IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v677y2025ics0378437125005709.html

Multifractal and informational analysis of air traffic flow: A case in mainland China

Author

Listed:
  • Shi, Zongbei
  • Zhao, Mo
  • He, Min
  • Xue, Yichen
  • Yan, Jiajie
  • Wang, Xinglong

Abstract

Air traffic flow is a crucial indicator of aviation operational performance, and plays a pivotal role in ensuring the smooth and orderly management of airspaces. Analyzing the multifractal characteristics and informational properties of air traffic flow helps reveal complex fluctuations and identify evolutionary trends. In this study, we analyze the air traffic flow data from five months in 2019, covering 138 sectors distributed across seven regions in mainland China. We utilize multifractal detrended fluctuation analysis (MFDFA) and Fisher–Shannon analysis to characterize the dynamic behaviors of these air traffic flow series. The results indicate that air traffic flows in all studied regions exhibit clear multifractal properties, characterized by right-skewed multifractal spectra. These multifractal characteristics are primarily driven by long-range correlations present within the air traffic flows. Particularly notable multifractal features are observed in the southwest, north, and east regions of mainland China. Moreover, multifractal properties are prevalent across high-altitude sectors, demonstrating heterogeneous spatial distribution patterns. Among these regions, Xinjiang exhibits the highest level of organization and orderliness in air traffic flow, and correspondingly, the weakest multifractal strength. The relationship between the Fisher information and Shannon entropy of air traffic sectors in China displays bi-segmental scaling, following a power-law distribution. This finding further underscores the presence of distinct variations in operational patterns among different air traffic sectors.

