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地理研究    2017, Vol. 36 Issue (1): 97-108     DOI: 10.11821/dlyj201701008
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
京津冀地区经济发展冷热点格局演化及其影响因素
刘浩1(),马琳2,李国平1()
1. 北京大学政府管理学院,北京 100871
2. 北京大学城市与环境学院,北京 100871
Pattern evolution and its contributory factor of cold spots and hot spots of economic development in Beijing-Tianjin-Hebei region
LIU Hao1(),MA Lin2,LI Guoping1()
1. School of Government, Peking University, Beijing 100871, China
2. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
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摘要 

为了探讨京津冀地区经济发展失衡,引入DMSP/OLS夜间灯光构建GDP指数,利用优化的热点分析和时空模式挖掘识别经济发展的格局演化,以SLM和SEM模型从自然环境、基础设施及区域开发等方面量化失衡因素。结果表明:① 区域经济发展趋于波动性集聚,经济发展呈明显的京津市区、京津郊区和河北区县城区、河北偏远县乡等3种类型,而京津市区和郊区之间、京津市域和河北省域之间都存在显著的“虹吸效应”所诱发的发展断崖。② 持续的热点、振荡的热点和振荡的冷点是经济发展冷热点的主要演化模式。经济发展热点自中心城区至远郊呈同心圆圈层式弱化,而无明显圈层变化的冷点集中连片地广布在河北乡村。③ 经济发展与自然环境、基础设施和区域开发有复杂非线性关系,经济发展繁荣地区(热点)多受惠于基础设施和区域开发及行政区划的整体优势,而合适的海拔条件次之。经济发展落后地区(冷点)总体受制于坡度条件和基础设施及区域开发的总体劣势。

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刘浩
马琳
李国平
关键词 经济失衡冷热点格局分析时空模式挖掘DMSP/OLS夜间灯光京津冀 
Abstract

The rapid and imbalanced economic development in the Beijing-Tianjin-Hebei region has widened the gap between Beijing-Tianjin and surrounding areas since the 1990s, therefore, it is an important social consensus to achieve coordinated development. In this paper, we analyzed the imbalanced economic development in the Beijing-Tianjin-Hebei region by proposing a GDP Index using the DMSP/OLS nighttime light data to represent the regional economic development. Then the Getis-Ord General G, Global Moran's I and Optimized Hot Spot Analysis were applied to qualify the spatial pattern of the GDP Index. Third, Space Time Pattern Mining, Spatial Lag Model (SLM) and Spatial Error Model (SEM) were employed to identify the dynamics of the spatial pattern and evaluate the effects of four factors, which were natural environment (elevation and gradient), infrastructure (road network), policy (land use cover) and administrative division (urban or rural area), to the imbalance in the economy, respectively. Results show that: (1) the study area can be divided into three groups based on the level of economic development: urban Beijing-Tianjin, rural Beijing-Tianjin and urban Hebei, and rural Hebei. And there are two economic development gaps caused by Siphon Effect between urban and rural Beijing-Tianjin, and Beijing-Tianjin and Hebei, which is different from the previous view that only one economic development gap between Beijing-Tianjin and Hebei. (2) The dynamics of spatial pattern of economic development are mainly constant hot spot, fluctuant hot spot and fluctuant cold spot. The degree of hot spot, which is mostly in Beijing-Tianjin, decreases from urban center to rural area as concentric circles. In contrast, the majority of cold spots, which have no obvious ring structure, are located in rural Hebei. (3) The economic development in the Beijing-Tianjin-Hebei region has non-linear relationship with natural environment, infrastructure, policy and administrative division. In the hot spot region where the economy is more developed, all four factors, especially infrastructure, policy and administrative division, are positively correlated with economic development. However, high gradient, insufficient infrastructure and improper policy limit the economic development in the place with less developed economy, i.e. the cold spot region. This research may be helpful to understand the process and current conditions of economic development in the Beijing-Tianjin-Hebei region, and useful to realize coordinated development in this region.

