Analysis of Factors Influencing the Urban Carrying Capacity of the Shanghai Metropolis Based on a Multiscale Geographically Weighted Regression (MGWR) Model

Author:

Cao Xiangyang,Shi YishaoORCID,Zhou LiangliangORCID,Tao Tianhui,Yang Qianqian

Abstract

With the rapid development of urban economy and the continuous expansion of urban scale, the limitations of urban carrying capacity begin to appear. For the sustainable development of the city, more and more scholars are paying attention to the research onurban carrying capacity. Basedon the continuous research of the authors’ research group over the past ten years, this paper uses a multiscale geographically weighted regression model and method to explore the impact of geographical location, floor area ratio, public transportation, residents’ consumption level, the density of high-tech enterprises, and the ecological environment on the carrying capacity of the Shanghai metropolis. The results show that (1) the impact of geographical location on the bearing capacity decreases from downtown to the outer areas and from the northeastern area to the southwestern area of Shanghai. (2) On the whole, the elasticity of the average floor area ratio to the urban carrying capacity is 0.52%. In different regions, most of the central urban areas have exceeded the optimal average plot ratio. With an increase in the average plot ratio, the urban carrying capacity presents a downward trend. Other sample areas generally did not reach the average optimal plot ratio, especially the southwestern area of Shanghai. With an increase in the average plot ratio, the urban carrying capacity of this area improved significantly. (3) The elasticity of public transportation convenience to the urban carrying capacity is 0.23%; that is, the average increase in the urban carrying capacity is 0.23% for every 1% increase in public transportation convenience. The elasticity of residents’ consumption level is −0.18%; in other words, every 1% increase in residents’ consumption level will reduce the urban carrying capacity by 0.18% on average. The elasticity of the density of high-tech enterprises is 0.08%; hence, when the density of high-tech enterprises increases by 1%, the urban carrying capacity increases by 0.08% on average. Lastly, the elasticity of the eco-environmental status index is 0.17%; that is, every 1% increase in the eco-environmental status index increases the urban carrying capacity by 0.17% on average.

Funder

Shanghai Planning and Land Resource Administration

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Ecology,Global and Planetary Change

Reference46 articles.

1. Analysis on the urban land resources carrying capacity during urbanization——A case study of Chinese YRD

2. An alternative method for analyzing dimensional interactions of urban carrying capacity: Case study of Guangdong-Hong Kong-Macao Greater Bay Area

3. Analysis on the effectiveness of indicators for evaluating urban carrying capacity: A popularity-suitability perspective

4. Research on water resources bearing capacity of Wuhan based on multivariate linear regression model;Chen;J. Henan Polytech. Univ. Nat. Sci.,2017

5. Analysis of temporal-spatial patterns and influencing factors of urban ecosystem carrying capacity in urban agglomeration in the middle reaches of the Yangtze River;Shen;Acta Ecol. Sin.,2019

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