On the multi-dimensionality and sampling of air transport networks |
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| Affiliation: | 1. Innaxis Foundation & Research Institute, José Ortega y Gasset 20, 28006 Madrid, Spain;2. Centro de Investigación en Simulación Computacional, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain;3. Department of Planning and Transport, University of Westminster, 35 Marylebone Road, London NW1 5LS, UK;4. University of Oxford, Department of Engineering Science, Parks Road, Oxford OX1 3PJ, UK;5. Faculdade de Ciências e Tecnologia, Departamento de Engenharia Electrotécnica, Universidade Nova de Lisboa, Lisboa, Portugal;1. Department of Planning and Transport, University of Westminster, London, United Kingdom;2. The Innaxis Foundation and Research Institute, Madrid, Spain;1. Faculty of Management and Economics, Dalian University of Technology, No. 2 Linggong Road, Dalian City 116024, China;2. Transportation Management College, Dalian Maritime University, No. 1 Linghai Road, Dalian City 116026, China;1. Department of Transport and Planning, University of Westminster, 35 Marylebone Road, London NW1 5LS, United Kingdom;2. The Innaxis Foundation and Research Institute, Calle de José Ortega y Gasset, 20, 28006, Madrid, Spain;1. Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Campus UIB, 07122 Palma de Mallorca, Spain;2. Transport and ICT Directorate, Ingeniería de Sistemas para la Defensa de España, S.A., Beatriz de Bobadilla 3, 28040 Madrid, Spain;1. Department of Planning and Transport, University of Westminster, 35 Marylebone Road, London NW1 5LS, UK;2. Delft University of Technology, Section Control and Operations, Kluyverweg 1, 2629 HS Delft, The Netherlands;3. Scuola Normale Superiore, Piazza dei Cavalieri 7, Pisa 56126, Italy;4. Dipartimento di Fisica e Chimica, Università degli Studi di Palermo, Viale delle Science Ed. 18, Palermo 90128, Italy;5. Central European University, Center for Network Science and Department of Economics, Nador u. 9, 1051 Budapest, Hungary;6. Department of Aerospace Engineering, Escuela Superior de Ingenieros, Camino de los Descubrimientos, Universidad de Sevilla, 41092 Sevilla, Spain;7. The Innaxis Foundation & Research Institute, José Ortega y Gasset 20, 28006 Madrid, Spain;8. Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal;1. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong Special Administrative Region;2. Department of Systems Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenue, Hong Kong Special Administrative Region |
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| Abstract: | Complex network theory is a framework increasingly used in the study of air transport networks, thanks to its ability to describe the structures created by networks of flights, and their influence in dynamical processes such as delay propagation. While many works consider only a fraction of the network, created by major airports or airlines, for example, it is not clear if and how such sampling process bias the observed structures and processes. In this contribution, we tackle this problem by studying how some observed topological metrics depend on the way the network is reconstructed, i.e. on the rules used to sample nodes and connections. Both structural and simple dynamical properties are considered, for eight major air networks and different source datasets. Results indicate that using a subset of airports strongly distorts our perception of the network, even when just small ones are discarded; at the same time, considering a subset of airlines yields a better and more stable representation. This allows us to provide some general guidelines on the way airports and connections should be sampled. |
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| Keywords: | Air transport Complex networks Network topology |
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