Unified position

Airplane: aircraft from the opensky and adsb.lol networks

Format: GeoJSON
Updates: Every 5 minutes
Latest snapshot: 2 Nov 2026, 22:43 UTC
Snapshots stored: about 42,097

curl -H "Authorization: Bearer $MOBILITYTWIN_TOKEN" "https://api.mobilitytwin.brussels/airplane/unified-position"

Get a token

Unified real-time positions of aircraft, merging the OpenSky Network feed and adsb.lol. Aircraft are deduplicated by icao24 (with a callsign fallback). When both feeds see the same plane, the adsb.lol position is preferred (more recent) but OpenSky-only attributes such as origin_country are kept. Each feature includes a sources array listing which feeds reported it ("opensky", "adsb.lol", or both). adsb.lol data is available under the Open Database License (ODbL).

Which days have data

Data from 7 May 2026 to 2 Nov 2026, on 175 days. 30 of the last 30 days have data. A typical day holds 264 snapshots. Days are in UTC.

2026

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
`icao24`	string
`callsign`	string
`origin_country`	string or null
`time_position`	number or null
`last_contact`	number
`baro_altitude`	number or null
`on_ground`	boolean
`velocity`	number or null
`true_track`	number or null
`vertical_rate`	number or null
`sensors`	null
`geo_altitude`	number or null
`squawk`	string or null
`spi`	boolean
`position_source`	string
`category`	string or null
`registration`	string or null
`aircraft_type`	string or null
`source_feed`	string
`sources`	array

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/airplane/unified-position"

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

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

# Each feature carries a `sources` array indicating which feeds saw the plane.
both = gdf[gdf["sources"].apply(lambda s: len(s) > 1)]
only_adsb_lol = gdf[gdf["sources"].apply(lambda s: s == ["adsb.lol"])]
only_opensky = gdf[gdf["sources"].apply(lambda s: s == ["opensky"])]

print(f"total:          {len(gdf)} aircraft")
print(f"both feeds:     {len(both)}")
print(f"adsb.lol:       {len(only_adsb_lol)} (only)")
print(f"opensky:        {len(only_opensky)} (only)")

# Filter to airborne planes inside a Belgium bounding box.
import shapely.geometry as sg
belgium = sg.box(2.5, 49.4, 6.55, 51.55)
in_belgium = gdf[gdf.geometry.within(belgium) & (~gdf["on_ground"].fillna(False))]
print(f"airborne over Belgium: {len(in_belgium)}")

# Plot, coloured by feed coverage.
def feed_color(sources):
    if "adsb.lol" in sources and "opensky" in sources:
        return "#9b59b6"
    if "adsb.lol" in sources:
        return "#27ae60"
    return "#e67e22"

gdf.plot(figsize=(10, 8), color=gdf["sources"].map(feed_color), markersize=12)