Key wordseconomic imbalance    hot and cold spot    space time pattern mining    DMSP/OLS nighttime light    Beijing-Tianjin-Hebei region
收稿日期: 2016-05-25      出版日期: 2017-01-22
基金资助:国家自然科学基金项目(41671120,41371005)
引用本文:   
刘浩, 马琳, 李国平 . 京津冀地区经济发展冷热点格局演化及其影响因素[J]. 地理研究, 2017, 36(1): 97-108.
LIU Hao, MA Lin, LI Guoping . Pattern evolution and its contributory factor of cold spots and hot spots of economic development in Beijing-Tianjin-Hebei region[J]. GEOGRAPHICAL RESEARCH, 2017, 36(1): 97-108.
链接本文:  
http://www.dlyj.ac.cn/CN/10.11821/dlyj201701008      或      http://www.dlyj.ac.cn/CN/Y2017/V36/I1/97
模式名称 ID 定义
非显著模式 0 无统计显著性
新增的热点 1 最后时间步长成为统计显著性热点,之前从未是统计显著性热点
连续的热点 2 至多90%条柱是统计显著性热点,最后热点运行之前均非统计显著性热点,带有最后时间步长间隔的统计显著性热点单次未中断运行
加强的热点 3 90%时间步长间隔(含最后时间步长)已是统计显著性热点,每个时间步长中数量较小的聚类强度总体增加,且增加有统计显著性
持续的热点 4 90%时间步长间隔已是统计显著性热点,计数聚类强度无明显增减趋势
渐少的热点 5 90%时间步长间隔(含最后时间步长)已是统计显著性热点,每个时间步长中数量较小的聚类强度总体减少,且减少有统计显著性
分散的热点 6 至多90%时间步长间隔已是统计显著性热点,热点断断续续,时间步长间隔均非统计显著性冷点
振荡的热点 7 至多90%时间步长间隔已是统计显著性热点,统计显著性热点的最后时间步长间隔有一段之前为统计显著性冷点的历史
历史的热点 8 至少90%时间步长间隔已是统计显著性热点,最近时段不是热点
新增的冷点 -1 最后时间步长成为统计显著性冷点,之前从未是统计显著性冷点
连续的冷点 -2 至多90%条柱为统计显著性冷点,最后冷点运行之前均非统计显著性冷点,带有最后时间步长间隔的统计显著性冷点单次未中断运行
加强的冷点 -3 90%时间步长间隔(含最后时间步长)已是统计显著性冷点,每个时间步长中数量较小的聚类强度总体增加,且增加有统计显著性
持续的冷点 -4 90%时间步长间隔已是统计显著性冷点,计数聚类强度无明显增减趋势
渐少的冷点 -5 90%时间步长间隔(含最后时间步长)已是统计显著性冷点,每个时间步长中数量较小的聚类强度总体减少,且减少有统计显著性
分散的冷点 -6 至多90%时间步长间隔已是统计显著性冷点,冷点断断续续,时间步长间隔均非统计显著性热点
振荡的冷点 -7 至多90%时间步长间隔已是统计显著性冷点,统计显著性冷点的最后时间步长间隔有一段之前为统计显著性热点的历史
历史的冷点 -8 至少90%时间步长间隔已是统计显著性冷点,最近时段不是冷点
Tab. 1  时空模式挖掘的模式类型及其定义
Fig. 1  1992-2013年京津冀地区的全局空间格局分析
Fig. 2  1992-2013 年京津冀地区经济发展的冷点和热点发生概率
Fig. 3  1992-2013年京津冀地区经济发展的热点和冷点的时空模式挖掘分析
Fig. 4  1992-2013年京津冀地区经济发展冷热点概率的影响因素关系
变量 Spatial Lag + Error Spatial Error Spatial
Lag
No Spatial Regression
Wy -0.1242 0.0960
(0.1671) (0.0618)
x1 -27.7426** -35.2358*** -50.5146*** -56.7650***
(13.8757) (13.1181) (12.2737) (11.6282)
x2 -6.1954 -2.4066 11.4067 13.0428*
(7.4991) (7.5936) (7.9100) (7.8612)
x3 140.7602*** 135.9657*** 118.4495*** 119.1758***
(8.5950) (8.4397) (8.2748) (8.2844)
x4 -108.6509*** -107.3908*** -102.1181*** -102.3979***
(3.9867) (3.9582) (2.9524) (2.9551)
x5 12.5488*** 12.8802*** 13.6537*** 13.9638***
(1.0515) (1.0318) (0.9793) (0.9614)
常数项 3.5869 0.2409 6.7111 11.6018
(13.8509) (8.9957) (8.4688) (7.8842)
Lambda 0.8966***
(0.0813)
R2 0.3143 0.3126 0.3169 0.3140
样本数 4841 4841 4841 4841
Tab. 2  京津冀地区经济发展热点的影响因素分析
变量 Spatial Lag+Error Spatial Error Spatial
Lag
No Spatial Regression
Wy 1.5523*** 1.5601***
(0.0859) (0.0906)
x1 -0.5403 -28.8215*** -1.8767 3.3874**
(0.8501) (4.0991) (1.1818) (1.5649)
x2 -14.5886*** -9.4589*** -13.5263*** 4.5093**
(2.1382) (2.6640) (1.9138) (2.1959)
x3 -11.8277*** 26.6048*** -12.0994*** 21.5347***
(1.9848) (6.0791) (2.2825) (1.6195)
x4 5.9853*** -4.6857* 4.2490*** -9.8031***
(1.5510) (2.7697) (1.6159) (1.9116)
x5 0.4117 -2.0965** -0.0306 -1.3350
(0.2996) (0.8802) (0.4497) (0.6077)**
常数项 -5.8361*** 6.0934 -4.2922** 11.6047***
(1.5766) (5.7726) (1.8021) (2.1216)
Lambda -0.8340*** 0.9610***
(0.0681) (0.0134)
R2 0.5730 0.0079 0.5734 0.0312
样本数 6525 6525 6525 6525
Tab. 3  京津冀地区经济发展冷点的影响因素分析
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