The Global Centre for Risk and Innovation (GCRI)
Earth observation sensors measure reflected sunlight, emitted heat, radar echoes and laser returns from orbit. Each sensor type sees some things well and others not at all: optical sensors are blocked by cloud, radar sees through it, thermal sensors measure heat. This page sets out how the main sensor types work, how their resolution and revisit shape what they can detect, and what evidence serves the users choosing data for a task.
GCRI · In development · service level R0
Earth observation sensors are satellite and airborne instruments that measure reflected light, emitted heat, radar echoes or laser returns from the Earth. Optical sensors need clear skies, radar sees through cloud, and every sensor trades spatial, spectral and temporal resolution against coverage.
For earth observation sensors, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery and land cover, framed on the Arctic; every other NASA layer, live feed and forecast waits in the layer list.
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Layers 2
Earth observation, for this page
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NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
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For earth observation sensors, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery and land cover, framed on the Arctic; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.
Layers and dates
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
Earth observation sensors · Flood basin AOI · Activation ACT-815
next 7 passes
| P-1 | Radar | n/a | Processed |
| P-2 | Optical | 84 | Cloudy |
| P-3 | Radar | n/a | Downlinking |
| P-4 | Optical | 30 | Scheduled |
Optical, radar, thermal and hyperspectral methods. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Multispectral and hyperspectral sensors measure reflected sunlight in many bands, revealing vegetation, water and materials. Cloud and darkness block them.
Synthetic aperture radar sends its own microwave pulses and records echoes, day or night and through cloud, sensing surface roughness, moisture and movement.
Spatial, spectral and temporal resolution compete. Very high resolution images cover small areas; wide-swath sensors revisit often but see less detail.
Sun-synchronous orbits give consistent lighting; constellations of many small satellites shorten revisit times but vary in calibration.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Multispectral sensor | A sensor that records reflected light in several distinct wavelength bands. |
| Synthetic aperture radar | An active radar that forms high-resolution images using the satellite's motion. |
| Revisit time | How often a sensor or constellation can observe the same place. |
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.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Spatial resolution | metres per pixel | per sensor | Mission specifications | DECLARED |
| Revisit interval | days | per mission or constellation | Mission specifications | DECLARED |
| Cloud-free observation frequency | observations per month | per location | Archive analysis | OBSERVED |
| Radiometric calibration uncertainty | percent | per sensor | Calibration reports | REPORTED |
| Spectral bands | count | per sensor | Mission specifications | DECLARED |
| Data latency | hours from acquisition to availability | per product | Data provider records | OBSERVED |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| Copernicus Sentinel missions (ESA and European Commission) | Radar, optical, ocean and atmospheric data | Free and open, Copernicus terms |
| Landsat archive (USGS and NASA) | Optical and thermal imagery since the 1970s | Public domain, US government data |
| CEOS Missions, Instruments and Measurements database | Characteristics of Earth observation missions | Public, CEOS terms |
| WMO OSCAR database | Observing system capabilities and requirements | Public, WMO terms |
| NASA Earthdata | MODIS, VIIRS, GEDI and other mission data | Open, NASA data policy |
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 decides | The question | Evidence this page serves |
|---|---|---|
| Agencies and analysts using EO | Which sensors and products suit a task | Sensor selection guides; coverage analyses |
| Space agencies | Which missions and instruments to fund next | Gap and continuity evidence |
| Procurement bodies | When commercial data add value over free data | Resolution and revisit comparisons |
Remote-sensing scientists approach any application with a set of sensor questions.
Optical sensors record reflected sunlight in visible and infrared bands, revealing vegetation, water, soils and built surfaces. They need daylight and clear skies. Thermal sensors record emitted heat, useful for surface temperature, fires and urban heat. Synthetic aperture radar sends its own microwave pulses and measures the return, so it works day and night and through cloud; it is sensitive to surface roughness, structure and moisture, and interferometric techniques can measure ground movement of very small magnitude.
Hyperspectral sensors record many narrow bands, allowing identification of minerals, plant stress and water quality, at the cost of large data volumes and often coarser coverage. Every sensor involves trade-offs between spatial detail, revisit frequency, spectral range and swath width. No single sensor answers every question.
Converting raw signals to physical units using onboard references and ground sites, grounded in physics. Calibration drifts over a mission's life.
Removing atmospheric effects to estimate surface properties. Errors are largest over water, in haze and in mountainous terrain.
Speckle filtering, terrain correction and interferometry, within Earth observation. Interpretation of radar signals needs specialist expertise.
Combining data from multiple sensors. Mismatched timing and resolution can introduce artefacts.
The current service level is R0: information and enquiries. 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.