No abstract

With the development of metro systems, the problem of unbalanced ridership into and out of the stations, caused by the singleness of station area development, has become increasingly prominent. Research on land use optimization in metro station areas based on a two-way balance of ridership is proposed. First, the stepwise regression analysis method was used to build a relationship model between ridership and the land use index under the guidance of the two-way balance of ridership. Second, the range was optimized by calculating the land use factors of the metro station area. Finally, the land use of the metro station area was optimized from the perspectives of development intensity and land usage. Taking metro stations in Xi’an as an example, the results show that the land use characteristics of metro station areas are quite different. Under the guidance of the two-way balance of ridership, the current land use values of Daminggongxi Station, Nanshaomen Station, and Tiyuchang Station exceed the optimal value range and can be reduced by more than 2.78%. The current land use values of Chaoyangmen Station, Longshouyuan Station, and Weiyijie Station are within the optimized range. The land use values of Kaiyuanmen Station, Banpo Station, and Fengchengwulu Station are below the optimized range and could be increased by more than 13.7%. In addition, optimizing the development intensity or adjusting the land type is further proposed to ensure that the land use factors of station areas are within the calculated optimal value range. The results provide a reference for the optimization of land use in the Xi’an metro station area.

During the different periods of a day, the imbalanced distribution of inbound ridership, that is related to land use, results in extreme flow, which makes metro management challenging. The causes of imbalanced passenger flow from the perspective of land use in metro station areas are studied in this paper. More specifically, based on site classification, the impact of land use, including the floor area ratio and gross floor area on passenger flow, was explored by using a multiple linear regression model. The results first indicate that the impact intensities of the floor area ratio on peak hourly flow were 0.41, 0.21, and 0.20 around business, residential, and mixed sites, respectively. Second, for the abovementioned sites, the types with the greatest impact intensities of gross floor area on peak hourly flow were commercial and business facilities (B), residential (R), as well as administration and public services (A), which were 0.73, 0.32, and 0.87, respectively. Finally, for the land-development-control schemes for business, residential, and mixed sites, the maximum values of the floor area ratio were roughly 7.2, 5.3, and 8.2, respectively. The results presented in this study provide guidance for land development in metro station areas and contribute to avoiding the emergence of extreme passenger flow.

In recent years, Xi'an metro construction has been progressing rapidly, becoming the primary mode of urban green public transportation. Since the ridership of the metro is closely linked to the characteristics of its surrounding built environment, a key problem in promoting the benign development between the two is to explore the spatiotemporal distributional difference in ridership and its influencing factors. In this study, the "5D" characteristics of built environment are described by density, diversity, design, destination and distance variables. The spatiotemporal distribution characteristics of ridership are analyzed via Arc GIS and Python, while the nonlinear relationships between ridership and built environment of 106 metro stations of downtown Xi'an, as well as relevant threshold effects are revealed via Shapley additive explanations  with gradient boosted decision tree (GBDT-SHAP). The results show that: (1) Xi'an metro travel presents a medium-short spatiotemporal distribution, and the ridership network is characterized by strong center-spillover. (2) The nonlinear relationship between built environment and ridership is ubiquitous and presents a threshold effect. The impact threshold of bus stop density on ridership is 4-6 pcs/km2, the impact threshold of road network density is roughly 4-5 km/km2, and the effective threshold of building density does not exceed 20%. (3) The positive impact of POI facility density on peak ridership is stronger than that at flat hours. Variables like land use mixture, population density and distance from downtown have a time-driven effect on the ridership, whose importance and influence change with time. This study provides a better understanding of the spatiotemporal impact of Xi'an's built environment on metro travel, which is of profound significance for the coordinated development between the city and metro construction.