The algorithm uses object detection in Pléiades display imagery to detect and classify multiple types of aircraft. The result is a GeoJSON file with vertically oriented polygons drawn around detected aircraft.
This process detects and classifies multiple types of aircraft:
- Carrier aircraft
- Fighter aircraft
- Helicopters
- Small aircraft
- Other
Aircraft detection can be used for aircraft management, airport monitoring, and environmental modeling.
See more on the marketplace.
The algorithm has been developed using 2,500 satellite images across 350 air bases in 50 countries spanning 6 continents. The algorithm counted 54,000 aircraft to create a historical baseline of activity and detect ongoing changes.
For optimal results, the algorithm should be applied to imagery captured over airport areas. You can apply it to similar areas, but the same level of performance isn’t guaranteed.
Scenarios represented in the training data:
- Different times of day
- Different times of year
- Different terrains
- Different object configurations
The STAC item should be a Pléiades image of the display radiometric processing level.
The STAC item should be CNAM-compatible. Check that the STAC item has been added to storage in 2023 or later.
Required parameters
Input imagery
You need to specify the STAC items you want to apply the process to.
Output title
You need to specify the title of the output objects. This title will be assigned to the resulting STAC item and STAC collection.
A sample input payload for the process
JSON
{
"inputs":{
"title": "Aircraft detection over Dubai airport",
"item": "https://api.up42.com/v2/assets/stac/collections/21c0b14e-3434-4675-98d1-f225507ded99/items/23e4567-e89b-12d3-a456-426614174000"
}
}
| Parameter | Overview |
|---|---|
inputs.title | object / required The title of the output objects: STAC item and STAC collection. |
inputs.item | object / required The STAC item link in the following format: https://api.up42.com/v2/assets/stac/collections/{collection-id}/items/{item-id} |