Simulating the spatial dynamics of urban growth with an integrated modeling approach: A case study of Foshan, China

Abstract

Foshan is one of China's rapidly industrializing cities, and the municipality has undergone significant urbanization in the past 20 years. To investigate the urban development of Foshan municipality, we used an integrated modeling approach based on Markov chain (MC), logistic regression, and cellular automata (CA) to study dynamic changes in land use. An MC and neighborhood transfer matrix were used to determine the influence of the central cell and neighborhoods, while logistic regression was fitted by factors derived from a principle component analysis to produce probability maps of the driving forces. The accuracy of the Markov-logistic-CA model was sufficient for predicting processes of change in urban land use compared to other models. Then three scenarios were constructed through the setting of potential land use policies, land demands, and mapping future public transportation to reflect the possible urban patterns of Foshan in 2025. The simulation results indicated that a spread-out urban pattern will be dominant in Foshan in the future, while zoning development, with the preservation of ecological features in rural-urban areas, will relieve the environmental deterioration of the Foshan municipality.