Plain-language summary
- What it solves
- Etna's signals come from different sensors of varying quality that sometimes contradict each other.
- Who it can serve
- Anyone following the volcano, and anyone studying fusion of heterogeneous sensor data.
- What it produces
- An activity index with its uncertainty, sensor health status, and 1- and 5-day forecasts checked afterwards.
- Frequency
- Hourly nowcast · social Tue/Thu/Sat
- Status
- Active · experimental · quality-aware
- Output shown
- images from the post published on · open on Bluesky ↗
To bring very different Etna signals together without hiding quality, degradation or the difference between estimating activity and forecasting VONA notices.
3 · What it produces
Activity index with its uncertainty band, data and sensor health, 1- and 5-day VONA forecast, prospective verification and an adaptive model that only runs “in the shadows”.
The cards expose multiple views of the same workflow so result, method, evidence and history remain distinct.
4 · How it works
Bounded acquisition + data health + quality-aware fusion + prospective ledger
1FDSN/seismicity, FIRMS/thermal, cloud data, optional multi-station tremor and event history; freshness, completeness and quality per modality
2quality-adjusted fusion; Activity Index/band; 1h/6h escalation probabilities enabled only after sufficient reconciled evidence; VONA forecast reuses the validated Hawkes/modality gate
3immutable issue ledger, reconciliation sidecars, prospective calibration, hysteresis/cooldown and adaptive learner kept in shadow before gates
4Persistence, rendering and governed publishing.
5 · Data and signals
| Element | Detail |
|---|---|
| Data and signals | FDSN/seismicity, FIRMS/thermal, cloud data, optional multi-station tremor and event history; freshness, completeness and quality per modality |
| Industrial transferability | sensor fusion, condition monitoring, anomaly evidence and governed communication |
| Research | prospective calibration, modality ablation, drift and comparison with strong baselines |
| Interpretation condition | Activity Index, escalation and VONA ash-positive are distinct targets; no output replaces official sources |
quality-adjusted fusion; Activity Index/band; 1h/6h escalation probabilities enabled only after sufficient reconciled evidence; VONA forecast reuses the validated Hawkes/modality gate
immutable issue ledger, reconciliation sidecars, prospective calibration, hysteresis/cooldown and adaptive learner kept in shadow before gates
Python, pandas/NumPy, SciPy/scikit-learn, Matplotlib/Pillow, FDSN/HTTP, GitHub Actions, AT Protocol
mistaking activity nowcast for eruption prediction or VONA ash-positive; sensor degradation/absence and insufficient samples for escalation calibration
Workflow technical dossier
Methods, checks, stack and transferability conditions.
Data and signals
FDSN/seismicity, FIRMS/thermal, cloud data, optional multi-station tremor and event history; freshness, completeness and quality per modality
Inference / calculation
quality-adjusted fusion; Activity Index/band; 1h/6h escalation probabilities enabled only after sufficient reconciled evidence; VONA forecast reuses the validated Hawkes/modality gate
Validation
immutable issue ledger, reconciliation sidecars, prospective calibration, hysteresis/cooldown and adaptive learner kept in shadow before gates
Stack
Python, pandas/NumPy, SciPy/scikit-learn, Matplotlib/Pillow, FDSN/HTTP, GitHub Actions, AT Protocol
Limitations
mistaking activity nowcast for eruption prediction or VONA ash-positive; sensor degradation/absence and insufficient samples for escalation calibration
See recent outputs
The Publications page collects local previews and, on request, the public feed.
Related projects · Etna and the volcano
Other workflows on the same topic.
Potential transferability
Have a problem similar to Etna Fusion Lab?
A first discussion can start from the objective, available data and success criterion without sending confidential information. A result observed here is not assumed to transfer automatically to another context.