Articles | Volume 13, issue 2
https://doi.org/10.5194/essd-13-357-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-357-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
11 Feb 2021
Data description paper |
| 11 Feb 2021
| 11 Feb 2021
Crowdsourced air traffic data from the OpenSky Network 2019–2020
Martin Strohmeier
CORRESPONDING AUTHOR
Armasuisse Science and Technology, 3603 Thun, Switzerland
Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK
OpenSky Network, 3400 Burgdorf, Switzerland
Xavier Olive
ONERA DTIS, Université de Toulouse, 31055 Toulouse CEDEX 4, France
OpenSky Network, 3400 Burgdorf, Switzerland
Jannis Lübbe
OpenSky Network, 3400 Burgdorf, Switzerland
Matthias Schäfer
OpenSky Network, 3400 Burgdorf, Switzerland
University of Kaiserslautern, 67663 Kaiserslautern, Germany
Vincent Lenders
Armasuisse Science and Technology, 3603 Thun, Switzerland
OpenSky Network, 3400 Burgdorf, Switzerland
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Total article views: 9,380 (including HTML, PDF, and XML)
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| 7,318 | 1,918 | 144 | 9,380 | 173 | 153 |
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Total article views: 7,174 (including HTML, PDF, and XML)
Cumulative views and downloads
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| HTML | XML | Total | BibTeX | EndNote | |
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| 5,882 | 1,152 | 140 | 7,174 | 147 | 130 |
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- XML: 140
- Total: 7,174
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Total article views: 2,206 (including HTML, PDF, and XML)
Cumulative views and downloads
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Total article views: 9,380 (including HTML, PDF, and XML)
Thereof 8,736 with geography defined
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Total article views: 7,174 (including HTML, PDF, and XML)
Thereof 6,795 with geography defined
and 379 with unknown origin.
Total article views: 2,206 (including HTML, PDF, and XML)
Thereof 1,941 with geography defined
and 265 with unknown origin.
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- Deep learning-derived optimal aviation strategies to control pandemics S. Rizvi et al. 10.1038/s41598-024-73639-7
- Air traffic modernization and control: ADS-B system implementation update 2022: A review D. Kožović et al. 10.5937/fme2301117K
- Visual analysis of changes in European air transport during the COVID-19 pandemic from interactive maps Y. Abilpatta & V. Voženílek 10.2478/mgrsd-2023-0038
- Study of a representative wind selection method using track data to evaluate Pacific flight operations H. Hirabayashi et al. 10.1016/j.jairtraman.2024.102639
- Spectral Embedding of Weighted Graphs I. Gallagher et al. 10.1080/01621459.2023.2225239
- A fine-grained RDF graph model for fuzzy spatiotemporal data H. Ji et al. 10.1016/j.asoc.2024.112166
- Estimating the risk of SARS-CoV-2 infection in New Zealand border arrivals R. Arnold et al. 10.1186/s44263-024-00057-2
- Deep learning techniques for enhanced security and privacy in 6G terrestrial–nonterrestrial network architecture M. Khalid et al. 10.1007/s11227-025-07097-x
- PANDEM-Source, a tool to collect or generate surveillance indicators for pandemic management: a use case with COVID-19 data F. Orchard et al. 10.3389/fpubh.2024.1295117
- Quantifying aviation’s contribution to global warming M. Klöwer et al. 10.1088/1748-9326/ac286e
- Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change J. Laughner et al. 10.1073/pnas.2109481118
- Construction of Economic Data Management System Based on BP Neural Network X. Han & R. Khan 10.1155/2022/9036917
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- High diversity in Delta variant across countries revealed by genome‐wide analysis of SARS‐CoV‐2 beyond the Spike protein R. Suratekar et al. 10.15252/msb.202110673
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- Modeling Civil Aviation Emissions with Actual Flight Trajectories and Enhanced Aircraft Performance Model J. Wang et al. 10.3390/atmos15101251
- Framework for assessing and easing global COVID-19 travel restrictions T. Le et al. 10.1038/s41598-022-10678-y
6 citations as recorded by crossref.
- A Taxonomy Proposal for the Assessment of the Changes in Soundscape Resulting from the COVID-19 Lockdown C. Asensio et al. 10.3390/ijerph17124205
- Crowdsourced air traffic data from the OpenSky Network 2019–2020 M. Strohmeier et al. 10.5194/essd-13-357-2021
- Исследование зависимостей и распределений в случайных сетях для смешанных моделей эволюции и при удалении узлов М. Наталья Михайловна et al. 10.25728/ubs.2024.109.5
- How the COVID-19 Pandemic Muted and Remixed the World’s Acoustics for a While C. Asensio et al. 10.1007/s40726-022-00236-5
- Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change J. Laughner et al. 10.1073/pnas.2109481118
- Hitting the ‘pause’ button: What does COVID-19 tell us about the future of heritage sounds? D. Spennemann & M. Parker 10.1515/noise-2020-0022
Latest update: 09 Jul 2025
Short summary
Flight data have been used widely for research by academic researchers and (supra)national institutions. Example domains range from epidemiology (e.g. examining the spread of COVID-19 via air travel) to economics (e.g. use as proxy for immediate forecasting of the state of a country's economy) and Earth sciences (climatology in particular). Until now, accurate flight data have been available only in small pieces from closed, proprietary sources. This work changes this with a crowdsourced effort.
Flight data have been used widely for research by academic researchers and (supra)national...
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