Measuring and Examining Accessibility and Its Spatial Heterogeneity from a Route Perspective

Considering the overall performance of public transportation systems is crucial for evaluating a system and is essential for accurately assessing the accessibility of the system. However, most previous studies have measured accessibility from the perspective of stations. Only a few studies have addressed accessibility and its spatial heterogeneity from the route perspective. To fill these gaps, this paper explores the construction and validation of a route-level accessibility measure. First, this study proposes a route-level accessibility measure that holistically evaluates the accessibility level of public transit systems from a route perspective. Second, the proposed measure is applied to assess the accessibility of bus and metro in Beijing, the two most widely used modes in the existing public transit system. Finally, the proposed measure is compared with other route-level accessibility measures from the literature. Machine learning models are used to explore the nonlinear relationship between these accessibility outcomes and land prices. The proposed measure is then validated by comparing its evaluation performance with other methods. The results of the three performance evaluation metrics, namely, R2, root-mean-square error, and relative importance, indicate that the proposed measure outperformed the existing route-level accessibility measure. The proposed measure exhibits stronger predictive power for land prices compared with the existing route-level accessibility measure in the literature. By measuring the accessibility of public transit systems from a route perspective, this study complements the exploration of route-level accessibility measures in the research field, helping planners rationally evaluate the coverage level of urban public transit networks.