Suggested Citation

  • Shi, Zongbei & Zhao, Mo & He, Min & Xue, Yichen & Yan, Jiajie & Wang, Xinglong, 2025. "Multifractal and informational analysis of air traffic flow: A case in mainland China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 677(C).
  • Handle: RePEc:eee:phsmap:v:677:y:2025:i:c:s0378437125005709
    DOI: 10.1016/j.physa.2025.130918
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437125005709
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2025.130918?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Yang, Lei & Yin, Suwan & Han, Ke & Haddad, Jack & Hu, Minghua, 2017. "Fundamental diagrams of airport surface traffic: Models and applications," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 29-51.
    2. Gui, Jun & Zheng, Zeyu & Fu, Dianzheng & Fu, Yang & Liu, Zhi, 2021. "Long-term correlations and multifractality of toll-free calls in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    3. Liu, Hongzhi & Zhang, Xie & Hu, Huaqing & Zhang, Xingchen, 2022. "Exploring the impact of flow values on multiscale complexity quantification of airport flight flow fluctuations," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    4. Nasri, Bouchra R. & Rémillard, Bruno N., 2019. "Copula-based dynamic models for multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 172(C), pages 107-121.
    5. Guan, Sihai & Wan, Dongyu & Yang, Yanmiao & Biswal, Bharat, 2022. "Sources of multifractality of the brain rs-fMRI signal," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    6. Rak, Rafał & Grech, Dariusz, 2018. "Quantitative approach to multifractality induced by correlations and broad distribution of data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 48-66.
    7. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    8. Jaros{l}aw Kwapie'n & Pawel Blasiak & Stanis{l}aw Dro.zd.z & Pawe{l} O'swik{e}cimka, 2022. "Genuine multifractality in time series is due to temporal correlations," Papers 2211.00728, arXiv.org, revised Mar 2023.
    9. Laura Raisa Miloş & Cornel Haţiegan & Marius Cristian Miloş & Flavia Mirela Barna & Claudiu Boțoc, 2020. "Multifractal Detrended Fluctuation Analysis (MF-DFA) of Stock Market Indexes. Empirical Evidence from Seven Central and Eastern European Markets," Sustainability, MDPI, vol. 12(2), pages 1-15, January.
    10. Wang, Qizhen, 2019. "Multifractal characterization of air polluted time series in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 167-180.
    11. Liu, Hongzhi & Zhang, Xingchen & Zhang, Xie, 2020. "Multiscale multifractal analysis on air traffic flow time series: A single airport departure flight case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    12. Zhang, Xie & Liu, Hongzhi & Zhao, Yifei & Zhang, Xingchen, 2019. "Multifractal detrended fluctuation analysis on air traffic flow time series: A single airport case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    13. Gao-Feng Gu & Wei-Xing Zhou, 2010. "Detrending moving average algorithm for multifractals," Papers 1005.0877, arXiv.org, revised Jun 2010.
    14. Fang, Zhenyuan & Zhu, Shichao & Fu, Xin & Liu, Fang & Huang, Helai & Tang, Jinjun, 2022. "Multivariate analysis of traffic flow using copula-based model at an isolated road intersection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    15. Telesca, Luciano & Abate, Nicodemo & Faridani, Farid & Lovallo, Michele & Lasaponara, Rosa, 2023. "Revealing traits of phytopathogenic status induced by Xylella Fastidiosa in olive trees by analysing multifractal and informational patterns of MODIS satellite evapotranspiration data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    16. Robert Kluszczyński & Stanisław Drożdż & Jarosław Kwapień & Tomasz Stanisz & Marcin Wątorek, 2025. "Disentangling Sources of Multifractality in Time Series," Mathematics, MDPI, vol. 13(2), pages 1-32, January.
    17. Zhang, Mingyuan & Liang, Boyuan & Wang, Sheng & Perc, Matjaž & Du, Wenbo & Cao, Xianbin, 2018. "Analysis of flight conflicts in the Chinese air route network," Chaos, Solitons & Fractals, Elsevier, vol. 112(C), pages 97-102.
    18. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    19. Erjia Ge & Yee Leung, 2013. "Detection of crossover time scales in multifractal detrended fluctuation analysis," Journal of Geographical Systems, Springer, vol. 15(2), pages 115-147, April.
    20. Sadegh Movahed, M. & Hermanis, Evalds, 2008. "Fractal analysis of river flow fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 915-932.
    21. Cárdenas-Moreno, P.R. & Moreno-Torres, L.R. & Lovallo, M. & Telesca, L. & Ramírez-Rojas, A., 2021. "Spectral, multifractal and informational analysis of PM10 time series measured in Mexico City Metropolitan Area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    22. Telesca, Luciano & Lovallo, Michele & Chamoli, Ashutosh & Dimri, V.P. & Srivastava, K., 2013. "Fisher–Shannon analysis of seismograms of tsunamigenic and non-tsunamigenic earthquakes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3424-3429.
    23. Rafal Rak & Dariusz Grech, 2018. "Quantitative approach to multifractality induced by correlations and broad distribution of data," Papers 1805.11909, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guan, Sihai & Wan, Dongyu & Yang, Yanmiao & Biswal, Bharat, 2022. "Sources of multifractality of the brain rs-fMRI signal," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    2. Sierra-Porta, D., 2024. "A multifractal approach to understanding Forbush Decrease events: Correlations with geomagnetic storms and space weather phenomena," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    3. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Casado Belmonte, M.P. & Trinidad Segovia, J.E., 2020. "A note on power-law cross-correlated processes," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    4. Olivares, Felipe & Zanin, Massimiliano, 2022. "Corrupted bifractal features in finite uncorrelated power-law distributed data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    5. Chandra, Aitichya & Verma, Ashish & Sooraj, K.P. & Padhi, Radhakant, 2023. "Modelling and assessment of the arrival and departure process at the terminal area: A case study of Chennai international airport," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    6. Li, Xing, 2021. "On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    7. Dutta, Srimonti & Ghosh, Dipak & Samanta, Shukla, 2014. "Multifractal detrended cross-correlation analysis of gold price and SENSEX," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 195-204.
    8. Yao, Can-Zhong & Liu, Cheng & Ju, Wei-Jia, 2020. "Multifractal analysis of the WTI crude oil market, US stock market and EPU," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    9. Schadner, Wolfgang, 2022. "U.S. Politics from a multifractal perspective," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    10. Sarker, Alivia & Mali, Provash, 2021. "Detrended multifractal characterization of Indian rainfall records," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    11. Marcin Wk{a}torek & Marcin Kr'olczyk & Jaros{l}aw Kwapie'n & Tomasz Stanisz & Stanis{l}aw Dro.zd.z, 2024. "Approaching multifractal complexity in decentralized cryptocurrency trading," Papers 2411.05951, arXiv.org.
    12. Morales Martínez, Jorge Luis & Segovia-Domínguez, Ignacio & Rodríguez, Israel Quiros & Horta-Rangel, Francisco Antonio & Sosa-Gómez, Guillermo, 2021. "A modified Multifractal Detrended Fluctuation Analysis (MFDFA) approach for multifractal analysis of precipitation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    13. Chatterjee, Sucharita & Ghosh, Dipak, 2021. "Impact of Global Warming on SENSEX fluctuations — A study based on Multifractal detrended cross correlation analysis between the temperature anomalies and the SENSEX fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    14. Ghosh, Dipak & Chakraborty, Sayantan & Samanta, Shukla, 2019. "Study of translational effect in Tagore’s Gitanjali using Chaos based Multifractal analysis technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1343-1354.
    15. Wang, Fang & Han, Guosheng, 2023. "Coupling correlation adaptive detrended analysis for multiple nonstationary series," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    16. Ruan, Qingsong & Zhou, Mi & Yin, Linsen & Lv, Dayong, 2021. "Hedging effectiveness of Chinese Treasury bond futures: New evidence based on nonlinear analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    17. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    18. Gulich, Damián & Zunino, Luciano, 2014. "A criterion for the determination of optimal scaling ranges in DFA and MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 17-30.
    19. Chatterjee, Sucharita, 2020. "Analysis of the human gait rhythm in Neurodegenerative disease: A multifractal approach using Multifractal detrended cross correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    20. Wang, Jian & Huang, Menghao & Wu, Xinpei & Kim, Junseok, 2023. "A local fitting based multifractal detrend fluctuation analysis method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:677:y:2025:i:c:s0378437125005709. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.