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Aircraft detection
Description
An algorithm that detects and classifies multiple aircraft types (e.g., carrier, fighter, helicopter, small aircraft, and others) in Pléiades imagery using wide-area object detection. Uses cases include aircraft management, airport monitoring, and environmental modelling.
Technical information
| Source | Pléiades tasking or catalog collections |
| Compatibility | - The STAC item should be a Pléiades image of the display radiometric processing level - The STAC item should have been added to storage in 2023 or later |
| Required parameters | - Console: If your chosen input data meets the above specifications you will be able to run your job - API: You will need to input an Output title and the Input data |
| Output data format | GeoJSON file: with vertically oriented polygons drawn around detected aircraft |
| Output | The result will be added to your account as a STAC item in a new STAC collection. You can retrieve the resulting data in one of the following ways: - Open the console, go to Data management → Jobs - Retrieve the results via the API |
Algorithm performance and training data
The algorithm has been qualified on a large set of data encompassing different types of landscapes worldwide by a third party, with a high level of performances. The algorithm should be applied on airport areas. The algorithm was trained in over 50 countries spanning 6 continents. The training set spans many different conditions, for instance: different times of day, different terrains, different times of year, different configurations and types of planes, etc. Thus, the algorithm is location and direction invariant.
The algorithm counted 54,000 aircraft from 2,500 satellite images across 350 air bases to create a historical baseline of activity and detect ongoing changes.
Further information
For more information, please visit the technical documentation.