西南经济核心区中心城市城镇化结构质量比较分析——以成都、重庆为例

doi:10.13249/j.cnki.sgs.2021.06.011

摘要/Abstract

摘要：

运用耦合协调模型和基于主成分的多元线性回归法，对2005—2017年间中国西南经济核心区中心城市成都和重庆的城镇化结构质量及其驱动力展开对比分析。结果表明：① 重庆与成都的城镇化结构质量整体水平较高且在持续增长中；成都的城镇化结构质量明显高于重庆，这与因地形、发展阶段、城市定位而限定的重庆“主城区现代化大都市+非主城区广大农村地域”、成都现代化都市圈的空间结构组织形式密切相关；② 城镇化驱动因子呈现多元化、阶段性与差异性特征，行政力和市场力起主要作用；其次是内源力和外向力，但外向力正处在一个不断弱化的过程，反映中国城镇化发展的内生性特征；③ 基于取平均值的城镇化子系统及其系统耦合协调性分析，可有效避免当前城镇化耦合分析中因各子系统指标选取个数不等而带来的失真、不准确问题。

关键词: 城镇化结构质量, 经济核心区, 均方差赋权法, 成渝双城经济圈

Abstract:

The quality of urbanization structure based on the orderly coordination and coupling of internal systems is an important basic component of urbanization quality, which should be included in the existing urbanization quality analysis framework that based on urbanization development benefits. The former is called the foundation and supporting urbanization Quality I, the latter is called the benefit of urbanization quality II, which is mutually causal. Based on the perspective of urbanization structure quality, this article uses the improved coupling coordination model to comparative analysis the urbanization structure qualities and their driving forces between Chongqing and Chengdu that are the core cities of Southwest Economic Core Area (Chengdu-Chongqing urban agglomeration area) from 2005 to 2017, in order to provide a reference for the integrated construction of the “Chengdu-Chongqing Twin Cities Economic Circle”. The results show: 1) The qualities of urbanization structure in Chongqing and Chengdu are relatively high, and their are continuously in growing, and Chengdu ’s urbanization structure quality is significantly higher than that of Chongqing. Which is closely related to the spatial organization structures formed by topography, development stage, and urban positioning, of Chongqing ’s “modern metropolis in the main urban area + vast rural areas in non-main urban areas” spatial organization structure and Chengdu’s modern metropolitan spatial organization structure. 2) The driving factors of urbanization show the characteristics of diversification, stages and differences. In which, the administrative force and market force played important roles during the period, and followed by the internal forces and the external forces, while the external forces in the whole process is continuous weakening, reflecting that China’s urbanization is an endogenous development progress. 3) Based on the average values of the urbanization subsystem and its system coupling and coordination analysis, can effectively avoid the distortion and inaccuracy caused by the differences in index selection of each urbanization subsystem. Finally, this article puts forward some suggestions for the urbanization sustainable of the two cities.

Key words: urbanization structure quality, economic core area, mean square deviation weighting method, Chengdu-Chongqing economic core area

中图分类号:

F293.1/K928.5

孙平军, 罗宁. 西南经济核心区中心城市城镇化结构质量比较分析——以成都、重庆为例[J]. 地理科学, 2021, 41(6): 1019-1029.

Sun Pingjun, Luo Ning. Comparative Analysis on the Quality of Urbanization Structure of Central Cities in Southwest Economic Core Area of China: Taking Chengdu-Chongqing as Examples[J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(6): 1019-1029.

