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Analysis of degree characteristics in airport networks

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Abstract

Flight operation data provides a record of air traffic behaviour in detail, and has become an important resource for studying air traffic patterns. In this paper, the degree characteristic of air traffic networks is studied using flight operation data in order to explain air traffic behaviour. The degree indexes were founded from the perspective of network structure and network function based on complex network theory and traffic flow theory. The connectivity degree, traffic degree and delay degree were established, and the characteristics of these three degrees were studied based on American flight data from different days in 2015 over different time periods of each day. Research shows that at all scales the number degrees, volume degrees and duration degrees are all of power-law distribution, and the power exponents are different depending on the scale, date and index. The power exponents fluctuate from 0.5 to 1.5. In general, the connectivity degree exponent is greater than that of the traffic degree and the delay degree. The duration degree exponent is greater than the traffic degree. The exponents are greater on holidays than they are on non-holidays, as well as during non-working hours than during working hours of the day. Compared with non-holidays, the average connectivity degree and delay degree are larger on holidays, and the average traffic degree is smaller. This reveals that most airports only provide flights to one airport, and the airports’ numbers and flight volumes both decrease on holidays. The power indexes of the delay degree and traffic degree are basically the same. The main mode of traffic (arrivals or departures) during each time period is also studied.

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Acknowledgements

The authors are grateful to their anonymous reviewers for their critical and constructive review of the manuscript. This study was co-supported by the National Natural Science Foundation of China (Grant No.: 71801215), and the Fundamental Research Funds for the Central Universities (3122016C009). The authors would like to acknowledge Logan Praznik for his efforts proofreading end editing this manuscript.

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Authors and Affiliations

  1. College of Air Traffic Management, Civil Aviation University of China, Tianjin, 300300, People’s Republic of China

    Zhaoyue Zhang & Shanmei Li

  2. Department of Mathematics and Computer Science, Brandon University, Brandon, R7A6A9, Canada

    Gautam Srivastava

  3. Research Center for Interneural Computing, China Medical University, Taichung, 40402, Taiwan, People’s Republic of China

    Gautam Srivastava

  4. Department of Information Management, National Taichung University of Science and Technology, Taichung, 404, Taiwan

    Shu-Fen Chiou

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  1. Zhaoyue Zhang
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  2. Shanmei Li
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  3. Gautam Srivastava
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  4. Shu-Fen Chiou
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Correspondence to Gautam Srivastava.

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Zhang, Z., Li, S., Srivastava, G. et al. Analysis of degree characteristics in airport networks. J Ambient Intell Human Comput (2019). https://doi.org/10.1007/s12652-019-01558-x

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