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Integrated Communications, Navigation and Surveillance Conference, ICNS ; 2023-April, 2023.
Article in English | Scopus | ID: covidwho-20244358


The European Air Transportation Network was significantly impacted by the COVID-19 pandemic, resulting in an unprecedented loss of flight connections. Utilizing a combination of graph representation learning and time series analysis, this paper studies the evolution of both the global connectivity as well as the structure of the European Air Transportation Network from January 2020 to December 2022. Specifically, it finds strong differences in recovery rates for flights across six different market segments. In terms of network structure, the study finds that structural roles that are present in the pre-covid network have seen a loss in performance over the course of the pandemic, but have recovered to pre-covid levels. Using regional changes in structural roles, this study identifies Italy as the region with the strongest increase and the United Kingdom as the region with the strongest decrease in structural role, finding substantial differences in recovery rates per market segment. Lastly, this study pays special attention on the effect of the Russia-Ukrainian war on the European Air Transportation Network. © 2023 IEEE.

40th IEEE/AIAA Digital Avionics Systems Conference, DASC 2021 ; 2021-October, 2021.
Article in English | Scopus | ID: covidwho-1642524


The COVID-19 pandemic accelerated the use, sharing, and distribution of data on a global basis. Higher levels of transparency were achieved with continual updates of pandemic related information. The air transportation sector - while by definition an information rich industry - is a notable exception. While different organizations offered aggregated data on air traffic developments on national or airport level, complementary data on air traffic movements for further analysis are not available publicly. This creates a deadlock between addressing the societal needs of monitoring how aviation recovers from the COVID-19 pandemic and addresses the aspirational environmental goals. This paper investigates the feasibility of utilizing open data for the operational performance monitoring at airports. The exploratory work focusses on a subset of the indicators proposed under ICAO's Global Air Navigation Plan used to assess the operational performance in the arrival phase. A novel approach to characterize and assess the arrival flow management and level of traffic synchronization is presented. This will allow to evaluate on-going air traffic recovery and identify operational bottlenecks. The study is performed as a use-case analysis for three major European airports by comparing the observed performance in the months of March and May for the successive years 2019, 2020, and 2021. The results demonstrate the general feasibility and utility of open data for operational performance monitoring. The classical performance measure for the arrival flow are determined based on the open trajectory data. A geospatial-temporal evaluation support the tracking of traffic synchronisation effort. A higher level of transparency therefore available to the interested public, policy decision-makers and strategic planners with direct feedback on the recovery and actual operational performance. The suitability of the traffic synchronization measure and its parameterization requires further validation across a wider set of airports and will be iteratively refined. © 2021 IEEE.