Improving the integration of rail and long-distance bus services is essential for enhancing regional connectivity and sustainable transport accessibility. Existing node-place models mainly focus on station surroundings and do not consider how buses extend access explicitly to support the transit network. Therefore, this study develops a multimodal network-based approach applied to a case of sub-rural Scotland. Three new integration metrics are designed — travel time-weighted population (demand coverage), feeder bus service availability (supply), and network centrality (regional connectivity). These indicators are then incorporated into a three-dimensional node-place framework, which evaluates the integration performance of 102 railway stations across the study area. Results reveal spatial differences in integration performance, identifying well-connected hubs such as Inverness and Stirling, alongside stations like Rosyth and Dunfermline City where demand is not matched by service provision. The analysis also shows opportunities to strengthen east–west regional links and improve multimodal access through targeted interventions, such as co-locating bus termini. By extending the node–place model to include multimodal catchments and network-level connectivity, the framework captures aspects of integration that are overlooked in rail-only assessments and offers a unified diagnostic tool for identifying where rail-bus integration improvements may have the greatest effect. The method is built on publicly available data, enabling its application in other regions and adaptation to support future demand modelling. • An integrated bus-rail network is constructed for multimodal node-place analysis. • Feeder bus services to stations are evaluated with time-weighted population coverage. • Impact of both interurban and feeder bus services on rail accessibility is evaluated. • Centrality analysis of rail-only and rail-bus networks reveals structural differences. • Generation of spatial options to help identify gaps for integration improvements.
Lin et al. (Thu,) studied this question.