usgs-earthquake-geojson

name	usgs-earthquake-geojson
description	Parse and work with USGS earthquake GeoJSON data, extracting IDs, magnitudes, coordinates, times, and place descriptions.

USGS Earthquake GeoJSON Parsing

Data Structure

USGS earthquake GeoJSON follows the standard FeatureCollection format:

{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": {
        "mag": 5.1,
        "place": "13 km NW of Port-Vila, Vanuatu",
        "time": 1735537742808,   // Unix timestamp in milliseconds
        "mag": 5.1,
        "magType": "mww"
      },
      "geometry": {
        "type": "Point",
        "coordinates": [168.2183, -17.6555, 66.612]  // [lon, lat, depth_km]
      },
      "id": "us6000pgf9"
    }
  ]
}

Loading into GeoDataFrame

import geopandas as gpd
import json
from datetime import datetime, timezone

with open("earthquakes_2024.json") as f:
    eq_data = json.load(f)

records = []
for feat in eq_data["features"]:
    props = feat["properties"]
    coords = feat["geometry"]["coordinates"]
    time_ms = props["time"]
    time_iso = datetime.fromtimestamp(time_ms / 1000, tz=timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
    records.append({
        "id": feat["id"],
        "place": props["place"],
        "time": time_iso,
        "magnitude": props["mag"],
        "longitude": coords[0],
        "latitude": coords[1],
    })

gdf = gpd.GeoDataFrame(
    records,
    geometry=gpd.points_from_xy([r["longitude"] for r in records], [r["latitude"] for r in records]),
    crs="EPSG:4326"
)

Key Notes

• time field is Unix timestamp in milliseconds (divide by 1000 for seconds)
• geometry.coordinates is [longitude, latitude, depth_km] — NOT [lat, lon]
• Use datetime.fromtimestamp(ms/1000, tz=timezone.utc) for ISO 8601 UTC formatting