The Spatial Pattern and Influencing Factors of Traffic Dominance in Xi’an Metropolitan Area

Abstract

Metropolitan areas shoulder the crucial task of regional and even national economic development. Analyzing the spatial patterns and influencing factors of metropolitan traffic dominance can provide a scientific basis for the optimization of its transportation and industrial layout, which is conducive to the development of its economy. Previous studies on traffic dominance paid little attention to metropolitan areas and even less so to study these areas from the perspective of town units, even though these are the basic units that narrow the gap between urban and rural areas and thus achieve regional economic integration. The traffic dominance model can comprehensively and wholly reflect regional traffic conditions, due to its multidimensional characteristics (including traffic network density, traffic arterial influence and accessibility). Consequently, taking the Xi’an metropolitan area as an exemplar and the town as the basic unit, this paper employs this model and other methods to study the spatial pattern and influencing factors of its traffic dominance. The results show the following: (1) the traffic network density, traffic arterial influence and accessibility had different distribution patterns; however, they were the same in that their superiorities were relatively high in the main urban area of Xi’an city or along and on both sides of the high-speed railways (HSRs), whereas relatively low in the peripheral areas; (2) the integrated traffic dominance consistently displayed a “point-axis” pattern, with greater superiority in the east–west axis areas within 30 km of Xi’an city, especially in the main urban area of Xi’an city; (3) the integrated traffic dominance between towns had stable agglomeration correlation in the global areas and formed three major modes in the local areas: high–high, low–low and low–high aggregation. High–high mode was concentrated in the main urban areas of Xi’an and Xianyang city, low–low mode was mainly distributed in the Weibei hilly and gully areas and the Qinling mountain areas and low–high mode always nested on the edge of high–high areas; and (4) the location, GDP and elevation had a greater impact, whereas construction intensity, population and slope had a relatively small influence on the town’s traffic dominance, and their influence ability had a decreasing trend from 2010 to 2022. Finally, this paper discusses the theoretical implications, practical values and some prospects based on the research results.