## 5 Results and Discussion
### Nonlinear Effects on Metro Ridership  
We select the top three explanatory variables for nonlinear analysis according to the influence degree of explanatory variables in the two zones. Figure 7 shows the nonlinear results for the explanatory variables for metro stations inside and outside the 4 th Ring Road. For metro stations inside the 4 th Ring Road, the relationship between the number of entrances and exits and metro ridership is overall positively correlated. When the number of entrances and exits is between five and seven, the effect of the number of entrances and exits on metro ridership is stable. This means that if we want to adjust the ridership at a metro station, adjusting the number of entrances in the range of 5-7 may not change the ridership at the metro station. However, when the number of entrances and exits is greater than seven, the impact of the number of entrances and exits on metro ridership tends to increase (Figure 7a). When the mixed utilization of land is less than 0.84, the impact of the mixed utilization of land on metro ridership is minimal (Figure 7b) and the overall impact of the mixed utilization of land on metro ridership is positive. If we want to improve the ridership of a metro station inside the 4 th Ring Road, it may be more effective to increase the land use mix degree beyond 0.84. The nonlinear effect of the density of bus lines on metro ridership is more complex. When the density of the bus line is less than 35, the effect of the bus line density on metro ridership is less. At the same time, when the density of the bus line is in the range of 35-39, the effect of the bus line density on ridership is negative. In addition, when the density of bus lines is greater than 54, the effect of the bus line density on ridership is also negative (Figure 7c). Figure 7: Nonlinear results for explanatory variables of metro stations inside and outside the 4 th Ring Road: (**a**) Number of entrances and exits for metro stations inside the 4 th Ring Road. (**b**) Mixed utilization of land for metro stations inside the 4 th Ring Road. (**c**) Density of bus lines for metro stations inside the 4 th Ring Road. (**d**) Number of public service facilities for metro stations outside the 4 th Ring Road. (**e**) Building density for metro stations outside the 4 th Ring Road. (**f**) Road density for metro stations outside the 4 th Ring Road. For metro stations outside the 4 th Ring Road, when the number of public service facilities is less than 65, the impact of the number of public service facilities on the ridership at metro stations is small. However, when the number of public service facilities is in the range of 65-80, the impact of the number of public service facilities on the ridership at metro stations increases sharply. At the same time, when the number of public service facilities is greater than 80, the influence of the number of public service facilities on the ridership of the metro station tends to level off and there is even a negative correlation (Figure 7d). The overall impact of building density on metro ridership is negative. The effect of building density on metro ridership decreases sharply when building density is in the range of 0.07-0.10. The effect of building density on metro ridership is relatively flat when the building density is greater than 0.10 (Figure 7e). The effect of road density on metro ridership decreases sharply when the road density is between 1.9 and 4.5, but levels off when the road density is greater than 4.5 (Figure 7f). This demonstrates that the 1.9-4.5 range is the most effective if road density is to be used to change metro ridership. We find the selected explanatory variables have a strong threshold effect on the ridership of the metro station. That is consistent with existing research findings [3; 21]. Understanding the nonlinear effects of explanatory variables on metro ridership can help us to adjust metro ridership from an urban renewal perspective.