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<p>Understanding whether urban spatial patterns are becoming more concentrated or decentralized is central to debates on sustainable urban development and spatial restructuring. Using geocoded enterprise registration locations as a fine-grained proxy for economic activities, this study models intraurban density decay from city centers for 118 prefecture-level Chinese cities in 2006 and 2019. We first compare three classical density functions, negative exponential, inverse power, and Gaussian, and identify the negative exponential function as the best-performing specification for characterizing urban density profiles. Building on the selected model, we calculate comparable gradient-based indicators to quantify concentration versus decentralization and examine their spatiotemporal evolution. The findings indicate that 60.2% of cities experienced a flattening of the density gradient, suggesting a shift towards more decentralized spatial structures, whereas 39.8% exhibited recentralization. Further exploratory regression analyses identify factors associated with these divergent urban trajectories, including urban size, GDP per capita, public transport infrastructure, and government interventions. This study provides a comparable framework for measuring urban spatial restructuring from the perspective of economic activity distribution and offers policy-related evidence for balancing core intensification and periphery expansion in the context of rapid urbanization.</p>

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Concentration or decentralization? Evidence from the density functions of urban economic activities

  • 期刊论文

  • 发表日期：

    2026年6月26日

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  • Ying Xu,
  • Ke Chen,
  • Chang Xia

摘要

Understanding whether urban spatial patterns are becoming more concentrated or decentralized is central to debates on sustainable urban development and spatial restructuring. Using geocoded enterprise registration locations as a fine-grained proxy for economic activities, this study models intraurban density decay from city centers for 118 prefecture-level Chinese cities in 2006 and 2019. We first compare three classical density functions, negative exponential, inverse power, and Gaussian, and identify the negative exponential function as the best-performing specification for characterizing urban density profiles. Building on the selected model, we calculate comparable gradient-based indicators to quantify concentration versus decentralization and examine their spatiotemporal evolution. The findings indicate that 60.2% of cities experienced a flattening of the density gradient, suggesting a shift towards more decentralized spatial structures, whereas 39.8% exhibited recentralization. Further exploratory regression analyses identify factors associated with these divergent urban trajectories, including urban size, GDP per capita, public transport infrastructure, and government interventions. This study provides a comparable framework for measuring urban spatial restructuring from the perspective of economic activity distribution and offers policy-related evidence for balancing core intensification and periphery expansion in the context of rapid urbanization.