TartanAviation: A Multi-Modal Dataset for Aviation Applications

This resource contains the scripts to download the dataset. The scripts can also be found at https://github.com/castacks/TartanAviation.

We introduce TartanAviation, an open-source multi-modal dataset focused  on terminal-area airspace operations. TartanAviation provides a holistic  view of the airport environment by concurrently collecting image,  speech, and ADS-B trajectory data using setups installed inside airport  boundaries. The datasets were collected at both towered and non-towered  airfields across multiple months to capture diversity in aircraft  operations, seasons, aircraft types, and weather conditions. In total,  TartanAviation provides 3.1M images, 3374 hours of Air Traffic Control  speech data, and 661 days of ADS-B trajectory data. The data was  filtered, processed, and validated to create a curated dataset. In  addition to the dataset, we also open-source the code-base used to  collect and pre-process the dataset, further enhancing accessibility and  usability. We believe this dataset has many potential use cases and  would be particularly vital in allowing AI and machine learning  technologies to be integrated into air traffic control systems and  advance the adoption of autonomous aircraft in the airspace.