Simultaneous Simulation of Urban Shrinkage and Expansion Using Cellular Automaton and Maximum Information Entropy Models: Case Study of Urban Evolution in Wuhan Metropolitan Area

During the past two decades discussions on urban shrinkage have been increasing in intensity, mainly due to the irresistible trends of migration, economic transformation, and the so-called "siphon effect" of large and mega cities. Yet, very few studies have tried to understand urban shrinkage from the perspective of local microscopic unit evolution. This study develops a novel model for simultaneous simulation of expansion and shrinkage (MSSES) of urban built-up areas. Starting from a microscopic basis, our MSSES can simulate both the processes and the states that lead to spatial expansion or shrinkage. A MaxEnt model is further used to investigate the driving factors of microspatial changes and compute the probabilities of shrinkage (or expansion) of urban built-up areas. Finally, it simulates the explicit layout of the spatial distribution of shrinkage (or expansion) patches with the help of a sorting cellular automata (CA) model. The validity of MSSES is verified using multisourced data from the Wuhan agglomeration, China. We show that (1) MSSES can more accurately simulate urban expansion or shrinkage than the currently widely used neighborhood-based Logistic-CA (NL-CA) and (2) MSSES has advantage in solving the commonly seen problem of "diffusion-coalescence," especially for the simulation of outlying expansion. Against the context of the Wuhan metropolitan area, we also found that overall the shrinkage trend is slowing down significantly, presenting three types of shrinkage at city-scale: remote shrinkage, peripheral shrinkage, and international shrinkage. Our study has contributions to the body of knowledge as well as practical implications for urban management and improving the sustainable development of urban areas in both China and abroad. The city we live in may be experiencing a situation where expansion and shrinkage are happening simultaneously. Hence, the simulation and prediction of temporal and spatial changes in urban expansion and shrinkage hold great importance in formulating urban policies. In this study, we propose a model capable of simultaneously predicting urban growth and shrinkage, and apply this model to the urban morphological changes in the Wuhan metropolitan area from 2000 to 2035. The simulation results demonstrate the effectiveness of this model in predicting the locations of urban expansion and contraction in advance. Furthermore, we discovered that the overall shrinkage trend is projected to significantly decelerate in the future. These findings offer support for intervention in urban planning, guiding the development of urban spaces and advancing the scientific aspects of urban planning.