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

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.