Operational points

Infrabel: belgium's rail network manager

Format: GeoJSON
Updates: Daily
Latest snapshot: 2 Nov 2026, 01:22 UTC
Snapshots stored: about 707

curl -H "Authorization: Bearer $MOBILITYTWIN_TOKEN" "https://api.mobilitytwin.brussels/infrabel/operational-points"

Get a token

The operational points of the Belgian rail network: the start and end points of the line-sections.

Which days have data

Data from 21 Aug 2024 to 2 Nov 2026, on 747 days. 30 of the last 30 days have data. A typical day holds 1 snapshot. Days are in UTC.

2026

JanFebMarAprMayJunJulAugSepOctNovDec

2025

JanFebMarAprMayJunJulAugSepOctNovDec

2024

JanFebMarAprMayJunJulAugSepOctNovDec

Full day
Partial, 50–90% of a typical day
Low, under 50%
No snapshot
Not expected

Get a day

Click a day above, or pick a date, to get its requests.

Parameters

Name	Meaning
`timestamp`	Return the last snapshot at or before this moment, in Unix seconds or ISO 8601 (e.g. `2026-05-06T12:00:00Z`). Without it, the latest snapshot is returned.

Response fields

A GeoJSON FeatureCollection. Field names without a prefix are in each feature's properties.

Field	Type
`class_fr`	string
`commerciallongnamedutch`	string
`commerciallongnamefrench`	string
`commercialmiddlenamedutch`	string
`commercialmiddlenamefrench`	string
`commercialshortnamedutch`	string
`commercialshortnamefrench`	string
`geo_point_2d.lat`	number
`geo_point_2d.lon`	number
`longnamedutch`	string
`longnamefrench`	string
`ptcarid`	string
`shortnamedutch`	string
`shortnamefrench`	string
`symbolicname`	string
`taftapcode`	string

Python example

import requests
import geopandas as gpd

from datetime import datetime, timedelta, timezone

yesterday_noon = (datetime.now(timezone.utc) - timedelta(days=1)).replace(
    hour=12, minute=0, second=0, microsecond=0
)
params = {
    "timestamp": yesterday_noon.isoformat(),   # ISO accepted; epoch also works
}

url = "https://api.mobilitytwin.brussels/infrabel/operational-points"

data = requests.get(url, headers={
        'Authorization': 'Bearer [MY_API_KEY]'
}, params=params).json()

gdf = gpd.GeoDataFrame.from_features(data["features"])

# Filter only stations (class_fr "Gare")
stations = gdf[gdf['class_fr'] == 'Gare']
print(f"Total stations: {len(stations)}")
for _, s in stations.head(10).iterrows():
    print(f"  {s['commerciallongnamefrench']} ({s['symbolicname']})")

# Plot all operational points
gdf.plot(figsize=(10, 8), markersize=5, color="navy")