地理科学进展 ›› 2022, Vol. 41 ›› Issue (3): 361-370.doi: 10.18306/dlkxjz.2022.03.001
• 研究论文 • 下一篇
孙斌栋1,2,3(), 王言言1,2,3, 张志强1, 李琬1,2,3,*(
)
收稿日期:
2021-06-08
修回日期:
2021-09-22
出版日期:
2022-03-28
发布日期:
2022-05-28
通讯作者:
*李琬(1990— ),女,河南周口人,博士后,主要从事城市和区域空间结构研究。E-mail: lw1436@163.com作者简介:
孙斌栋(1970— ),男,河北阜平人,教授,博士生导师,主要从事城市地理与经济地理研究。E-mail: bdsun@re.ecnu.edu.cn
基金资助:
SUN Bindong1,2,3(), WANG Yanyan1,2,3, ZHANG Zhiqiang1, LI Wan1,2,3,*(
)
Received:
2021-06-08
Revised:
2021-09-22
Online:
2022-03-28
Published:
2022-05-28
Supported by:
摘要:
鉴于以往研究较少关注城市规模分布形态的规模差异性和城市规模分布演化与城市增长模式之间的关联,论文基于1953—2010年中国6次人口普查数据,选择了全部城市(包含地级市市区和县级市)和地级市(地级市市区)2种样本组,对中国城市位序规模分布的形态特征、演变趋势及其与Gibrat定律间的关系进行了实证分析。结果显示,中国的城市规模分布主体符合Zipf定律的线性分布,但两端即小城市和超大城市因规模不足而偏离线性分布,这一现象也得到全球各国证据的支持;从演化角度来看,中国城市规模分布在早期逐渐分散化并偏离Zipf定律,但从2000年开始转而向符合Zipf定律的方向回归,其中大城市率先在1990年就开始了转向,与这一阶段城市人口随机增长表现出耦合性,从而验证了Zipf定律和Gibrat定律的逻辑一致性。该发现对于促进中国城市规模分布高质量发展具有重要启示。
孙斌栋, 王言言, 张志强, 李琬. 中国城市规模分布的形态和演化与城市增长模式——基于Zipf定律与Gibrat定律的分析[J]. 地理科学进展, 2022, 41(3): 361-370.
SUN Bindong, WANG Yanyan, ZHANG Zhiqiang, LI Wan. The form and evolution of city size distribution and urban growth model in China: An analysis based on Zipf’s Law and Gibrat’s Law[J]. PROGRESS IN GEOGRAPHY, 2022, 41(3): 361-370.
表1
历次人口普查的城市位序规模分布帕累托指数
样本 | 指标 | 1953年 | 1964年 | 1982年 | 1990年 | 2000年 | 2010年 |
---|---|---|---|---|---|---|---|
所有城市 | 帕累托指数 | 0.876 | 0.933 | 0.927 | 1.05 | 1.243*** | 1.166*** |
标准误 | -0.097 | -0.103 | -0.085 | -0.07 | -0.068 | -0.064 | |
城市数量 | 163 | 165 | 236 | 455 | 663 | 656 | |
地级市 | 帕累托指数 | 0.935 | 1.130 | 1.090 | 1.250* | 1.268** | 1.169* |
标准误 | -0.140 | -0.183 | -0.144 | -0.129 | -0.111 | -0.098 | |
城市数量 | 89 | 76 | 114 | 188 | 263 | 287 |
表2
固定城市数量下的城市位序规模分布帕累托指数
城市规模 排位 | 1953年 | 1964年 | 1982年 | 1990年 | 2000年 | 2010年 |
---|---|---|---|---|---|---|
Top50 | 1.211 | 1.586 | 1.865 | 2.035 | 1.622 | 1.592 |
Top89 | 1.136 | 1.377 | 1.609 | 2.188 | 1.741 | 1.484 |
Top100 | 1.116 | 1.331 | 1.552 | 2.220 | 1.773 | 1.489 |
Top150 | 1.002 | 1.081 | 1.354 | 2.250 | 1.880 | 1.537 |
Top200 | — | — | 1.170 | 2.168 | 1.914 | 1.577 |
Top300 | — | — | — | 1.905 | 1.953 | 1.611 |
Top400 | — | — | — | 1.581 | 1.914 | 1.608 |
Top500 | — | — | — | — | 1.819 | 1.561 |
Top600 | — | — | — | — | 1.627 | 1.438 |
表4
城市增长模式回归结果(所有城市样本)
年均增长率 | 基期年份 | ||||
---|---|---|---|---|---|
1953 | 1964 | 1982 | 1990 | 2000 | |
g53_64 | -0.254*** | ||||
g53_82 | -0.322*** | ||||
g53_90 | -0.393*** | ||||
g53_00 | -0.404*** | ||||
g53_10 | -0.351*** | ||||
g64_82 | -0.147*** | -0.165*** | |||
g64_90 | -0.218*** | ||||
g64_00 | -0.245*** | ||||
g64_10 | -0.247*** | ||||
g82_90 | -0.153*** | -0.093*** | -0.228*** | ||
g82_00 | -0.292*** | ||||
g82_10 | -0.269*** | ||||
g90_00 | -0.100** | -0.061* | -0.109*** | -0.127*** | |
g90_10 | -0.130*** | ||||
g00_10 | 0.020 | 0.030 | 0.025 | 0.022 | 0.021 |
表5
城市增长模式回归结果(地级市样本)
年均增长率 | 基期年份 | ||||
---|---|---|---|---|---|
1953 | 1964 | 1982 | 1990 | 2000 | |
g53_64 | -0.203*** | ||||
g53_82 | -0.266*** | ||||
g53_90 | -0.314*** | ||||
g53_00 | -0.247*** | ||||
g53_10 | -0.238*** | ||||
g64_82 | -0.121*** | -0.138*** | |||
g64_90 | -0.149*** | ||||
g64_00 | -0.072* | ||||
g64_10 | -0.061 | ||||
g82_90 | -0.096* | -0.020 | -0.107** | ||
g82_00 | -0.133 | ||||
g82_10 | -0.202* | ||||
g90_00 | 0.037 | 0.056 | 0.013 | -0.020 | |
g90_10 | -0.066 | ||||
g00_10 | 0.012 | 0.062** | 0.012 | -0.010 | -0.021 |
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