Big Data and Spatial Econometric Analysis of the Layout of Public Transport Stations in Wuhan and Zhengzhou

Along with the rapid development of urbanisation in China, the development pressure of urban public transport is increasing day by day. As an important infrastructure and component of the urban public transport system, the rationality of the spatial layout of bus stops is of great significance in improving the efficiency of the urban public transport system. Most of the studies on the layout of public transport are about how urban public transport can serve the urban residents in terms of living, socialising, commuting, consumption and recreation. This paper proposes that public transport facilities in cities (especially megacities) should also match the spatial distribution of residential areas, companies, catering services, attractions, and recreation. Different from the traditional methods of spatial statistical analyses, such as Moran index, nuclear density and so on. This paper adopts big data spatially econometrically analyse the layout of public transport stations in Wuhan and Zhengzhou from the perspective of multi-source data. The results of the case study show that compared with the obvious inner ring monocentric agglomeration layout of bus stops in Zhengzhou, the spatial layout of bus stops in Wuhan takes into account the clothing, food, housing, transportation and socio-economic development of the residents, and thus the spatial layout of bus stops in Wuhan seems to be more reasonable than that of Zhengzhou. The distribution of public bus stops in both cities is affected by the spatial distribution of public bus stops in its surrounding areas, which shows a significant spatial autocorrelation. This is consistent with the linear layout of public bus stops and the spatial concentration of its service objects.