ABSTRACT
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.
ABSTRACT
The COVID19 pandemic shifted the focus and attention of political decision-makers and strategic planers over the past years. There is an emerging need to address the local and regional differences of the impact of policies and demonstrate to airspace users and the travelling public how the air transportation system responds to such large-scale events. This paper approaches the impact of the COVID-19 pandemic as a massive air service disruption of the pre-pandemic global connectivity and regional air transport networks. A resilience based approach is followed to identify and quantify the impact levels. For this initial application the parameters have been chosen in accordance with the operational experience of the authors. This paper applies a data driven approach and uses open and crowd-collected data to assess the impact of COVID-19. This included data preparatory action to augment the ADSB based data set with other publicly available data sources to provide a basis for the analysis of three major regional air transport networks. The analytical results were obtained for the United States, Europe, and Brazil for the pandemic period 2020 and the first half of 2021. The year 2019 is used for reference purposes and to establish a baseline for the impact evaluation. The analysis of the developments in Brazil, Europe, and the United States showed similarities but also stark differences in terms of the response to curb the spread of COVID-19 and associated travel policies. The results obtained demonstrate the feasibility to address global air transport problems with open and crowd sourced data. Future work to harmonize the open data collection and utility can provide a basis for a more open and transparent management of air transportation crisis response, evaluation, or strategic planning. The initial approach to address resilience can further inform the on-going work of the ICAO performance expert group under the Global Air Navigation Plan. © 2021 IEEE.
ABSTRACT
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.