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Aircraft detection at planetary scale
Introduction On a typical day, there are greater than 10,000 aircraft (commercial, private, and military) in flight at any given time. The precise departure (point A) and destination (point B) locations, as well as the timing of flight activity, provide critically important information for myriad industries.
Monitoring aircraft activity is vital for economic, defense, and intelligence purposes, but current methods rely on tedious and expensive processes, especially at scale. The rapid pace of geopolitical developments and sheer volume of data means that analyzing airfields manually is no longer feasible, especially in conflict/sensitive zones where aircraft movements aren’t publicly reported. We utilize a deep learning object detection model optimized for Planet’s medium resolution imagery, which runs at sufficient speed so that we are free to analyze as many airports and airstrips as desired.
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