## 4 Discussion  
### Analysis of Indicators for Evaluating Key Nodes  
(1) Connectivity Strength (CS)  
Using the node importance evaluation method, the CS was calculated using Equation (9). The results are illustrated in Figure 9:  
* The middle line plot shows the CS of each node across different network layers;
* The stacked bar chart above displays the cumulative CS of the same node across different networks;
* The curve on the right depicts the distribution of node CS within the same layer network. Figure 8: Spatial analysis of node rankings in the railway station network. Figure 9 presents the computed Connectivity Strength (CS) values for each node in the LC, YX, and DC networks. The horizontal axis represents the network nodes, while the vertical axis denotes the CS values, reflecting the connectivity strength of individual nodes across the three network layers. The data points are distinguished using different markers and colors:  
* LC network (red circles, dashed red lines);
* YX network (orange squares, dashed orange lines);
* DC network (blue diamonds, dashed blue lines). The figure demonstrates considerable variation in CS values across different network layers:  
* The LC network exhibits the highest degree of fluctuation, with multiple nodes showing significantly elevated CS values;
* The DC network maintains a more moderate distribution, with peaks aligning with those in the LC network, albeit at lower magnitudes;
* The YX network displays relatively stable CS values, with minimal fluctuation, indicating a more evenly distributed connectivity structure. The highest CS values are observed at specific nodes: Node 6-18 DG shows the maximum CS values in the LC and DC networks, reaching 25 and 16, respectively. This indicates that this node plays a critical role in network connectivity and likely represents a major junction or switching point in the railway station network. Several other nodes exhibit localized peaks in CS values, particularly within the LC network, suggesting highly connected regions that may serve as key operational hubs. From the viewpoint of structural influence, the higher CS values in the LC network suggest that certain nodes hold greater connectivity importance, potentially serving as critical decision points for train routing and operational efficiency. The relatively lower CS values in the YX network indicate a more stable and distributed connectivity pattern, which may contribute to network robustness but limit the adaptability of certain nodes. The alignment of peak values between the LC and DC networks suggests a correlation between local connectivity strength and overall network topology, which could be further investigated for infrastructure optimization. This comparative analysis provides valuable insights into node connectivity strength across different network layers, highlighting key junctions, connectivity hubs, and potential structural bottlenecks. Future research could incorporate real-time traffic data and simulation models to further assess the impact of high-CS nodes on network performance and operational efficiency. (2) Destination and Source Node Count (DNC and SNC)  
Figure 9: Comparative distribution of CS across LC, YX, and DC networks. Using Equations (10) and (11), the DNC and SNC of each node were calculated. The distributions of DNC and SNC are shown in Figure 10, where darker data points indicate a higher density of nodes at that location. Figure 10 illustrates the relationship between destination node count (DNC) and source node count (SNC) for the LC, YX, and DC networks, respectively. Each figure contains the following features:  
* The horizontal axis represents DNC and the vertical axis represents SNC, denoting the number of source connections a node possesses;
* The color intensity of each scatter point corresponds to the density of nodes at that location, with darker points representing a higher concentration of nodes;
* All three plots maintain identical axis ranges to facilitate direct comparisons across network layers.