Space-weather-aware pass quality scorer for ground station operators — looking for feedback

Hi SatNOGS community,
I’m Nilabh, an MSc Physics graduate from India. I built OrbitGuard — a tool that scores upcoming satellite pass windows from 0–100 by combining orbital geometry with real-time space weather data.
The motivation: SatNOGS schedules observations based on pass geometry, but a high-elevation pass during a geomagnetic storm can still be a poor observation due to ionospheric scintillation and signal degradation. OrbitGuard adds a space-weather layer on top of the geometry.
Scoring uses:
Elevation angle and pass duration
Real-time Kp index from NOAA SWPC
Solar flux F10.7
Ionospheric TEC
Works for any LEO satellite via NORAD ID, including ones tracked by SatNOGS stations.
Live demo: https://orbitguard-1.onrender.com

API docs: OrbitGuard API - Swagger UI
I’d genuinely value feedback from people who actually operate ground stations — especially whether the scoring weights make sense operationally, and whether something like this would be useful alongside SatNOGS scheduling.

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Hi @nilabh and welcome!

Is this software open-source?

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image

meh

Hi. Yes — the full source is on GitHub: GitHub - nilabh-astrophysics/orbitguard · GitHub

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try test it, set the location, etc. and then comparing with gpredict. the result is different, time, max elevation, duration etc. im wondering is your TLE up to date?

73!

73! Thanks for actually testing it — this is exactly the feedback I needed.

The TLE source is Space-Track.org, fetched fresh and cached for 6 hours. However, if Space-Track is unreachable (which can happen on the free hosting tier I’m using), it falls back to hardcoded TLEs from May 2025 — which would definitely explain timing differences. That’s a real bug and I’ll fix the fallback behaviour.

A few other things that could cause differences vs Gpredict: — Minimum elevation cutoff (I default to 10°, Gpredict may use a different value) — Atmospheric refraction modelling (Skyfield includes refraction, not sure how Gpredict handles it)

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