Analyzing and Predicting Spatio-Temporal Urban Expansion Based on Cellular Automata Modelling

Urban agglomerations play a pivotal role in the economic and social progress of regions and countries. Substantial urban expansion, particularly in metropolitan areas, has been generally associated with economic and population growth. This study investigates the spatio-temporal urban expansion of Romania’s major metropolitan areas using Cellular Automata (CA). Focusing on eight metropolitan areas, the paper analyzes land cover dynamics from 2015 to 2020 and it develops a model of urban growth for the years 2025 and 2030. The novelty of the paper is represented by the combination of the CA algorithm and economic complexity for predicting the expansion of built-up areas. To our knowledge it is the first attempt to combine these two aspects in modelling urban growth. The analysis incorporates six variables such as land use, population density, distance to roads, slope, restricted areas and economic complexity to offer insights into future urbanization trends. Our study concluded that CA proved to be a valuable approach for modelling urban growth. The great added value of the paper is related to the integration of the economic complexity index into urban growth model. Doing so, our results not only summarize both economic development and demographic dynamics within major metropolitan areas, but they have provided the urban growth model with a novel and more robust basis for prediction. The results indicate variations in the growth rates and spatial patterns of urbanization, emphasizing the importance of informed urban planning for a sustainable urban development. A major conclusion of the paper is that the actual urban fabric will not suffer significant changes, as it is already compact. Only at the peripheries of the major urban centres there are free space reserves which can be densified by future constructions. Thus, the lack of free space in the city’s core areas and the expensive costs drive the expansion of the built-up areas towards the suburban localities located near the urban centres.