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

Siyu Miao, Yang Xiao () and Ling Tang
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Siyu Miao: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Yang Xiao: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Ling Tang: Dongguan Geographic Information and Planning Research Center, Dongguan 523129, China

Land, 2022, vol. 11, issue 12, 1-14

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 (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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