## 4 Data Analysis
### Accessing Distance Analysis  
The accessing distance for cyclists to rail transit is also influenced by urban morphology, such as station characteristics and the non-motorized transportation environment around the station [36]. This section analyzes the accessing distance of Mobike at four categories of stations to determine the relationships therein. The distance used in the study  
Figure 5: Tukey HSD analysis results of six indicators.  
is the bicycle travel distance recommended by navigation software. Although it is not the actual distance, it approximates the actual situation more precisely than the Euclidean distance. Taking 100 m as the interval in the analysis, the probability density distribution scatter diagrams of accessing distance were generated based on the preliminary assumption that its probability density is a normal distribution. Aided by the MATLAB curve fitting toolbox, the probability density distribution curve of a linear or quadratic normal distribution model was selected to fit the accessing distance of four categories (Figure 5).  
The fitting effect is illustrated in Figure 6. SSE and RMSE are approximately 0, and the R-square and adjusted R-square values are approximately 1. Thus, the fitting effect is reasonable.  
The normal distribution exhibits two symmetrical catastrophe points, of which the right catastrophe point is at 85% cumulative probability, called the 85% quantile. After this quantile, the passenger service rate decreases significantly with an increase in distance. Hence, the distances of all the means of transportation at 85% cumulative probability are deemed as the accessing distance:  
\[\text{d}_{\text{Cluster1}}=1874\text{ m},\quad\text{d}_{\text{Cluster2}}=1690 \text{ m},\]  
\[\text{d}_{\text{Cluster3}}=2460\text{ m},\;\text{d}_{\text{Cluster4}}=1467 \text{ m}.\]  
According to the fitting results, there are significant variations in the accessing distances of various subway stations. The general rule is that the accessing distance at the urban center is short, whereas it is large at the periphery.  
The accessing distance for Cluster 3 stations located in the periphery is significantly larger than those of the other three categories. The land-use mixture and road network density around the stations are low, the distance between the adjacent stations is large, and rail transit is the most convenient means of transport for the residents living in these areas to travel downtown; therefore, travelers are more willing to ride a larger distance to use the rail transit.  
Cluster 4 of stations with the shortest accessing distance is located in the urban center. The streets and alleys are densely scattered around the station, the land mixture and public transport coverage are high, and the station spacing is short; therefore, a traveler generally travels a shorter distance to reach the rail transit station, or by selecting other means of transport. Thus, the acceptable critical accessing distance is short. The location of Cluster  
Figure 6: Probability density distribution of accessing distances for FFBS to urban rail transit.  
1 and Cluster 2, their degree of influence by the urban morphology, and their accessing distances lie between those of Cluster 3 and Cluster 4 stations.