Poseidon / README.md
BorisKriuk's picture
Add link to paper and task metadata (#2)
1e8f4ad
metadata
license: cc-by-4.0
task_categories:
  - time-series-forecasting
language:
  - en
pretty_name: Poseidon
size_categories:
  - 1M<n<10M
tags:
  - geophysics
  - earthquake-prediction

Poseidon: Global Earthquake Dataset (1990-2020)

This is the official dataset for the paper POSEIDON: Physics-Optimized Seismic Energy Inference and Detection Operating Network.

Overview

Poseidon is a largest opensource global earthquake dataset containing 2.8+ million seismic events spanning 30 years (1990-2020). Named after the Greek god of earthquakes, this dataset is designed for machine learning applications including earthquake prediction, seismic hazard analysis, spatiotemporal pattern recognition, and energy-based modeling.

Dataset Statistics

Metric Value
Total Events 2,833,766
Time Span 1990-01-01 to 2024-12-31
Magnitude Range 0.0 - 9.1
Geographic Coverage Global (-90 to 90 lat, -180 to 180 lon)
Spatial Resolution 180 x 360 grid bins (1 degree resolution)

Features

Core Seismic Properties

Column Type Description
id string Unique USGS event identifier
time string ISO 8601 timestamp (UTC)
latitude float64 Event latitude (-90 to 90)
longitude float64 Event longitude (-180 to 180)
depth float64 Hypocenter depth in kilometers
magnitude float64 Event magnitude
mag_type string Magnitude type (ml, mb, mw, md, etc.)

Event Metadata

Column Type Description
place string Human-readable location description
type string Event type (earthquake, quarry blast, etc.)
status string Review status (reviewed, automatic)
tsunami int64 Tsunami flag (1 = tsunami generated, 0 = none)
sig int64 Significance score (0-1000+)
net string Contributing seismic network code

Quality Metrics

Column Type Description
nst float64 Number of stations used
dmin float64 Minimum distance to nearest station (degrees)
rms float64 Root mean square travel time residual
gap float64 Azimuthal gap (degrees)
horizontal_error float64 Horizontal location uncertainty (km)
depth_error float64 Depth uncertainty (km)
mag_error float64 Magnitude uncertainty
mag_nst float64 Number of stations for magnitude calculation

Temporal Features (Pre-computed)

Column Type Description
year int64 Event year
month int64 Event month (1-12)
day int64 Event day (1-31)
hour int64 Event hour (0-23 UTC)
minute int64 Event minute (0-59)
second int64 Event second (0-59)

Spatial Grid Features (Pre-computed)

Column Type Description
lat_bin int64 Latitude bin index (0-179) for heatmap generation
lon_bin int64 Longitude bin index (0-359) for heatmap generation

Energy Features (Pre-computed)

Column Type Description
energy_joules float64 Seismic energy release in Joules
log_energy float64 Log10 of energy (for numerical stability)

Energy Calculation

Seismic energy is computed using the Gutenberg-Richter energy-magnitude relation:

log10(E) = 1.5 x M + 4.8

Where E = Energy in Joules and M = Earthquake magnitude.

Example values:

Magnitude Energy (Joules) Equivalent
2.0 6.3 x 10^7 Small explosion
4.0 6.3 x 10^10 15 tons TNT
6.0 6.3 x 10^13 15 kilotons TNT
8.0 6.3 x 10^16 15 megatons TNT
9.0 2.0 x 10^18 475 megatons TNT

Usage

import pandas as pd
df = pd.read_csv("poseidon.csv")
df['datetime'] = pd.to_datetime(df['time'])

Example: Filter Significant Events

major_quakes = df[df['magnitude'] >= 6.0]
print(f"Major earthquakes (M6+): {len(major_quakes):,}")

tsunami_events = df[df['tsunami'] == 1]
print(f"Tsunami-generating events: {len(tsunami_events):,}")

Applications

This dataset is designed for:

  • Earthquake Prediction Models
  • Aftershock Sequence Analysis
  • Magnitude-Frequency Analysis
  • Tsunami Early Warning
  • Energy-Based Models (EBMs)
  • CNN/RNN Training
  • Seismic Hazard Mapping

License

This dataset is released under CC BY 4.0.

Acknowledgments

  • USGS Earthquake Hazards Program for providing the source data
  • Gutenberg and Richter for the foundational energy-magnitude relation