基于ESDA方法的黄土高原地区经济发展格局及其演化特征分析
Exploratory Spatial Data Analysis of the Distribution and Evolution of Economic Growth in Loess Plateau Region during 1990-2007
查看参考文献23篇
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文摘
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探索式空间数据分析(ESDA)方法可以很好地揭示区域经济增长特征及其与空间环境的关系，是深入了解和把握区域经济的空间分布和演化规律的有效手段之一。本文基于ESDA方法，利用黄土高原地区284个县市级行政单元1990、2000和2007年3期的人均GDP数据，分析了黄土高原地区经济增长的空间分布格局和动态演变特征，验证了ESDA方法在揭示社会经济发展空间分异和演变规律方面的作用。分析结果表明：黄土高原地区的人均GDP分布表现出了显著的高值和低值集聚(空间正相关)特征，且其空间分异状况具有一定的稳定性；目前黄土高原地区的经济增长仍以不平衡增长为主，短期内高水平地区高速增长趋势仍将继续，而低水平地区很难实现经济增长的快速提高；黄土高原地区存在着常态化的城市产业集聚推动型和机遇性的资源开发拉动型两种增长类型，后者对人均GDP水平的拉动效应更强，然而却容易造成产业畸形单一，经济增长缺乏可持续性、稳定性和抗干扰性。 |
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其他语种文摘
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Exploratory spatial data analysis(ESDA)can finely reveal the characteristics of economic growth of a region in relation to its geographical environment,and therefore is a powerful tool to help us better understanding the spatial-temporal dynamics of the distributions of economic factors in each region.The study of the spatial distribution of per capita GDP of 284 counties in the Loess Plateau region since 1990 using ESDA proved its role in investigating the rules of distribution and evolution of social or economic development.And several points can be highlighted.First,ESDA reveals significant positive global and local spatial autocorrelation of per capita GDP in the Loess Plateau region throughout the period 1990-2007.Second,the analysis of scatter plots and local indicators of spatial association(LISA)over the period indicates that there are four significant regional clusters persisting over time.The first is a significant High-High (HH)type of clustering,located mainly in Inner Mongolia-north Ningxia-north Shaanxi in the Loess Plateau region.The other HH forms of clustering are located in Northwest Henan and Southeast Shanxi.The largest areas of low-low(LL)type of clustering are primarily located in the south of Gansu,the south of Ningxia and east of Gansu.Third,the comparative analysis of per capita GDP and average growth rates of per capita GDP suggests that the development of per capita GDP in the Loess Plateau region is mainly in a way of polarized growth in the past 20 years.And it is predictable that this trend will persist,and even get stronger in the near future.Until now there are no characteristics of β-convergence detected in the Loess Plateau region.Finally,the stable spatial patterns in Loess Plateau region indicate two kinds of economic growth modes.One is the normal economic growth pushed by industrial agglomeration,and the other is the opportunistic economic growth pulled by energy/resources exploring.The latter is far more powerful in promoting the level of per capita GDP,but always with problems of singleness of industrial type and lack of stability,sustainability and interference immunity during its working process in pulling economic growth. |
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来源
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地理科学进展
,2011,30(5):627-634 【核心库】
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关键词
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探索式空间数据分析(ESDA)
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空间自相关
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人均GDP
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黄土高原地区
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地址
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中国科学院地理科学与资源研究所, 北京, 100101
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1007-6301 |
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学科
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社会科学总论 |
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基金
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国家自然科学基金重点项目
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国家科技支撑计划项目
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文献收藏号
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CSCD:4209771
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参考文献 共
23
共2页
|
|
1.
徐建华. 中国区域经济差异的时空尺度分析.
地理研究,2005,24(1):57-68
|
CSCD被引
135
次
|
|
|
|
|
2.
郭腾云. 1952～2003年我国区域经济发展不均衡的长期变化态势.
地理科学进展,2005,24(1):21-30
|
CSCD被引
5
次
|
|
|
|
|
3.
韩增林. 中国海洋经济地域差异及演化过程分析.
地理研究,2008,27(3):613-622
|
CSCD被引
19
次
|
|
|
|
|
4.
Rey S. US regional income convergence:a spatial econometric perspective.
Regional Studies,1999,33(2):143-1564
|
CSCD被引
50
次
|
|
|
|
|
5.
Unwin A. Exploratory spatial data analysis with local statistics.
The Statistician,1998,47(3):415-421
|
CSCD被引
4
次
|
|
|
|
|
6.
Giuseppe A. The role of spatial effects in the empirical analysis of regional concentration.
Journal of geographical systems,2001,3(3):271-281
|
CSCD被引
25
次
|
|
|
|
|
7.
杨振山. 空间统计学进展及其在经济地理研究中的应用.
地理科学进展,2010,29(6):757-768
|
CSCD被引
23
次
|
|
|
|
|
8.
Fotheringham A S. Exploratory spatial data analysis and GIS:Commentary.
Environment&Planning A,1992,24(12):1675-1678
|
CSCD被引
1
次
|
|
|
|
|
9.
Moran P A P. Notes on continuous stochastic phenomena.
Biometrika,1950,37(1/2):17-23
|
CSCD被引
296
次
|
|
|
|
|
10.
Geary R C. The Contiguity ratio and statistical mapping.
The Incorporated Statistician,1954,5(3):115-145
|
CSCD被引
74
次
|
|
|
|
|
11.
Anselin L. Local indicators of spatial association-LISA.
Geographical Analysis,1995,27(2):93-115
|
CSCD被引
949
次
|
|
|
|
|
12.
Getis A. The analysis of spatial association by use of distance statistics.
Geographical Analysis,1992,24(3):189-206
|
CSCD被引
443
次
|
|
|
|
|
13.
Ord J K. Local spatial autocorrelation statistics:Distributional issues and an application.
Geographical Analysis,1995,27(4):286-306
|
CSCD被引
151
次
|
|
|
|
|
14.
Gallo J L. Exploratory spatial data analysis of the distribution of regional per capita GDP in Europe,1980-1995.
Papers in Regional Science,2003,82(2):175-201
|
CSCD被引
21
次
|
|
|
|
|
15.
孟斌. 基于空间分析方法的中国区域差异研究.
地理科学,2005,25(4):393-400
|
CSCD被引
135
次
|
|
|
|
|
16.
Tang Jianjun. Exploratory spatial data analysis of the distribution of regional per capita GDP in Yangtze Delta,China:1994-2004.
Ecological Economy,2008,4(2):180-188
|
CSCD被引
3
次
|
|
|
|
|
17.
靳诚. 基于县域单元的江苏省经济空间格局演化.
地理学报,2009,64(6):713-724
|
CSCD被引
154
次
|
|
|
|
|
18.
杨振山. 利用探索式空间数据解析北京城市空间经济发展模式.
地理学报,2009,64(8):945-955
|
CSCD被引
16
次
|
|
|
|
|
19.
Haining R.
Spatial Data Analysis in the Social and Environmental Sciences,1990
|
CSCD被引
11
次
|
|
|
|
|
20.
Bailey T C.
Interactive Spatial Data Analysis,1995
|
CSCD被引
39
次
|
|
|
|
|
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