Urban growth and transport infrastructure interaction in Jeddah between 1980 and 2007

This paper aims to use spatial statistical tools to explore the reciprocal spatial–temporal effects of transport infrastructure and urban growth of Jeddah city, a fast developing polycentric city in Saudi Arabia. Global spatial autocorrelation (Moran's I) and local indicators of spatial association (LISA) are first used to analyze the spatial–temporal clustering of urban growth and transport infrastructure from 1980 to 2007. Then, spatial regression analysis is conducted to investigate the mutual spatial–temporal effects of urban growth and transport infrastructure. Results indicate a significant positive global spatial autocorrelation of all defined variables between 1980 and 2007. LISA results also reveal a constant significant spatial association of transport infrastructure expansion and urban growth variables from 1980 to 2007. The results not only indicate a mutual spatial influence of transport infrastructure and urban growth but also reveal that spatial clustering of transport infrastructure seems to be influenced by other factors. This study shows that transport infrastructure is a constant and strong spatial influencing factor of urban growth in the polycentric urban structure that Jeddah has. Overall, this study demonstrates that exploratory spatial data analysis and spatial regression analysis are able to detect the spatial–temporal mutual effects of transport infrastructure and urban growth. Further studies on the reciprocal relationship between urban growth and transport infrastructure using the study approach for the case of monocentric urban structure cities are necessary and encouraged.

► Planners in fast growing cities need to better understand the growth–transport interaction.
► A set of spatial statistical tools are used to explore this interaction.
► We find that transport infrastructure strongly influences urban growth.
► These tools are able to describe the mutual spatial–temporal interaction.
► These tools help planners to respond to spatial challenges in fast growing cities.