Skip to content

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.

Country programme console

Earth observation · Country programme A · Month 5 · Example interface, not a record

National Model in buildGCRI · GCRI

Programme

  1. Formationdossier
  2. National Deskstaffed
  3. National Modelbuild
  4. Portfoliooptions
  5. Annual missiontest
  6. Reportedition

System coupling

dependency strength, 0 to 100

Example strengths a National Model replaces with estimates.

Evidence ledger

Reservoir storageOBSERVEDNational Desk
Hydropower outputMODELLEDTechnical office
Grid stressSCENARIOTechnical office
Hospital continuityESTIMATEDHealth ministry
Country programme console.Illustrative interface; not live data.

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 typeGood forLimits
Optical multispectralLand cover, vegetation, water extentClouds and darkness block the view
Synthetic aperture radarFlood mapping through cloud, ground movementHarder to interpret, sensitive to terrain and surface
ThermalHeat, fire, water temperatureCoarser resolution for many missions
Ground sensorsCalibration, continuous local measurementSparse 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

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 systemWhat it measuresNotes on use
Copernicus Sentinel-1 (radar)Surface backscatter through cloud; flood extent; ground deformation by interferometrySentinel-1C launched in December 2024, restoring two-satellite coverage
Copernicus Sentinel-2 (optical)Land cover, vegetation condition, water extent at 10 to 60 metresClouds limit use in wet seasons and the tropics
Landsat 8 and 9Optical and thermal imagery with a record back to 1972 through earlier missionsCollection 2 processing makes the long record more consistent
SWOT (NASA and CNES, launched 2022)Water surface elevation of rivers and lakesAccuracy 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 moistureNew mission; products and validation still maturing
International Charter Space and Major DisastersRapid tasking of member agencies’ satellites after a major disasterActivated 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.

  1. 01

    Comparable inputs

    Images compared only when their sensor, processing level and processing version are comparable, and differences are corrected or stated.

  2. 02

    Validation

    Classifications and change estimates checked against independent reference data, with accuracy reported.

  3. 03

    Seasonality and timing

    Seasonal and acquisition-time differences are separated from real change.

  4. 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.

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.
ReportsContribute

Contribute evidence from this page.

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.

GCRI
The Global Centre for Risk and Innovation

Bring a method, a dataset or a question.

Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.