Land Use Transition and Regional Development Patterns Under Shared Socioeconomic Pathways: Evidence from Prefecture-Level Cities in China

Xiaodong Zhang, Mingjie Yang, Rui Guo, Yaolong Li and Fanglei Zhong ()
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Xiaodong Zhang: Information and Communication Company of State Grid Gansu Electric Power Company, Lanzhou 730000, China
Mingjie Yang: Information and Communication Company of State Grid Gansu Electric Power Company, Lanzhou 730000, China
Rui Guo: Information and Communication Company of State Grid Gansu Electric Power Company, Lanzhou 730000, China
Yaolong Li: School of Economics, Minzu University of China, Beijing 100081, China
Fanglei Zhong: School of Economics, Minzu University of China, Beijing 100081, China

Land, 2025, vol. 14, issue 3, 1-22

Abstract: This study evaluates the spatial–temporal evolution of land use intensity and regional development under five shared socioeconomic pathways (SSPs) through prefecture-level projections in China (2020–2050). This study integrates the population–development–environment model with back propagation (BP) neural networks, a supervised learning algorithm, to analyze how differentiated development trajectories reshape land systems. Results reveal distinct pathways: SSP5 (conventional development) and SSP1 (sustainability) achieve high-income thresholds by 2025/2028 with intensive land development, while SSP3 (fragmentation) risks stagnation post-2037 accompanied by inefficient land use. Spatial analysis identifies persistent dualism across the Hu Huanyong Line—83.6% of urban land expansion concentrates in eastern regions, whereas western areas exhibit 56% lower land productivity. By 2050, regional land use efficiency differentials (0.3–4.3% Gross Domestic Product/capita growth) highlight challenges in balancing urban agglomeration and ecological conservation. These findings provide empirical evidence for optimizing land allocation policies during China’s economic transition.

Keywords: shared socioeconomic pathways; middle-income trap; prefecture city scale; population–development–environment model; BP neural network model; China (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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