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Spatial pattern evolution and casual analysis of county level economy in Changsha-Zhuzhou-**angtan urban agglomeration, China

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Abstract

In order to evaluate whether or not the county units’ economy in the Changsha-Zhuzhou-**angtan (Chang-Zhu-Tan) Urban Agglomeration was growing as expected, this study analyzed the spatial economy pattern at county-level by using the Exploratory Spatial Data Analysis (ESDA) method. In this process, the global Moran’s I and local Getis-Ord G i * indexes were employed to analyze indicators including per capita GDP and three industrials (i.e. primary, secondary and tertiary industry) from 2000 to 2010. The results show that: 1) the county units’ economy in the Chang-Zhu-Tan Urban Agglomeration has exhibited a strong spatial autocorrelation and an accelerated integration trend since 2008 (Moran’ s I increased from 0.26 to 0.56); 2) there is a significant difference in economy development between the northern and southern county units in the Chang-Zhu-Tan Urban Agglomeration: the hotspot zone with high economic level was formed among the northern county units whereas the coldspot zone with low economic level was located in the southern areas. This difference was caused primarily by the increasingly prominent economic radiation effect of Changsha ‘upheaval’; 3) town density, secondary industry, and the integration policy are the major contributors driving the evolution of the spatial economy pattern in the Chang-Zhu-Tan Urban Agglomeration.

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References

  • Akita T, 2003. Decomposing regional income inequality in China and Indonesia using two-stage nested Theil decomposition method. The Annals of Regional Science, 37(1): 55–77. doi: 10.1007/s001680200107

    Article  Google Scholar 

  • Andrienko N, Andrienko G, 2006. Exploratory Analysis of Spatial and Temporal Data. Berlin, Germany: Springer.

    Google Scholar 

  • Anselin L, 1995. Local indicators of spatial association: LISA. Geographical Analysis, 27(2): 93–115. doi: 10.1111/j.1538-4632.1995.tb00338.x

    Article  Google Scholar 

  • Arbia G, 2001. The role of spatial effects in the empirical analysis of regional concentration. Journal of Geographical Systems, 3: 271–281. doi: 10.1007/PL00011480

    Article  Google Scholar 

  • Bivand R, Müller W G, Reder M, 2009. Power calculations for global and local Moran’s I. Computational Statistics & Data Analysis, 53(8): 2859–2872. doi: 10.1016/J.csda.2008.07.021

    Article  Google Scholar 

  • Carl G, Kùhn I, 2007. Analyzing spatial autocorrelation in species distributions using Gaussian and logit models. Ecological Modeling, 207: 159–170. doi: 10.1016/j.ecolmodel.2007.04. 024

    Article  Google Scholar 

  • Dong Guanpeng, Guo Tengyun, Ma **g, 2010. GIS based analysis on spatial disparity of economic growth in BTHMR. Journal of Geo-information Science, 12(6): 797–805. (in Chinese)

    Article  Google Scholar 

  • Ellison G, Glaeser E L, 1997. Geographic concentration in U.S. manufacturing industries: A dartboard approach. The Journal of Political Economy, 105(5): 889–927.

    Article  Google Scholar 

  • Ertur C, Koch W, 2006. Regional disparities in the European Union and the enlargement process: An exploratory spatial data analy sis, 1995–2000. The Annals of Regional Science, 40: 723–765. doi: 10.1007/s00168-006-0062x

    Article  Google Scholar 

  • Fishman R, 2000. The American metropolis at century’s end: Past and future influences. Housing Policy Debate, 11(1): 199–213. doi: 10.1080/10511482.2000.9521367

    Article  Google Scholar 

  • Gallo J, Ertur C, 2003. Exploratory spatial data analysis of the distribution of regional per capita GDP in Europe, 1980–1995. Papers in Regional Science, 82(2): 175–201. doi: 10.1007/s101100300145

    Article  Google Scholar 

  • Gao **aona, Ma Yanji, 2008. Spatial pattern and influencing factor of county-level industrial development in Liaoning Province of China. Chinese Geographical Science, 18(1): 24–32. doi: 10.1007/s11769-008-0024-6

    Article  Google Scholar 

  • Garrigues S, Allard D, Baret F et al., 2006. Quantifying spatial heterogeneity at the landscape scale using variogram models. Remote Sensing of Environment, 103(1): 81–96. doi: 10.1016/j.rse.2006.03.013

    Article  Google Scholar 

  • Getis A, Ord JK, 1992. The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3): 189–206. doi: 10.1111/j.1538-4632.1992.tb00261.x

    Article  Google Scholar 

  • Goodchild M, Anselin L, Applebaum R et al., 2000. Towards a spatially integrated social science. International Regional Science Review, 23: 139–159. doi: 10.1177/01600176000230-0201

    Article  Google Scholar 

  • Goodchild M, Haining R, 1992. Integrating GIS and spatial data analysis: Problems and possibilities. International Journal of Geographical Information Systems, 6(5): 407–423. doi: 10.1080/0269379 9208901923

    Article  Google Scholar 

  • Guillain R, Le Gallo J, 2010. Agglomeration and dispersion of economic activities in and around Paris: An exploratory spatial data analysis. Environment and Planning B: Planning and Design, 37(6): 961–981. doi: 10.1068/b35038

    Article  Google Scholar 

  • Hunan Provincial Bureau of Statistics, 2001–2011. Hunan Statistical Yearbook (2000–2010). Bei**g: China Statistics Press. (in Chinese)

    Google Scholar 

  • ** Cheng, Lu Yuqi, 2009. Evolvement of spatial pattern of economy in Jiangsu Province at county level. Acta Geographica Sinica, 64(6): 714–724. (in Chinese)

