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中国相对发达城市的城市规模分布特征分析。

Analysis on urban scaling characteristics of China's relatively developed cities.

机构信息

School of Economics and Management, Beihang University, Beijing, China.

出版信息

PLoS One. 2020 Jul 29;15(7):e0236593. doi: 10.1371/journal.pone.0236593. eCollection 2020.

DOI:10.1371/journal.pone.0236593
PMID:32726337
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7390399/
Abstract

China is undergoing rapid urbanization, but the speed and stage of urban development are quite heterogeneous among different regions and city types. Understanding the urban scaling characteristics of China's relatively developed cities is important for addressing environmental and social challenges. Within the scope of 114 third-tier-and-above Chinese cities, the research calculate the scaling parameters of various urban development variables with respect to urban population and urban GRP in different city types based on urban scaling quantitative models. Also, univariate and multivariate regression analyses were performed on the factors affecting urban electricity consumption. The research results show that the urban scaling characteristics of Chinese cities differ between different types of cities, industrial cities show unique scaling features compared to commercial cities and mixed-economy cities. Additionally, urban electricity consumption is found to be closely related to urban population, urban construction land area and street lamp number. The results can help different types of cities make targeted policies and provide insights for reducing resource consumption during the urbanization process.

摘要

中国正在经历快速的城市化进程,但不同地区和城市类型的城市化速度和阶段存在很大差异。了解中国相对发达城市的城市规模特征对于应对环境和社会挑战至关重要。在 114 个三线及以上中国城市的范围内,本研究根据城市规模定量模型,计算了不同城市类型中各种城市发展变量相对于城市人口和城市 GRP 的规模参数。此外,还对影响城市用电量的因素进行了单变量和多变量回归分析。研究结果表明,不同类型城市的中国城市的城市规模特征存在差异,工业城市与商业城市和混合经济城市相比具有独特的规模特征。此外,城市用电量与城市人口、城市建设用地面积和路灯数量密切相关。研究结果可以帮助不同类型的城市制定有针对性的政策,并为减少城市化进程中的资源消耗提供思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b90/7390399/04ed93b1c92b/pone.0236593.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b90/7390399/9e77dbee2ed5/pone.0236593.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b90/7390399/caa530aa7650/pone.0236593.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b90/7390399/c388d5d0b0a4/pone.0236593.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b90/7390399/04ed93b1c92b/pone.0236593.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b90/7390399/9e77dbee2ed5/pone.0236593.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b90/7390399/caa530aa7650/pone.0236593.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b90/7390399/c388d5d0b0a4/pone.0236593.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b90/7390399/04ed93b1c92b/pone.0236593.g004.jpg

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