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Science-Grade Earth
Observation Data

The measurement foundation for reliable Earth intelligence.

Most satellite imagery is built for visual interpretation, not measurement. Science-grade Earth observation data is calibrated, validated, and consistent over time, the properties that let measurements be trusted in decisions that carry real consequence.

  • What science-grade data actually is, and how it is built

  • Why measurement consistency is the foundation of reliable change detection

  • Why governments depend on data that stays comparable over time

  • 34 pages, fully referenced, World Economic Forum, NASA, USGS, CEOS, Swiss Re

 

What the paper covers

The paper covers science-grade data from definition through to the workflows that depend on it. No remote-sensing background is assumed.

What science-grade data actually means

Calibration, validation, geometric consistency and spectral depth the technical status that separates measurement from imagery.

How the EarthDaily Constellation delivers it

22 spectral bands, 5 m resolution, daily global coverage, and cross-calibration against established science missions.

Why it is the foundation of change detection

When the baseline keeps shifting, change becomes noise. Consistent measurement is what makes change reliable.

Why governments depend on consistency

Public reporting, audits and policy rely on data that stays comparable long after the observation was made.

What spatial quality really means

Detail that comes from the sensor is unsharpened, directly measured, not introduced by processing.

The road ahead: foundation models

Daily, global, science-grade observations across visible, infrared and thermal bands. The data that geospatial AI needs.

Key figures from the paper

$700B

the total economic opportunity in Earth observation by 2030.

World Economic Forum & Deloitte

$263B

in annual EO value that remains unrealized.

World Economic Forum & Deloitte

80%

of analyst time spent preparing data rather than analyzing it.

Industry research

$117B

in annual value unrealized due to processing constraints.

World Economic Forum & Deloitte

Stack of satellite images of the same site over time, showing consistent measurement across passes

Worked examples

EDC 5 m satellite image of a coastline with a sand spit, harbour and industrial shoreline

“Change detection is only as good as the consistency behind it. A record that holds its shape across time is what makes comparison reliable.”

Reliable change detection depends on measurements that line up cleanly from one pass to the next all calibrated, consistent, and spatially reliable.

Chapters 3 and 5 carry worked examples:
EDC 5 m imagery compared against Sentinel-2 and high-resolution reference imagery.

Fine electrical-grid structure preserved within a true 5 m product, and field boundaries that hold up for change detection over time.

Cover of the EarthDaily white paper: Science-grade Earth observation data

Free download

Download the white paper

34 pages, fully referenced and free to download. Covers what science-grade data is, how it is built, and why measurement consistency matters for the workflows that depend on it.