juliensimon/global-meteor-network

Global Meteor Network Trajectory Data

Credit: NASA/ESA

Part of a dataset collection on Hugging Face.

Dataset description

Individual meteor trajectory solutions from the Global Meteor Network (GMN), a worldwide network of 500+ all-sky cameras operated by volunteer astronomers. Each row is one detected meteor with orbital elements derived from multi-station triangulation.

The GMN was founded in 2018 and has grown to cover all longitudes from Europe, the Americas, Australia, and beyond. When at least two cameras simultaneously detect a meteor, the geometry of their positions allows triangulation of the atmospheric trajectory. Combined with timing, this yields the meteoroid's velocity at the top of the atmosphere and — after correction for Earth's gravitational attraction — the heliocentric orbit before encounter. The result is a complete set of Keplerian elements (a, e, i, ω, Ω, q) that places each detected meteoroid in the Solar System context.

Unlike the IAU Meteor Shower Database which catalogs mean radiant/orbit solutions per shower, this dataset contains individual meteor detections with full orbital parameters. The majority of detections are sporadic meteors (shower_code = '...') with no known parent body; shower members are identified by matching with the IAU shower list. The n_stations column provides a quality indicator: two-station solutions are the minimum for a valid trajectory, while higher counts improve the accuracy of both the radiant and the orbital elements.

This dataset is valuable for: identifying new meteor streams, studying the dynamical evolution of meteoroid trails, searching for meteoroids of potential interstellar origin (high eccentricity or retrograde orbits), correlating meteor detections with asteroid/comet close approaches, and building ML models for meteor source classification.

This dataset is suitable for tabular classification, tabular regression tasks.

Schema

Column	Type	Description	Sample	Null %
datetime_utc	datetime64[ns]	Peak brightness datetime in UTC (format: YYYY-MM-DD HH:MM:SS.ff); used as the primary deduplication key; typically accurate to ±0.1 s	2018-12-10 01:06:56.588151	0.0%
shower_code	str	IAU three-letter code for the meteor shower (e.g. 'PER' = Perseids, 'GEM' = Geminids); '...' = sporadic (not associated with any known stream)	...	0.0%
radiant_ra_deg	float64	Geocentric radiant right ascension J2000.0 (degrees, 0–360); the apparent sky point from which meteors of this stream diverge, corrected for Earth's orbital velocity	321.76912	0.0%
radiant_dec_deg	float64	Geocentric radiant declination J2000.0 (degrees, -90 to +90); together with ra defines the meteor's approach direction in inertial space	57.70221	0.0%
v_g_kms	float64	Geocentric velocity at the top of the atmosphere before deceleration (km/s); range ~11 km/s (Earth-grazing) to ~72 km/s (retrograde head-on); determines meteor brightness and persistent train likelihood	18.18262	0.0%
a_au	float64	Orbital semi-major axis of the meteoroid's heliocentric orbit (AU); NaN/inf for hyperbolic trajectories; Jupiter-family comets: 3-5 AU; Halley-type: 10-50 AU	7.95221	0.0%
e	float64	Orbital eccentricity (0 = circular, 1 = parabolic, >1 = hyperbolic); most shower meteoroids: 0.7–0.99; sporadic: wider range	0.876616	0.0%
i_deg	float64	Orbital inclination to the ecliptic plane (degrees, 0–180); <90° = prograde (same direction as planets); >90° = retrograde; Perseids: ~113°, Leonids: ~162°	23.695753	0.0%
peri_deg	float64	Argument of perihelion of the meteoroid orbit (degrees, 0–360); combined with node_deg locates the perihelion direction	187.272169	0.0%
node_deg	float64	Longitude of the ascending node (degrees, 0–360); for Earth-crossing orbits, approximately equals the solar longitude at the shower's peak activity	257.649026	0.0%
q_au	float64	Perihelion distance of the meteoroid's orbit (AU); must be ≤ ~1.01 AU for Earth-crossing; values close to 1.0 AU indicate recent parent-comet ejection	0.981174	0.0%
peak_abs_magnitude	float64	Absolute magnitude at peak brightness (normalized to 100 km range); lower values = brighter; scale: -4 (fireball) to +7 (faint); used for mass and flux estimation	0.05	0.0%
peak_height_km	float64	Altitude above sea level at peak brightness (km); typical range 80–110 km; slower meteors peak higher; depends on velocity and meteoroid composition	78.0939	0.0%
duration_sec	float64	Total duration of the visible meteor trail in seconds; from first detection to last; fast meteors: 0.1-0.5 s; fireballs: up to 5-10 s	1.29	0.0%
n_stations	Int64	Number of GMN cameras that simultaneously detected this meteor; ≥2 required for trajectory solution; higher values indicate better geometry and orbital accuracy	2	0.0%

Quick stats

• 3,081,915 meteor trajectories (2018-12-10 to 2026-05-13)
• 835,671 shower meteors (27%) and 2,246,244 sporadics (73%)
• Top 5 showers by count: PER (123,787), GEM (104,735), ORI (52,467), SDA (34,148), ETA (31,180)
• Median geocentric velocity: 41.2 km/s; fastest detected: 84.4 km/s

Usage

from datasets import load_dataset

ds = load_dataset("juliensimon/global-meteor-network", split="train")
df = ds.to_pandas()

from datasets import load_dataset
import pandas as pd

ds = load_dataset("juliensimon/global-meteor-network", split="train")
df = ds.to_pandas()

# Shower vs sporadic breakdown
print(df["shower_code"].value_counts().head(10))

# Velocity distribution by shower
import matplotlib.pyplot as plt
showers = df[df["shower_code"] != "..."]
top = showers["shower_code"].value_counts().head(6).index
showers[showers["shower_code"].isin(top)].boxplot(
    column="v_g_kms", by="shower_code", figsize=(10, 5)
)
plt.suptitle("")
plt.title("Geocentric Velocity Distribution by Meteor Shower")
plt.ylabel("v_g (km/s)")
plt.show()

# Radiant sky map
fig, ax = plt.subplots(figsize=(12, 6))
scatter = ax.scatter(
    df["radiant_ra_deg"], df["radiant_dec_deg"],
    c=df["v_g_kms"], s=0.5, cmap="plasma", alpha=0.3
)
plt.colorbar(scatter, label="v_g (km/s)")
ax.set_xlabel("RA (degrees)")
ax.set_ylabel("Dec (degrees)")
ax.set_title("GMN Meteor Radiants on the Sky")
plt.show()

Data source

https://globalmeteornetwork.org/data/

Update schedule

Daily at 10:00 UTC

Related datasets

• juliensimon/iau-meteor-showers

• juliensimon/fireball-bolide-events

• juliensimon/neo-close-approaches

• juliensimon/gaia-sso

• juliensimon/asterank

• juliensimon/lcdb

• juliensimon/bus-demeo

If you find this dataset useful, please consider giving it a like on Hugging Face. It helps others discover it.

About the author

Created by Julien Simon — AI Operating Partner at Fortino Capital. Part of the Space Datasets collection.

Citation

@dataset{global_meteor_network,
  title = {Global Meteor Network Trajectory Data},
  author = {juliensimon},
  year = {2026},
  url = {https://huggingface.co/datasets/juliensimon/global-meteor-network},
  publisher = {Hugging Face}
}

License

CC-BY-4.0