ASI Methodology

How the Artificial Snap Index (ASI) is Calculated Methodology & Data Sources (Updated April 2026)

Fading Sparks produces the ASI using only publicly available data from independent and official sources. No proprietary or classified information is used. All calculations are fully transparent and reproducible.

Data Sources & Weighting

To reduce bias from any single organization, we use a weighted blend:

  • 40% — Jonathan McDowell’s General Catalog of Artificial Space Objects (GCAT / planet4589.org) — the most detailed independent academic catalog.
  • 30% — NASA Orbital Debris Program Office + Space-Track.org — official U.S. military/public catalog.
  • 20% — ESA MASTER model and Space Environment Reports — European model-based estimates (especially useful for small-fragment populations).
  • 10% — Commercial corroboration (LeoLabs, Celestrak, KeepTrack.space) for rapid Starlink and megaconstellation counts.

All numbers are cross-checked against at least two sources before being finalized each month.

What Is Counted Each Month (End-of-Month Snapshot)

  • Tracked objects — All cataloged objects larger than 10 cm (the international standard for reliable tracking).
  • Active satellites — Confirmed operational payloads (maneuverable or not).
  • Megaconstellations — Starlink and others are broken out separately because they dominate density in crowded shells.
  • Small fragments (<10 cm) — Not directly tracked. We apply a separate “Fragment Field Risk Multiplier” based on ESA/NASA model estimates (≈1.2 million objects 1–10 cm and tens of millions <1 cm). This adds a realistic risk factor without inflating the raw tracked count.
  • Major events — Any breakup, collision, or large launch batch is noted and factored into the monthly change.

The ASI Formula

ASI = Wt × (1 + It) × SPF

  • Wt (Base Burden) — Weighted combination of mass burden, concentration, large-object severity, fragment field, and operational state.
  • It (Synergy Penalty) — Interaction effects between key factors: concentration × persistence, large-object severity × crowding, fragment fields × active traffic, velocity severity × mass, and unmanaged state × concentration.
  • SPF (Snap Proximity Factor) — The non-linear growth engine that creates acceleration near tipping points: SPF = 1 + 1.0 × (D_norm / (1 – D_norm))² where D_norm is the normalized density in busy LEO shells (0 = empty, 1 = critical Snap Point threshold).

This non-linear SPF term is what allows the ASI to show clear progression: it grows slowly at first, then accelerates sharply as we approach a dangerous Snap Point.

Monthly Update Process & Charting

  1. Collect end-of-month data from the weighted sources.
  2. Calculate Wt and It using the defined variables and synergy families.
  3. Compute D_norm for the most crowded LEO shells.
  4. Apply the SPF to produce the final ASI value.
  5. Archive the result permanently and publish the monthly report.

Charting Starting with 2026 data, we will produce monthly trending charts (created from Excel exports of the archived data). These charts will visually display the ASI progression, density changes, and synergy pressure over time, making the risk trend easy to see at a glance. Historical charts will be added as the archive grows.

All raw data, intermediate calculations, and source links are available upon request via the Contact page.

This method is fully transparent, independent, and designed for long-term public accountability. We do not rely on any government or corporate press releases for the final ASI numbers.

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