A logistic regression model for explaining urban development on the basis of accessibility: a case study of Naples

In this paper, we present a statistical modelling approach in order to explain the presence and development of built-up areas by means of a set of distinct accessibility indicators, so as to use these results in local planning studies, to test urban sustainability measures, and to eventually forecast the impact of accessibility to transport systems on urban development. On the basis of encouraging results obtained in a previous study in the Netherlands, the authors apply a multinomial logistic regression, with urban development as the dependent variable and accessibility and context information as independent variables. The statistical model employs two kinds of accessibility measure: simple Euclidean distances, as well as a specific articulated accessibility indicator which takes into account spatial opportunities as well as distances. The results confirm the reliability and robustness of the chosen approach and confirm the limited usefulness of retrieving and deploying complex data to obtain composite indicators.