Airplane

View API Documentation

Airplane tracking data over Belgium and the surrounding airspace. The platform combines two complementary feeds: OpenSky Network, a community-based ADS-B receiver network, and airplanes.live, a second community feed that typically reports 30–40% more aircraft. The unified-position endpoint fuses both feeds, deduplicating by ICAO24 hex code so each aircraft appears once with the most complete set of attributes available. Updated every minute. The data is provided in the GeoJSON format.

Source

Endpoints

Opensky position

/airplane/opensky-position

GEOJSON APPLICATION/JSON

Real-time positions of aircraft over Belgium as reported by the OpenSky Network.

Refresh: Every 5 minutes

From

2026-02-25 16:01:32

2026-05-20 06:07:46

Records

20,890

Airplanes live position

/airplane/airplanes-live-position

GEOJSON APPLICATION/JSON

Real-time positions of aircraft over Belgium and a 150 nm surrounding radius, as reported by the airplanes.live community ADS-B feed. Coverage is generally denser than OpenSky's free tier (about 30–40% more aircraft observed at peak). Output schema mirrors the OpenSky endpoint so the two feeds are interchangeable; additional fields include registration, aircraft_type and source_feed.

Refresh: Every minute

From

2026-05-07 12:05:08

2026-05-20 06:08:54

Records

17,827

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/airplanes-live-position"

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

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

# airplanes.live typically returns more aircraft than OpenSky (denser coverage).
# Schema mirrors opensky-position so the two feeds can be swapped freely.
print(f"{len(gdf)} aircraft tracked right now")

# Show the lowest/loudest movers — useful for noise impact analysis.
moving = gdf[(gdf["velocity"].fillna(0) > 5) & (~gdf["on_ground"].fillna(False))]
lowest = moving.nsmallest(10, "baro_altitude")[
    ["callsign", "registration", "aircraft_type", "baro_altitude", "velocity"]
]
print(lowest)

# Plot
gdf.plot(figsize=(10, 8), color="#27ae60", markersize=10)

Unified position

/airplane/unified-position

GEOJSON APPLICATION/JSON

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

Refresh: Every minute

From

2026-05-07 12:09:09

2026-05-20 06:07:46

Records

3,277

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_live = gdf[gdf["sources"].apply(lambda s: s == ["airplanes.live"])]
only_opensky = gdf[gdf["sources"].apply(lambda s: s == ["opensky"])]

print(f"total:          {len(gdf)} aircraft")
print(f"both feeds:     {len(both)}")
print(f"airplanes.live: {len(only_live)} (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 "airplanes.live" in sources and "opensky" in sources:
        return "#9b59b6"
    if "airplanes.live" in sources:
        return "#27ae60"
    return "#e67e22"

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