Relationships between Resident Activities and Physical Space in Shrinking Cities in China—The Case of Chaoyang City

Wenshi Yang, Fan Chen, Qianqian Wei and Zhenwei Peng ()
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Wenshi Yang: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Fan Chen: Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hong Kong SAR, China
Qianqian Wei: Shenzhen Institute, Sun Yat-sen University, Shenzhen 510275, China
Zhenwei Peng: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China

Land, 2024, vol. 13, issue 4, 1-18

Abstract: Shrinking cities suffer from a decreased level of resident activities. As a result, areas with low levels of resident activities may become breeding grounds for social issues. To ease and prevent social issues, it is important to deploy physical space optimisation strategies to effectively guide the distribution of resident activities in shrinking cities. To support the development of such spatial strategies, this paper introduces machine learning-based methods for analysing the nuanced non-linear relationship between resident activities and physical space in shrinking cities. Utilising dual-scale grids, this study calculates multi-source spatial elements, which are subsequently integrated with resident activity data to construct a gradient boosting decision tree model. It then analyses the weight of different spatial elements’ impacts on resident activities and their nonlinear relationships. The model proposed in this study demonstrates good precision in construing the relationship between resident activities and physical space. Based on the research findings, strategies for different types of spatial development in shrinking cities are drawn out. This paper advocates for the application of this analytical approach before conducting spatial planning in shrinking cities to maximise the effectiveness of spatial development in guiding resident activities.

Keywords: shrinking city; physical space elements; resident activities; gradient boosting decision tree model; physical space optimisation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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