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<p>Dynamic monitoring and quantitative assessment of evolving urban forms in metropolitan areas are critical for optimizing development trajectories through timely policy intervention, thereby fostering regional sustainable development and enhancing climate adaptation. However, existing research has predominantly emphasized single-city indicators, with intra-city spatial structures and inter-city linkages largely underexplored. Focusing on the Wuhan Metropolitan Area (WMA) in China using long-term remote sensing data, this study built a consistent analytic framework to: 1) delineate built-up areas with a bottom-up city clustering algorithm, 2) characterize urban form from aspects of size, shape, directionality, dispersion, and centrality, respectively measured by urban size, area-weighted mean shape index (AWMSI), equal fan analysis (EFA), dispersion index (DI), and Moran’s I, 3) assess spatio-temporal disparities and convergence at both metropolitan and city levels. Results revealed three typical modes of urban form evolution: 1) Differentiated development phases across WMA, with central Wuhan leading in early expansion and southwestern cities lagged behind; 2) Clustered development with Wuhan expanded relatively evenly in all directions, while surrounding cities displayed clear directional biases and formed two distinct clusters in southeast and west; 3) Dispersed expansion with rising shape complexity at the city level. These findings highlight pronounced spatial heterogeneity and partial convergence, underscoring the importance of compact intra-city growth and coordinated inter-city integration. Overall, the study provides a robust technical basis for metropolitan-scale urbanization monitoring and contributes to advancing United Nations Sustainable Development Goals, particularly SDG 11 (Sustainable Cities), SDG 13 (Climate Action), and SDG 15 (Life on Land).</p>

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Disparity and convergence in multi-dimensional urban form evolution: Unraveling typical urban development modes in Wuhan metropolitan area

  • 期刊论文

  • 发表日期：

    2025年12月10日

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  • J. Shen,
  • H. Liu

摘要

Dynamic monitoring and quantitative assessment of evolving urban forms in metropolitan areas are critical for optimizing development trajectories through timely policy intervention, thereby fostering regional sustainable development and enhancing climate adaptation. However, existing research has predominantly emphasized single-city indicators, with intra-city spatial structures and inter-city linkages largely underexplored. Focusing on the Wuhan Metropolitan Area (WMA) in China using long-term remote sensing data, this study built a consistent analytic framework to: 1) delineate built-up areas with a bottom-up city clustering algorithm, 2) characterize urban form from aspects of size, shape, directionality, dispersion, and centrality, respectively measured by urban size, area-weighted mean shape index (AWMSI), equal fan analysis (EFA), dispersion index (DI), and Moran’s I, 3) assess spatio-temporal disparities and convergence at both metropolitan and city levels. Results revealed three typical modes of urban form evolution: 1) Differentiated development phases across WMA, with central Wuhan leading in early expansion and southwestern cities lagged behind; 2) Clustered development with Wuhan expanded relatively evenly in all directions, while surrounding cities displayed clear directional biases and formed two distinct clusters in southeast and west; 3) Dispersed expansion with rising shape complexity at the city level. These findings highlight pronounced spatial heterogeneity and partial convergence, underscoring the importance of compact intra-city growth and coordinated inter-city integration. Overall, the study provides a robust technical basis for metropolitan-scale urbanization monitoring and contributes to advancing United Nations Sustainable Development Goals, particularly SDG 11 (Sustainable Cities), SDG 13 (Climate Action), and SDG 15 (Life on Land).