Characterizing the coordination and disequilibrium pattern of urban population, economics and urban built-up area in Eastern and Mid-China region

doi:10.3969/j.issn.1004-9479.2021.01.2019400

Abstract

Abstract:

Based on statistic and land use dataset of 261 prefectural cities in Eastern and Mid-China region in China from 2000 to 2015, this paper analyzed the spatial agglomeration and disequilibrium pattern change of urban population, GDP and urban built-up area and revealed the coordination degree between population urbanization rate and land urbanization rate by using spatial autocorrelation model, variation coefficient and the coupling model of three factors. The results show that: (1) the Moran's I value of urban population, GDP and construction land are all positive and the value in 2015 are larger than the value in 2000, implying an increased tendency of spatial cluster pattern from 2000 to 2015; (2) the variation coefficient of urban population and GDP per capita decreased from 1.38 and 0.91 in 2000 to 0.96 and 0.70 in 2015 respectively, while GDP per land increased from 1.32 to 1.77, which indicates the difference of urban population density and GDP per capita decreased but the difference of GDP per land increased in the same period; (3) the elastic coefficient of urban land increasing scale of 171 prefectural cities are lower than 1.12 and urban land per capita are lower than 115m²,which shows that land urbanization rate and scale are reasonable and can be controlled for most of cities, but economic outputs of urban land are still relatively low; (4) urban population, GDP and urban land are harmonious in both time spans for more than 90% of the prefectural cities. This paper will provide references and bases for formulating ordered, reasonable and balanced policies on the development and utilization of national land space, as well as solving urban spatial pattern optimization problems.

Key words: urban population, economy, urban land, spatial cluster, disequilibrium

摘要：

基于2000、2015年中国东中部地区261个地级市统计与土地利用数据，运用空间自相关模型，变异系数和三元协调度模型分析其城市人口、GDP和城市建设用地的空间集聚态势和非均衡变化过程，揭示人口城市化与土地城市化的协调程度。结果显示：（1）城市人口、GDP和建设用地的Moran’s I指数均为正值且2015年的值大于2000年的值，显示出明显的空间集聚特征，且在2000—2015年集聚特征不断加强；（2）城市人口密度和人均GDP的变异系数分别从2000年的1.38和0.91下降到2015年的0.96和0.70，地均GDP从1.32上升到1.77，表明城市人口密度和地均GDP的差异在逐步减小，但地均GDP的不均衡性却在增大；（3）2015年，共有171个地级市城市用地规模增长弹性系数小于1.12且人均城市用地小于115m²，但有104个地级市地均GDP在1000元/m²以下，表明虽然绝大部分地级市城市化规模和速率都在可控范围之内，城市用地经济产出仍然相对较低；（4）90%以上地级市的城市人口、GDP和城市建设用地三者在两个研究时间段内处于协调发展状态。

关键词: 城市人口, 经济, 城市建设用地, 空间集聚, 非均衡特征

Kehao ZHOU, Ronghui TAN. Characterizing the coordination and disequilibrium pattern of urban population, economics and urban built-up area in Eastern and Mid-China region[J]. World Regional Studies, 2021, 30(1): 90-100.

周克昊, 谭荣辉. 东中部地区城市人口、经济与城市建设用地的非均衡与协调性分析[J]. 世界地理研究, 2021, 30(1): 90-100.

Figures/Tables 9

Tab.1 The global Moran’s I change of urban population, GDP and urban land in China in 2000 and 2015

参数	2000年			2015年
参数	城市人口	GDP	建设用地	城市人口	GDP	建设用地
Moran’s I	0.029	0.061	0.232	0.056	0.161	0.290
E(I)	-0.0038	-0.0038	-0.0038	-0.0038	-0.0038	-0.0038
Mean	-0.0040	-0.0035	-0.0035	-0.0040	-0.0001	-0.0024
SD	0.0393	0.0383	0.0379	0.0371	0.0417	0.0404
Z-value	0.8304	1.6894	6.2189	1.6273	3.8734	7.2518
p-value	0.191	0.074	0.001	0.070	0.005	0.001

Fig.1 LISA of population, GDP and constuction land in study area in 2000 and 2015

Tab.2 Variation coefficients of urban population density, per capital GDP and GDP per urban land in 2000 and 2015

项目	2000	2015
城市人口密度	1.38	0.96
人均GDP	0.91	0.70
地均GDP	1.32	1.77

Tab.3 The change of variation coefficients of urban population density, per capital GDP and GDP per urban land in the three urban agglomeration regions in China in 2000 and 2015

项目

珠江三角洲城市群

2000 2015

长江三角洲城市群

2000 2015

京津冀城市群

2000 2015

Fig.2 The urban land elasticity coefficients based on urban population and GDP of 261 cities in 2000 and 2015

Fig.3 The per capital urban land and urban land elasticity coefficients of 261 cities in 2000 and 2015

Fig.4 The GDP per urban land and urban land elasticity coefficients of 261 cities in 2000 and 2015

Fig.5 Spatial distribution of population,GDP and urban land coordination degree of 261 cities in 2000,2015

Fig.6 The change of population,GDP and urban land coordination degree of 261 cities in 2000-2015

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