Line sections
Infrabel: belgium's rail network manager
- Format
- GeoJSON
- Updates
- Daily
- Latest snapshot
- Snapshots stored
- about 707
curl -H "Authorization: Bearer $MOBILITYTWIN_TOKEN" "https://api.mobilitytwin.brussels/infrabel/line-sections"The rail network split into line sections, with each section's route and technical characteristics. Join it with operational-points, which locates the start and end point of each section.
Meant for schematic maps, up to a scale of 1:25,000. Source: Infrabel open data.
Which days have data
Data from 21 Aug 2024 to 2 Nov 2026, on 748 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
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 |
|---|---|
etat | string |
geo_point_2d | |
geo_shape | null |
id | string |
linecalfa | string |
linecnum | integer or null |
modifdate | string |
trackcode | string |
trackname | 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/line-sections"
data = requests.get(url, headers={
'Authorization': 'Bearer [MY_API_KEY]'
}, params=params).json()
gdf = gpd.GeoDataFrame.from_features(data["features"], crs=4326)
# Plot the Belgian rail network
gdf.plot(figsize=(12, 10), linewidth=0.5, color="darkblue")
# Compute total network length
gdf['length_km'] = gdf.to_crs(31370).geometry.length / 1000 # metres need a projected CRS (Belgian Lambert 72)
print(f"Total rail network: {gdf['length_km'].sum():.0f} km")