Urban Growth Simulation Based on a Multi-Dimension Classification of Growth Types: Implications for China’s Territory Spatial Planning

Abstract

One of the primary aims of China’s territory spatial planning is to control the urban sprawl of local municipals and prevent regional competition and the negative consequences on the environment—which emphasizes the top-down spatial regulation. Indeed, the traditional cellular automaton (CA) model still has limitations when applied to the whole administration area since it may ignore the differences among cities and towns. Thus, this paper proposed a CM-CA (clustering, multi-level logit regression, integrated with cellular automaton) framework to simulate urban growth boundaries for cities and towns simultaneously. The significant novelty of this framework is to integrate several urban growth modes for all cities and towns. We applied our approach to the city of Xi’an, China, and the results showed satisfactory simulation accuracy of a CM-CA model for multiple cities and towns, and the clusters’ effects contributed 74% of the land change variance. Our study provides technical support for urban growth boundary delineation in China’s spatial planning.

Keywords

• urban growth boundary
• clustering
• multi-level logit regression
• cellular automaton
• urban simulation models