Spatiotemporal evolution of urbanization and its implications to urban planning of the megacity, Shanghai, China

Landscape Ecology(2022)

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摘要
Context Urbanization has profoundly changed urban landscape patterns and morphologies. Understanding the spatiotemporal evolution of these changes and their driving forces is vital to decision making for urban planning and sustainable urban development. Objectives This study aims to quantify the spatiotemporal pattern of urban growth in Shanghai, China for testing urban growth hypotheses, to identify its driving factors, and to provide insights for sustainable urban planning. Methods We fitted a nonlinear curve to the urbanization pattern, employed landscape expansion indices to quantify the spatiotemporal evolution of urbanization, utilized partial least square regression to differentiate contribution of main socioeconomic driving factors. Results Urbanized land in Shanghai exhibited a logistic growth pattern from 1985 to 2015. The annual growth rate of urban area showed a wave-like pattern and peaked in 2000–2005. Urban growth modes of leapfrog, edge expansion, and infilling were identified, and these patterns alternates in dominance over time. The urbanization process in Shanghai followed the spiraling diffusion-coalescence hypothesis. The net increase of year-end residential population, urban infrastructure investment, and the total investment in fixed assets were the dominant driving factors to urban growth. Conclusion A logistic curve well quantified the temporal pattern of urbanization in Shanghai. Urbanization has slowed down, approaching the plateau of the curve, implying that urban growth driven by population increase and investment should switch to sustainable urban renewal and ecological constructions. Investment to urban green and blue infrastructures could help achieve “negative growth” targeted by the Shanghai Master Plan (2017–2035) for the overall developed land.
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关键词
Shanghai,Urban growth pattern,Diffusion-coalescence process,Socioeconomic driving forces,Urban planning
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