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Swedish civil air traffic control dataset
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Luftfartsverket, Sweden. (Computer Graphics and Image Processing)ORCID iD: 0000-0003-1660-2834
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. (Computer Graphics and Image Processing)ORCID iD: 0000-0002-7765-1747
2023 (English)In: Data in Brief, E-ISSN 2352-3409, Data in Brief, ISSN 2352-3409, Vol. 48, article id 109240Article in journal (Refereed) Published
Abstract [en]

The Swedish Civil Air Traffic Control (SCAT) dataset consists of 13 weeks of data collected from the area control in Sweden flight information region. The dataset consists of detailed data from almost 170,000 flights as well as airspace data and weather forecasts. The flight data includes system updated flight plans, clearances from air traffic control, surveillance data and trajectory prediction data. Each week of data is continuous but the 13 weeks are spread over one year to provide variations in weather and seasonal traffic patterns. The dataset does only include scheduled flights not involved in any incident reports. Sensitive data such as military and private flight has been removed.

The SCAT dataset can be useful for any research related to air traffic control, e.g. analysis of transportation patterns, environmental impact, optimization and automation/AI.

Place, publisher, year, edition, pages
ELSEVIER , 2023. Vol. 48, article id 109240
Keywords [en]
Air traffic control, dataset, machine learning
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-194282DOI: 10.1016/j.dib.2023.109240ISI: 001018434100001PubMedID: 37383746OAI: oai:DiVA.org:liu-194282DiVA, id: diva2:1761267
Projects
WASP NEST _main_
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Swedish Transport Administration
Note

Funding: LFV; Trafikverket [TRV 2019/36272]

Available from: 2023-05-31 Created: 2023-05-31 Last updated: 2024-11-04

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Output format
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