转型期京津冀城市群空间扩展格局及其动力机制研究——基于夜间灯光数据方法

doi:10.11821/dlxb201612007

摘要/Abstract

摘要：

针对中西方城市群空间扩展路径研究的争论,以京津冀城市群为例,运用夜间灯光数据,采取扩展强度指数、空间关联模型、多维驱动力分析模型,定量揭示了城市群时空扩展路径及其动力机制。结果表明：① 1992-2012年,京津冀城市群时空扩展呈现以京津唐为核心的中心集聚扩展模式,保定—衡水—石家庄之间的“三角地带”成为城市群空间扩展的冷点区;② 城市群空间扩展虽然已经出现了扩散势头,但向心集聚的惯性作用力依然强大;③ 城市群时空扩展的动力机制表现出以市场力为主要驱动因子的特征,行政力、外向力和内源力对城市群空间扩展的影响作用依次递减,从城市群空间扩展的驱动力演化趋势看,市场力、行政力、外向力的影响呈现上升趋势,而内源力的影响系数则呈现下降趋势。最后,提出降低行政干预、构建市场主导机制、强化内外双向开放、推动产业升级政策建议,促进城市群空间结构持续优化。

关键词: 京津冀城市群, 时空扩展, 动力机制, 夜间灯光数据

Abstract:

Urban spatial expansion has been research hotspot of urban geography for a long time. However, urban spatial progress and its driving forces showed diversified state under the context of different political systems and different development phases in the world. For example, there are debates on metropolitan expansion path between Western countries and China. One view advocated that metropolitan spatial expansion showed a trend from clustered to dispersed under the role of scale-economy. Another view found that above theory could not explain metropolitan spatial expansion progress in developing countries, such as China and India. In these metropolitan regions, rapid urban spatial expansion existed in "urban-rural integration" areas, not central big cities of metropolitan regions. Thus, it was different from Western developed countries due to particular political and economic factors in developing countries. In order to clarify metropolitan spatial pattern in a transitional period from planned economy to market economy, we utilized nighttime light data to analyze Beijing-Tianjin-Hebei metropolitan area from 1992 to 2012 as a case. A series of measurement methods has been used in the study, such as expansion intensity index, spatial correlation model and multi-dimensional model. The results are as follows: (1) Beijing, Tianjin, Tangshan were hotspot regions of metropolitan expansion during the whole research period. "Triangle region" among Baoding-Tianjin-Hebei were coldspot regions of metropolitan expansion. (2) Although metropolitan expansion has showed a dispersed trend, centralized powers are still strong in the progress of metropolitan development. (3) Metropolitan driving forces showed a diversified state. Market power was the main driving forces, followed by administration power, exogenous power and endogenous power. Market power, administration power and exogenous power has showed an upward trend. However, endogenous power has showed a downward trend. (4) We put forward some policy suggestions to optimize metropolitan spatial structure, such as reducing administrative intervention, building market-driven mechanism, strengthening internal and external two-way reform and promoting industrial upgrade.

Key words: Beijing-Tianjin-Hebei metropolitan area, spatial-temporal expansion, driving dynamics, nighttime light data

王利伟, 冯长春. 转型期京津冀城市群空间扩展格局及其动力机制研究——基于夜间灯光数据方法[J]. 地理学报, 2016, 71(12): 2155-2169.

Liwei WANG, Changchun FENG. Spatial expansion pattern and its driving dynamics of Beijing-Tianjin-Hebei metropolitan region: Based on nighttime light data[J]. Acta Geographica Sinica, 2016, 71(12): 2155-2169.

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	1992-1997年	1997-2002年	2002-2007年	2007-2012年
京津冀城市群	0.18	0.16	0.20	0.58
中心城市(地级市)	1.14	0.91	1.02	2.13
次中心城市(县城)	0.06	0.06	0.09	0.38

京津冀城市群	回归模型	R²	F	T统计量值	双尾显著性概率（Sig）
总进程	Y=0.275X₁+0.276X₂+0.274X₃+0.208X₄	0.966	545.918	23.365	0.000
阶段I	Y=0.262X₁+0.259X₂+0.192X₃+0.236X₄	0.866	58.227	7.631	0.000
阶段II	Y=0.300X₁+0.301X₂+0.300X₃+0.101X₄	0.927	113.708	10.663	0.000
北京
总进程	Y=0.249X₁+0.246X₂+0.247X₃+0.227X₄	0.939	290.110	17.033	0.000
阶段I	Y=0.271X₁+0.266X₂+0.230X₃+0.239X₄	0.921	105.026	10.248	0.000
阶段II	Y=0.235X₁+0.234X₂+0.231X₃+0.211X₄	0.875	63.195	7.950	0.000
天津
总进程	Y=0.257X₁+0.257X₂+0.257X₃+0.229X₄	0.963	499.617	22.352	0.000
阶段I	Y=0.275X₁+0.270X₂+0.209X₃+0.279X₄	0.965	245.264	15.661	0.000
阶段II	Y=0.259X₁+0.257X₂+0.258X₃+0.227X₄	0.964	237.774	15.420	0.000
河北
总进程	Y=0.254X₁+0.257X₂+0.252X₃+0.224X₄	0.943	311.765	17.657	0.000
阶段I	Y=0.243X₁+0.238X₂+0.157X₃+0.235X₄	0.805	37.097	6.091	0.000
阶段II	Y=0.249X₁+0.249X₂+0.248X₃+0.215X₄	0.921	104.688	10.232	0.000