Measuring Connectivity of Pedestrian Street Networks in the Built Environment for Walking: A Space-Syntax Approach

Network connectivity is an important aspect of the built environment. However, it rarely captures the attention of decision-makers while implementing pedestrian projects. In recent years, Space-Syntax (SS) analysis is gaining popularity among researchers due to its ability to clearly demonstrate the topological configuration of a physical network. This research carries out a connectivity analysis of 297 links across three pedestrian networks in Varanasi, India, thereby exploring the relationship between pedestrian volume, SS indices in the Indian context, and other built environment features, such as presence of sidewalk, right-of-way (ROW) and landuse area. Data collection includes developing a GIS database of the pedestrian network, 30-min pedestrian volume counts at various locations, and calculating SS connectivity measures from the configuration of the pedestrian networks. Resulting SS indices were analyzed with existing pedestrian volumes through correlation, stepwise multiple linear regression (MLR), and path models. Results of the analysis showed that the SS index ‘Normalized Angular Integration (NAIN)’ to be highly correlated with pedestrian volume (r = 0.57). Subsequently, the MLR and path models show a statistically significant relationship of pedestrian volume with NAIN, ROW, presence of sidewalk, and commercial area. ROW affects the pedestrian volume both directly and indirectly in a commercial area, thereby indicating a requirement for improving/providing walking facilities in such areas. The study concludes with practical implications for local authorities that highlight the importance of providing walking infrastructures at commercial streets having high connectivity. The study also shows the significance of NAIN as an effective measure of pedestrian street network connectivity.