    Google Scholar 

  • Jong P, Sprenger C, Veen F, 1984. On extreme values of Moran’s I and Geary’s c. Geographical Analysis, 16(1): 17–24. doi: 10.1111/j.1538-4632.1984.tb00797.x

    Article  Google Scholar 

  • Li Tingting, Wu Shidai, Li Yongshi et al., 2010. Spatial variability and evolutionary mechanism of economic growth in Fujian Province. Scientia Geographica Sinica, 30(6): 848–853. (in Chinese)

    Google Scholar 

  • Li Tian, 2010. Regional economic disparities in Changzhutan Urban Agglomeration. **an: Shandong University. (in Chinese)

    Google Scholar 

  • Liu Xuhua, Wang **feng, 2002. Analysis and application on the specification methods of the spatial weight matrix. Geo-information Science, 4(2): 38–44. (in Chinese)

    Google Scholar 

  • Murray A, McGuffog I, Western J et al., 2001. Exploratory spatial data analysis techniques for examining urban crime implications for evaluating treatment. British Journal of Criminology, 41(2): 309–329. doi: 10.1093/bjc/41.2.309

    Article  Google Scholar 

  • Ord JK, Getis A, 1995. Local spatial autocorrelation statistics: Distributional issues and an application. Geographical Analysis, 27(4): 286–306. doi: 10.1111/j.1538-4632.1995.tb00912.x

    Article  Google Scholar 

  • Patacchini E, Rice P, 2007. Geography and economic performance: Exploratory spatial data analysis for Great Britain. Regional Studies, 41(4): 489–508. doi: 10.1080/0034340-0600928384

    Article  Google Scholar 

  • Pu Yingxia, Ge Ying, Ma Ronghua et al., 2005. Analyzing regional economic disparities based on ESDA. Geographical Research, 24(6): 966–973. (in Chinese)

    Google Scholar 

  • Qin Zhiqin, Zhang **yu, 2011. Simulation analysis on spatial pattern of urban population in Shenyang City, China in Late 20th century. Chinese Geographical Science, 21(1): 110–118. doi: 10. 1007/s11769-011-0444-6

    Article  Google Scholar 

  • Rosenthal S, Strange W C, 2004. Evidence on the nature and sources of agglomeration economies. Handbook of Regional and Urban Economics, 4: 2119–2171. doi: 10.1016/S1574008-0(04)80006-3

    Article  Google Scholar 

  • Tang Kai, Zhou Guohua, 2013. Analysis of spatial conflict measurement based on the perspective of economics: A case study of Changzhutan areas. Journal of Natural Science of Hunan Normal University, 36(3): 90–94. (in Chinese)

    Google Scholar 

  • Wang Fazeng, Lu **rong, 2011. The evaluation and spatial-temporal evolvement of the city competitiveness of Zhongyuan Urban Agglomeration. Geographical Research, 30(1): 50–59. (in Chinese)

    Google Scholar 

  • Wang **g, Fang Chuanglin, 2011. New-type driving forces of urban agglomerations development in China. Geographical Research, 30(2): 336–347. (in Chinese)

    Google Scholar 

  • Wang Yang, Fang Chuanglin, **u Chunliang et al., 2012. A new approach to measurement of regional inequality in particular directions. Chinese Geographical Science, 22(6): 705–717. doi: 10.1007/s11769-012-0556-7

    Article  Google Scholar 

  • Wang Youqiang, Tsui Kaiyuan, 2000. Polarization ordering and new classes of plarization indices. Journal of Public Economic Theory, 3(2): 349–363. doi: 10.1111/1097-3923.00042

    Article  Google Scholar 

  • Zhou Guohua, Peng Jiajie, 2012. The evolution characteristics and influence effect of spatial conflict: A case study of Changsha-Zhuzhou-**angtan urban agglomeration. Progress in Geography, 31(6): 717–723. (in Chinese)

    Google Scholar 

  • Zhang Songlin, Zhang Kun, 2007. Contrast study on Moran and Getis-Ord indexes of local spatial autocorrelation indices. Journal of Geodesy and Geodynamics, 27(3): 31–34. (in Chinese)

    Google Scholar 

  • Zhu Shunjuan, 2012. Study on the spatial structure of Changzhutan urban agglomeration and its optimization. Changsha: Central South University. (in Chinese)

    Google Scholar 

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Authors and Affiliations

  1. Department of Geography, Hunan University of Arts and Science, Changde, 415000, China

    Minghui Dong

  2. Department of Geomatics and Remote Sensing, Central South University, Changsha, 410083, China

    Bin Zou, Qiang Pu & Yanqing Luo

  3. Department of Geography, University of Utah, Salt Lake City, UT, 84112, USA

    Neng Wan

  4. Department of Geography, Northeast Normal University, Changchun, 130024, China

    Lingbin Yang

Authors
  1. Minghui Dong
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  2. Bin Zou
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  3. Qiang Pu
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  4. Neng Wan
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  5. Lingbin Yang
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  6. Yanqing Luo
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Corresponding author

Correspondence to Bin Zou.

Additional information

Foundation item: Under the auspices of National Natural Science Foundation of China (No. 41201384), Hunan Provincial Natural Science Foundation (No. 12JJ3034), State Key Laboratory of Resources and Environmental Information System, Nieying Talent Program of Central South University (No. 7601110176)

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Dong, M., Zou, B., Pu, Q. et al. Spatial pattern evolution and casual analysis of county level economy in Changsha-Zhuzhou-**angtan urban agglomeration, China. Chin. Geogr. Sci. 24, 620–630 (2014). https://doi.org/10.1007/s11769-014-0685-2

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  • DOI: https://doi.org/10.1007/s11769-014-0685-2

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