An Optimal Local Connectivity-Based Rasterization Method to Support Transport Accessibility and Resilience Analysis

Accurately calculating travel time-to map transport accessibility and assess transport resilience to inform sustainability-oriented decisions-remains a critical modeling and computational challenge if considering large-scale all-modal transport. Vector-based methods cannot capture movement across off-network areas and are still computationally expensive in some applications for large-scale networks, whereas conventional raster-based methods may bring considerable inaccuracies if computationally acceptable. Here, we propose an optimal local connectivity-based method to rasterize transportation networks and enable a smooth integration of all travel modes to support fastest travel time-based accessibility and resilience analysis. Experimental studies on road networks in cities worldwide, together with theoretical analyses of lattices and simulations of random planar graphs, show its capability for remarkably accurate and rapid estimation of travel time in various network conditions. Successful applications in accurately mapping national-scale accessibility to healthcare facilities and rapidly estimating the worst-case resilience against local disruption demonstrate its utility to support many research and policy needs.