Using Explorative Network Analysis Methods to Investigate Edinburgh’s Road & Bus Networks in the Context of Smart Cities

Abstract

Urban transport network expansion is often reactionary to physical demands from other forms of urban growth, such as population increase and urban sprawl, which can cause access imbalance. Characterising access is therefore critical, however with the immense inherent complexity of transport networks, this is challenging. Smart Cities provide a solution, with a foundational concept of making the invisible visible by digesting large complex data. Graph theory provides a methodological framework for this, through the abstraction and analysis of key network data. In this study, access in Edinburgh’s road and bus transport networks is characterised using novel network and multi-variate self-organising map analysis. A new perspective of access is developed, using betweenness, closeness, degree and power centrality measures. Results are compared with the SIMD Access Domain to identify similarities and disparities, with Closeness Centrality showing most similar distribution while Betweenness Centrality reveals greater reliance on arterial pathways for access. Power Centrality also imitates wave propagation as node density decreases. Through comparative analysis, Edinburgh’s bus network is determined well connected, optimising the use of the underlying road network by prioritising well connected routes based on centrality measures. Development opportunities in the bus network are explored aligning with the Smart City agenda, with road segments along E Fettes Avenue, Arboretum Place, the A199 and Restalrig Road identified as priority locations. Limitations of the study are explored, principally the use of open-source proxy variables in edge weight calculation relative to privatised empirical data.