An efficient method for calculating space-time accessibility measures based on the preprocessing of transport networks and its computational implementation

Abstract

In theory, space-time accessibility measures are supposed to be guaging the degree of accessibility to spatial opportunities more appropriately and accurately than other spatial accessibility measures. However, in practice, there expected to be computational time issues in calculating the measures. Considering the difficulties, this study develops an efficient method for calculating space-time accessibility measures based on the preprocessing of transport networks. It then demonstrates, from a case study, how the proposed method can be computationally implemented in the opensource programming language Python.