crisis (set off downstream)
- Currency crisis (set off downstream)
Systems and couplings
- Global and systemic risk
- Compound and cascading hazard standards Mechanism
- Financial stability and prudential risk Mechanism
- Supply chain and trade risk Cascade
- Future generations and long-term risk Common driver
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-H120Hazard family: Structural fragility of interconnected systems (NHS-1 sys.fragility)NRS-C6Systemic and cascading riskNRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-H62Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)NRS-H94Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)NRS-H60Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)
Observation
- INFORM Risk Index (listed for reference)
- World Bank Open Data and World Development Indicators API (listed for reference)
- IMF data services (WEO, IFS, FSI via SDMX) (listed for reference)
- Direct economic loss attributed to disasters in relation to global GDP
- Macroeconomic Dashboard
Example geography
- Bangladesh: 134 H3 hexagons at resolution 4
- 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
- Surface soil moisture (SMAP), NASA GIBS
How area and change estimates should be reported.
Olofsson and colleagues set out in 2014 the practice now standard for land change. Draw a probability sample of reference observations, build an error matrix, and estimate area from the reference data with a confidence interval. Do not count mapped pixels. Pixel counting is biased whenever omission and commission errors differ, which they usually do.
- Report user's and producer's accuracy per class with confidence intervals.
- Use analysis-ready data (CEOS ARD) or document every correction step.
- Treat a satellite change map as estimated evidence until it is checked on the ground.
Earth observation supports the Essential Climate Variables listed in the GCOS Implementation Plan of 2022, which sets out which variables are needed, at what accuracy and for how long.
Research use of public observation, with every product's terms kept.
GCRI operates no satellites and orders no acquisitions as an authority. It uses public missions and licensed data under their terms, develops and checks methods, and helps national agencies build processing capacity. Earth-observation evidence is designed for the Observatory Signal series and the Country Systems Risk and Resilience series, with each product described under NS-3b of the proposed Nexus Standards. Field teams can contribute reference observations, and agencies can share validation data under stated terms.
What makes satellite evidence trustworthy.
Two images of the same place are not automatically comparable. Quality checks come before any claim of change.
- 01
Comparable inputs
Images compared only when their sensor, processing level and processing version are comparable, and differences are corrected or stated.
- 02
Validation
Classifications and change estimates checked against independent reference data, with accuracy reported.
- 03
Seasonality and timing
Seasonal and acquisition-time differences are separated from real change.
- 04
Reproducibility
Inputs, code versions and parameters recorded so another team can repeat the result.
Systems, methods and platforms.
Earth-observation search, processing and change evidence run in EOP in Nexus Foundry. Methods are described at Earth observation and remote sensing, and spatial analysis under geospatial science. Field work is organized through the Space and Earth Observation platform, in development.
Describing a capability does not imply authority to order paid acquisition, and imagery keeps its provider's licence.
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.
- Copernicus Sentinel missions and services (European Union and ESA)
- Landsat Collection 2 (U.S. Geological Survey)
- NISAR, the NASA-ISRO synthetic aperture radar mission (NASA Jet Propulsion Laboratory)
- International Charter Space and Major Disasters
- Olofsson and others, Good practices for estimating area and assessing accuracy of land change, Remote Sensing of Environment 148 (2014)
- CEOS Analysis Ready Data for Land (Committee on Earth Observation Satellites)
- The 2022 GCOS Implementation Plan, GCOS-244 (Global Climate Observing System, 2022)
- NS-3b, Dataset and product metadata profile (STAC, DCAT, PROV-O), a proposed Nexus Standard
Questions and answers.
Can satellite images prove damage after a disaster?
Does GCRI operate satellites?
Why do two maps of the same flood differ?
Can I reuse GCRI's Earth observation products?
How does Earth observation support risk work?
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