Analysis of Jobs-Housing Relationship and Commuting Characteristics Around Urban Rail Transit Stations

In recent years, with the acceleration of the urbanization process, the contradiction between transportation infrastructure facilities and spatial layout of urban land use is escalating. However, integrated urban planning and transportation planning provides a new way to significantly relieve traffic congestion and the phenomenon of jobs-housing separation brought by urbanization. In this study, the massive internet data of urban planning (e.g. internet-based positioning data) and traditional data resources of the traffic system (e.g. smart card data) are combined to identify the jobs-housing relationship around urban rail transit stations instead of the method of theoretical modeling. All the stations are classified into different categories on this basis. Besides, as for the connections of different regions and the spatial distribution of the urban population, the method of smart card data mining is adopted to analyze commuting characteristics and spatial distribution of origin-destination travel demand for different categories of stations. Finally, analysis of the correlation between the resident population around urban rail transit stations and commuting passenger flow is carried out by statistical methods. Corresponding results can be further applied to the integrated planning of transportation and land use.