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Car detection
Description
An algorithm that detects and quantifies cars in Pléiades imagery using wide-area object detection. It can be used to conduct pattern-of-life analyses and activity-based intelligence. Car detection can be used for traffic and parking management, retail analysis, and urban planning.
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 point detections corresponding to the location of cars |
| 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 is applicable in wide areas worldwide. Its performance may however vary according to geography and imagery features. For example, the algorithm is more reliable in urban areas. The algorithm generally performs better in North American and European areas of interest. The algorithm has known limitations when dealing with highly shadowed imagery, those containing closely packed over vehicles (0 pixels in between), and desert imagery.
This algorithm was tested by a 3rd party using a validation set, consisting of approximately 100,000 marked cars in 50 countries spanning 20,000 images of deserts, ports and parking lots across 6 continents. The training set contains 180,000 images and spans many variable conditions including time of day, time of year, terrain, configuration of vehicles, etc.
Further information
For more information, please visit the technical documentation.