Skip to main content

Conceptual Framework

Cyclic Application Value Chain​

The cyclic value chain describes how EO data creates value for society and how societal needs in turn guide EO development:

  • EO data → Information → Knowledge → Policy/Decision — raw observations are processed into information products that inform decision-making.
  • Societal needs → Requirements → Missions → Data — policy objectives and societal challenges drive the specification of new EO missions and data products.
  • This cyclical relationship ensures EO remains relevant to real-world challenges such as climate change, food security, and disaster management.

[Figure in progress]

Linear Data Enhancement Value Chain​

The linear value chain describes how successive processing steps add value to EO data:

  • Level 0 — Raw instrument data (digital counts from sensor)
  • Level 1 — Calibrated physical quantities (e.g., top-of-atmosphere radiance)
  • Level 2 — Geophysical variables (e.g., surface reflectance, temperature)
  • Level 3/4 — Derived products, composites, model outputs, and analysis-ready data

Each step increases the accessibility and interpretability of the data, transforming raw observations into actionable information.

[Figure in progress]