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Exploring the relationships between urban form metrics and the vegetation biomass loss under urban expansion in China

Author

Listed:
  • Tong Zhang

    (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, PR China University of Chinese Academy of Sciences, PR China)

  • Sophia Shuang Chen

    (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, PR China)

  • Guangyu Li

Abstract

Compact urban form has been applied as a strategy to reduce the loss of green space that occurs from development, but the impact of this policy on the provision of green space still presents many uncertainties. This research investigated the statistical relationship between urban form indicators and the loss of vegetation biomass to understand the response of quality green space provision to changes in urban morphology. A methodology combining multi-source data assimilation, statistical analysis, and spatial analysis was adopted for the Yangtze River Delta cities of China. First, six urban metrics were selected to describe the shape and layout of urban patches in each city, and the total biomass loss index was then introduced as a parameter. The values of urban metrics and total biomass loss index were calculated for the 50 Yangtze River Delta cities. Second, ordinary least squares regression and geographically weighted regression analyses were then used to establish a quantitative relationship between total biomass loss index and urban form indicators. The results revealed an extremely negative correlation between total biomass loss index and the three urban variables of Richard compactness, density gradient, and the Gini coefficient; moreover, the parameter estimates for the three variables in the geographically weighted regression model were local and varied over space. Third, the mechanisms by which the urban form influences biomass loss were discussed and different urban form planning strategies for particular urban areas were suggested. In conclusion, compact urban form in a clustered layout of urban areas with a dense central agglomeration was verified to be ecologically superior and conducive to green space protection. For the physical interpretation of the statistical relationship between urban morphology and vegetation loss, the interface effect of urban agglomeration on vegetation merits further study.

Suggested Citation

  • Tong Zhang & Sophia Shuang Chen & Guangyu Li, 2020. "Exploring the relationships between urban form metrics and the vegetation biomass loss under urban expansion in China," Environment and Planning B, , vol. 47(3), pages 363-380, March.
    • Handle: RePEc:sae:envirb:v:47:y:2020:i:3:p:363-380
    DOI: 10.1177/2399808318816993
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    1. Brueckner, Jan K & Fansler, David A, 1983. "The Economics of Urban Sprawl: Theory and Evidence on the Spatial Sizes of Cities," The Review of Economics and Statistics, MIT Press, vol. 65(3), pages 479-482, August.
    2. Sun, Ranhao & Chen, Liding, 2017. "Effects of green space dynamics on urban heat islands: Mitigation and diversification," Ecosystem Services, Elsevier, vol. 23(C), pages 38-46.
    3. Tao, Yu & Li, Feng & Liu, Xusheng & Zhao, Dan & Sun, Xiao & Xu, Lianfang, 2015. "Variation in ecosystem services across an urbanization gradient: A study of terrestrial carbon stocks from Changzhou, China," Ecological Modelling, Elsevier, vol. 318(C), pages 210-216.
    4. Raymond Bunker, 2014. "How Is the Compact City Faring in Australia?," Planning Practice & Research, Taylor & Francis Journals, vol. 29(5), pages 449-460, October.
    5. Patrick Rérat, 2012. "Housing, the Compact City and Sustainable Development: Some Insights From Recent Urban Trends in Switzerland," International Journal of Housing Policy, Taylor & Francis Journals, vol. 12(2), pages 115-136.
    6. Wei Song & Xiangzheng Deng, 2015. "Effects of Urbanization-Induced Cultivated Land Loss on Ecosystem Services in the North China Plain," Energies, MDPI, vol. 8(6), pages 1-16, June.
    7. Clifford M. Hurvich & Jeffrey S. Simonoff & Chih‐Ling Tsai, 1998. "Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 271-293.
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    Cited by:

    1. Anqi Zhang & Weifeng Li & Jiayu Wu & Jian Lin & Jianqun Chu & Chang Xia, 2021. "How can the urban landscape affect urban vitality at the street block level? A case study of 15 metropolises in China," Environment and Planning B, , vol. 48(5), pages 1245-1262, June.
    2. Helena Madureira & Ana Monteiro, 2021. "Going Green and Going Dense: A Systematic Review of Compatibilities and Conflicts in Urban Research," Sustainability, MDPI, vol. 13(19), pages 1-20, September.
    3. Lingyue Li & Zhixin Qi & Teng Zhong, 2021. "Forest Transition and Its Dynamics in Subtropical Chongqing, China since 1990s," Land, MDPI, vol. 10(8), pages 1-14, July.

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