| Abstract |
This paper presents a predictive analysis of the urban growth in Riyadh city for the years 2030 and 2050. The Multi-Layer Perceptron Markov Chain model is used to simulate the forecast based on spatio-temporal transitional aspects of previous urban growth and driving factors. The driving factors encompass the population density, the topographic elevation and slope, the distances from the road network, railways and waterways. The simulations reveal that a combination of two driving factors: the road network and railways have the highest effect size with an accuracy rate of 84.18% and a skill measure of 0.6837. The results show also that the urban growth in Riyadh city is primarily driven by economic and infrastructural development as well as public policy initiatives rather than population growth. The predicted urban expansions will potentially follow locations highly accessible to rail-lines, with expected growth in the northwestern and southeastern zones. Thus, the expected urban shape will potentially converge towards the Transit Oriented Developments. This study emphasizes the importance of understanding the significant driving factors of urban growth for sustainable and smart urban agglomerations. Further studies are needed to explore the effects of economic, technological, and energetical reforms in Saudi Arabia on the evolution of urban dynamics. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. |
