深圳大学学报理工版

在建立深圳服务业地理数据库基础上,采用空间分析法分析深圳服务业的分布格局及空间自相关性.研究表明,点密度渲染和加权平均中心刻画出了地理要素总量分布情况,深圳服务业企业分布密度基本体现从市中心向外递减的规律,各服务业加权中心均西向偏离地理中心.通过Moran's I检验,显示深圳服务业具有不同的全局空间自相关性,高增加值比重(≥3%)服务业局部自相关集聚区呈多样化格局,区域分工已经形成,这是区位条件、经济联系和政府规划等因素共同作用的结果.研究指出,因为城市区位差异性和产业异质性的存在,不同区域有必要坚持定制化的服务业空间发展策略.

Based on the establishment of Shenzhen service enterprises geographic database, spatial analysis is adopted to develop empirical research on Shenzhen service industry spatial distribution and autocorrelation patterns. Conclusion s are drawn as follows: dot density rendering and centrographic statistics estimate the spatial distribution characteristics of geographic factors on the whole. Shenzhen service enterprises distribute with a strong trickle-down trend from the city center to the periphery. The weighted mean centers of Shenzhen service industries display an obviously western offset from the geometry center. Indicated by Moran's I verifications, Shenzhen service industries have different global spatial autocorrelations. Also Shenzhen services with high proportion of added values(≥3%)show diversified local spatial autocorrelations on agglomerative subdistricts. Regional industrial division has been formed, which is the result of cooperative effect of location condition, economic ties, and government planning. Furthermore, it would be necessary to keep customized spatial development policies for the specific service industry, because of the existence of urban regional differences and industrial heterogeneity.

引言
1 研究区域与数据处理
2 研究方法
3 深圳服务业空间分布总量分析
4 服务业空间自相关分析
5 结论

图1 深圳街道网格图<br/>Fig.1 Subdistrict grid map of Shenzhen

图1 深圳街道网格图
Fig.1 Subdistrict grid map of Shenzhen

图2 2012年深圳服务业企业点密度分布<br/>Fig.2 Dot density map of Shenzhen service enterprises on 2012

图2 2012年深圳服务业企业点密度分布
Fig.2 Dot density map of Shenzhen service enterprises on 2012

图3 2012年深圳服务业空间分布中心<br/>Fig.3 Mean centers of Shenzhen service industries on 2012

图3 2012年深圳服务业空间分布中心
Fig.3 Mean centers of Shenzhen service industries on 2012

表1 2012年深圳服务业全局空间自相关检验<br/>Table 1 Global Moran's I of Shenzhen service industries on 2012

表1 2012年深圳服务业全局空间自相关检验
Table 1 Global Moran's I of Shenzhen service industries on 2012

图4 2012年深圳高增加值比重服务业LISA集聚图<br/>Fig.4 LISA cluster map of Shenzhen services with high proportion of added value on 2012

图4 2012年深圳高增加值比重服务业LISA集聚图
Fig.4 LISA cluster map of Shenzhen services with high proportion of added value on 2012

[1] Hanink D M,Ebenstein A Y,Cromley R G.Spatial analysis of selected manufacturing and service sectors in China's economy using county employment data for 1990 and 2000[J].Regional Studies,2011,45(3):351-369.
[2] Funderburg R G,Boarnet M G.Agglomeration potential: the spatial scale of industry linkages in the Southern California economy[J].Growth and Change,2008,39(1):24-57.
[3] Marr P.The geography of the British motorcycle industry,1896-2004 [J].The Journal of Transport History,2012,33(2):163-185.
[4] Bi Xiujing,Wang Mingfeng,Li Jian,et al.Agglomeration and suburbanization: a study on the spatial distribution of software industry and its evolution in metropolitan Shanghai[J].Acta Geographica Sinica,2011,66(12):1682-1694.(in Chinese)
[5] Zhang Xiaoping,Sun Lei.Manufacture restructuring and main determinants in Beijing metropolitan area[J].Acta Geographica Sinica,2012,67(10):1308-1316.(in Chinese)
[6] Meng Xiaochen,Shi Xiaoyu.The spatial distribution of FDI manufacturers in Shenzhen City [J].City Planning Review,2003,27(8):19-25.(in Chinese)
[7] Li Jiang,He Chuanjiao.Mechanism of agglomerating development of industries: a case study of Shenzhen [J].City Planning Review. 2008,32(9):75- 80.(in Chinese)
[8] Li Qingquan,Li Deren.Big data GIS[J].Geomatics and Information Science of Wuhan University,2014,39(6): 641- 644,666.(in Chinese)
[9] Dormann C F, Mcpherson J M, Baraújo M, et al. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review[J].Ecography,2007,30(5):609- 628.
[10] Fang L,Yan L,Liang S,et al.Spatial analysis of hemorrhagic fever with renal syndrome in China [J].Bmc Infectious Diseases,2006,6(1):77.
[11] Sohn J.Industry classification considering spatial distribution of manufacturing activities [J].Area,2014,46(1):101-110.
[12] Getis A.Spatial weights matrices[J].Geographical Analysis,2009,41(4):404- 410.
[13] Moran P.Notes on continuous stochastic phenomena[J].Biometrika,1950,37(1):17-23.
[14] Anselin L.Local indicators of spatial association—LISA[J].Geographical Analysis,1995,27(2):93-115.
[15] Tobler W R.A computer movie simulating urban growth in the Detroit region[J].Economic Geography,1970,46(2):234-240.
[16] Qian Minghui.Hu Ridong.Research on the spatial radiation ability of regional financial center in China[J].Geographical Research,2014,33(6):1140-1150.(in Chinese)
[17] Ren Yinghua,Xu Ling,You Wanhai.A spatial econometric model and its application on the factors of financial industry agglomeration[J].The Journal of Quantitative & Technical Economics,2010(5):104-115.(in Chinese)
[18] Zhang Wen,Wang Jiaqiu.A research on Shenzhen's industrial spatial structurebased on PCA-SOM[J].Geographical Research,2014,33(9):1736-1746.(in Chinese)
[19] Zhong Yun,Liu Wei.Economic features of modern service cluster and their implications[J].Tropical Geography,2012(5):515-520,574.(in Chinese)

备注

引言

1 研究区域与数据处理

2 研究方法

3 深圳服务业空间分布总量分析

4 服务业空间自相关分析

5 结论

期刊信息

备注