GCRI · Science and methods
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.
01Workspace
The workspace for earth observation.
GCRI · GCRI · Country programme consoleIllustrative
Country programme console
Earth observation · Country programme A · Month 5 · Example interface, not a record
National Model in buildGCRI · GCRI
Programme
- Formationdossier
- National Deskstaffed
- National Modelbuild
- Portfoliooptions
- Annual missiontest
- Reportedition
System coupling
dependency strength, 0 to 100
Example 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 console. Country programme console: example names and illustrative values, not a record.
02Sensors
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 |
03Geography
Earth observation worldwide.
Land cover and vegetation 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
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
- 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
- MODIS Terra NDVI (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 greenness index over the 8 days to the date shown; an indicator of crop and pasture condition, not a yield estimate or a food security warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds and night leave gaps)
- Source
- VIIRS NOAA-20 NDSI (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds and night leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 500 m grid
- Uncertainty
- Satellite detection; clouds and night 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
- Source
- GHRSST MUR (NASA JPL PO.DAAC)
- Provider
- NASA JPL PO.DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite analysis
- Newest at build
- 2026-10-12
- Resolution
- about 1 km grid
- Uncertainty
- Satellite analysis. 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
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 the world.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 · 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
- 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
- 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 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.
- 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
- 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
04Observing systems in 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 |
05Accuracy and area
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.
06GCRI’s part
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.
07Quality
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.
08Where it runs
Systems, methods and platforms.
Earth-observation search, processing and change evidence run in NXS-EOP (earth observation and digital twins). Methods are described at Earth observation and remote sensing, and spatial analysis under geospatial science. Field work is organised through the Space and Earth Observation platform.
Describing a capability does not imply authority to order paid acquisition, and imagery keeps its provider’s licence.
09Sources
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 standard
10Questions
Questions and answers.
Can satellite images prove damage after a disaster?
They provide evidence of visible change, with stated accuracy. Damage assessment usually needs ground validation, and GCRI labels satellite-derived estimates as estimates.
Does GCRI operate satellites?
No. GCRI uses data from public and licensed sources, under their terms, and records the source and licence of every product.
Why do two maps of the same flood differ?
Different sensors, acquisition times, processing choices and thresholds produce different results. GCRI reports these choices so results can be compared.
Can I reuse GCRI’s Earth observation products?
Under the licence stated with each product. Underlying imagery keeps its provider’s terms, which may restrict redistribution.
How does Earth observation support risk work?
It maps exposure, tracks change in forests, water and settlements, observes hazards as they unfold and helps validate models. It is most useful combined with ground data and local knowledge.
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