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目标层	准则层	准则层权重	指标层	指标权重
城镇化水平综合评价指标体系	人口城镇化	0.252	常住人口城镇化率/%	0.057
			二三产业就业人员比重/%	0.062
			就业率/%	0.073
			二三产业产值占总产值比重/%	0.048
	经济城镇化	0.245	人均GDP/（元/人）	0.055
			城镇居民可支配收入/元	0.056
			二三产业GDP密度/（万元/km²）	0.059
			人均社会消费品零售总额/（元/人）	0.057
	空间城镇化	0.252	建成区面积占土地总面积比重/%	0.058
			建成区绿化覆盖率/%	0.048
			人均道路面积/（km²/人）	0.052
			城市道路网密度/（ km/10³ km²）	0.054
			人口建设用地面积/（km²/人）	0.085
	社会城镇化	0.251	人均用电量/（°/人）	0.055
			每万人卫生机构床位数/（张/万人）	0.061
			每万人普通高中专任教师数/（人/万人）	0.056
			每百人公共图书馆藏书量/（册/100人）	0.064

年份	重庆市				成都市
年份	人口S₁	经济S₂	空间S₃	社会S₄	人口S₁	经济S₂	空间S₃	社会S₄
2005	0.006	0.006	0.014	0.006	0.033	0.019	0.038	0.032
2006	0.008	0.009	0.017	0.008	0.036	0.022	0.039	0.037
2007	0.010	0.010	0.020	0.009	0.040	0.025	0.041	0.038
2008	0.013	0.013	0.023	0.010	0.042	0.028	0.043	0.032
2009	0.016	0.015	0.023	0.012	0.045	0.033	0.046	0.040
2010	0.019	0.018	0.024	0.014	0.047	0.036	0.048	0.046
2011	0.022	0.020	0.023	0.020	0.050	0.040	0.048	0.048
2012	0.026	0.023	0.026	0.023	0.051	0.044	0.049	0.052
2013	0.028	0.026	0.026	0.024	0.053	0.049	0.048	0.052
2014	0.031	0.028	0.027	0.025	0.055	0.051	0.043	0.052
2015	0.034	0.031	0.028	0.026	0.059	0.052	0.045	0.050
2016	0.037	0.034	0.030	0.026	0.058	0.051	0.045	0.044
2017	0.039	0.036	0.032	0.030	0.059	0.055	0.047	0.048

年份	耦合度C		协调指数T		耦合协调度D
年份	重庆	成都	重庆	成都	重庆	成都
2005	0.926	0.971	0.084	0.294	0.279	0.535
2006	0.951	0.974	0.111	0.320	0.324	0.559
2007	0.947	0.982	0.129	0.346	0.350	0.583
2008	0.956	0.985	0.150	0.350	0.379	0.587
2009	0.967	0.991	0.167	0.398	0.402	0.628
2010	0.984	0.994	0.186	0.431	0.428	0.654
2011	0.998	0.997	0.212	0.454	0.460	0.672
2012	0.999	0.998	0.243	0.483	0.492	0.694
2013	0.998	0.999	0.257	0.495	0.507	0.704
2014	0.997	0.996	0.274	0.491	0.523	0.699
2015	0.994	0.996	0.291	0.504	0.538	0.709
2016	0.992	0.994	0.313	0.485	0.557	0.694
2017	0.994	0.996	0.337	0.514	0.579	0.716

阶段	R²		调整R²		F值		标准误差		t值
阶段	重庆	成都	重庆	成都	重庆	成都	重庆	成都	重庆	成都
2005—2017年	0.981	0.949	0.980	0.944	581.589	204.458	0.022	0.035	24.116	14.299
2005—2010年	0.975	0.986	0.969	0.982	158.087	272.791	0.042	0.030	12.573	16.516
2011—2017年	0.932	0.792	0.918	0.750	68.050	19.045	0.064	0.121	8.249	4.364

阶段	双尾显著性概率		标准系数—重庆				标准系数—成都
阶段	重庆	成都	X_xz	X_sc	X_wx	X_ny	X_xz	X_sc	X_wx	X_ny
2005—2017年	0.000	0.000	0.141	0.141	0.134	0.131	0.130	0.129	0.127	0.129
2005—2010年	0.000	0.000	0.143	0.144	0.139	0.128	0.127	0.129	0.127	0.126
2011—2017年	0.000	0.000	0.154	0.152	0.112	0.157	0.173	0.173	0.113	0.156