2006—2015年湖北省城市相对收缩时空变化

doi:10.18306/dlkxjz.2020.07.004

Abstract

Abstract:

Cities shrinking is a major challenge for the new urbanization in China. Moreover, "flowing space" effect increasingly intensified relative city shrinkage in the process of socioeconomic transition. The Chinese central government has focused on transition of the shrinking cities with small and medium size. Understanding of relative city shrinkage, however, is currently a rudimentary and subjective issue. Hubei Province is a typical area with dense small and medium-sized cities in China. Based on these considerations, this article first presented a diagnostic framework of city relative shrinkage. Then, taking Hubei as a study area, the dynamic patterns and causes of city relative shrinkage between 2006 and 2015 were analyzed using the quantitative diagnostic method and a regression model of panel data. The results indicate that 27 cities showed relative shrinkage, which accounted for 75% of the cities in Hubei Province. Moreover, 18 cities showed strong relative shrinkage. Overall, proportion of relative shrinkage showed a spatial pattern of strong in the east and west and weak in the middle. "Flowing space" has a significant impact on the shrinkage of small and medium-sized cities. From the period of the 11th to the 12th Five-year Plan, Wuhan and Xiangyang showed continued growth. Meanwhile, cities of relative shrinkage increased from 21 to 24. Strategies of urban development presented by the 11th and the 12th five-year plans to some degree promotedcity development in western Hubei. However, within the Wuhan metropolitan area and its surrounding areas of 150 km radius, the development of large, medium, and small cities was still imbalanced. Industrial space expansion and improvement of urban construction, maintenance, and management levels played important and positive roles in controlling the relative shrinkage. Finally, suggestions on promoting coordinated development of cities in Hubei, implications for controlling the shrinkage of small and medium-sized cities, and methodology of relative city shrinkage research were discussed.

Key words: city shrinkage, city system, Hubei Province

ZHAO Qinglin, ZHANG Weina, LI Xinyi, LI Dianxin, SONG Xiaoqing. Spatiotemporal change of relative city shrinkage in Hubei Province, 2006-2015[J].PROGRESS IN GEOGRAPHY, 2020, 39(7): 1106-1116.

Figures/Tables 11

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References 43

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类型	R_i	LR_i
强相对扩张型	R_i≥ 0.2	LR_i≥ 0.2
弱相对扩张型	0.2>R_i>0	0.2>LR_i>0
转型扩张型	R_i<0	LR_i>0
强相对收缩型	R_i≤ -0.2	LR_i≤ -0.2
弱相对收缩型	-0.2<R_i<0	-0.2<LR_i<0
转型收缩型	R_i>0	LR_i<0

变量	变量含义	变量解释
x_IIA	产业用地面积 (km²)	考虑到2012年后城市建设用地分类体系变化^[25],从城市建设用地面积中扣除居住、公用设施、交通、道路广场、绿地、特殊用地等用地面积后,形成产业用地面积。该指标反映城市产业空间规模。一般而言,产业空间规模扩大理应与城市就业增加呈正相关关系,进而导致城市人口密度上升,反之亦然^[34,35]
x_GABA	建成区绿化覆盖面积 (hm²)	该指标反映城市人居环境质量。一般而言,人居环境改善理应吸引城市人口集聚,进而导致城市人口密度上升,反之亦然^{[36,37,38,39]}
x_PCLS	人均居住用地面积 (m²/人)	该指标反映城市居住水平。一般而言,人均居住用地面积增长理应有助于吸引城市人口集聚,进而导致城市人口密度上升,反之亦然^[40,41]
x_LMCI	地均城市建设维护资金投入 (万元/km²)	该指标反映城市维护建设管理水平。一般而言,指标值越大,城市维护建设管理水平越高,越有助于吸引城市人口集聚,进而导致城市人口密度上升^[42,43]

变量	最大值	最小值	平均值	中值	标准差	偏度	峰度	样本数
y	670.50	23.11	159.33	87.98	145.90	1.46	4.34	360
x_IIA	261.25	1.63	14.82	7.60	28.23	5.94	42.69	360
x_GABA	334.36	0.67	18.47	9.53	36.67	6.07	43.26	360
x_PCLS	924.60	12.77	183.02	155.64	143.20	1.50	6.60	360
x_LMCI	165.14	0.26	9.05	6.20	12.12	7.11	81.26	360

城市类型	150 km圈层区域		150~300 km圈层区域		300 km外圈层区域		总计
城市类型	数量/个	占该区域城市比重/%	数量/个	占该区域城市比重/%	数量/个	占该区域城市比重/%	数量/个	占全省城市比重/%
强相对扩张型	3	16.67	1	7.69	0	0	4	11.11
弱相对扩张型	0	0	1	7.69	0	0	1	2.78
转型扩张型	2	11.11	2	15.38	0	0	4	11.11
强相对收缩型	10	55.56	5	38.46	3	60.00	18	50.00
弱相对收缩型	3	16.67	4	30.77	2	40.00	9	25.00
转型收缩型	0	0	0	0	0	0	0	0

城市类型	150 km圈层区域		150~300 km圈层区域		300 km外圈层区域		总计
城市类型	数量/个	占该区域城市比重/%	数量/个	占该区域城市比重/%	数量/个	占该区域城市比重/%	数量/个	占全省城市比重/%
强相对扩张型	3	16.67	2	15.38	0	0	5	13.89
弱相对扩张型	4	22.22	4	30.77	0	0	8	22.22
转型扩张型	1	5.56	1	7.69	0	0	2	5.56
强相对收缩型	8	44.44	1	7.69	1	20.00	10	27.78
弱相对收缩型	2	11.11	5	38.46	4	80.00	11	30.56
转型收缩型	0	0	0	0	0	0	0	0

Spatiotemporal change of relative city shrinkage in Hubei Province, 2006-2015

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变量	系数	标准误	t值	P值
x_IIA	0.7915	0.3368	2.3502	0.0194
x_GABA	-0.7797	0.2107	-3.7011	0.0003
x_PCLS	-0.4328	0.0402	-10.7747	0
x_LMCI	0.2534	0.1485	1.7072	0.0889
常数	216.9173	15.3457	14.1354	0
AR(1)	0.6523	0.1259	5.1795	0
R²=0.9235; Durbin-Watson统计值=1.8237

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