PROGRESS IN GEOGRAPHY ›› 2014, Vol. 33 ›› Issue (2): 241-248.doi: 10.11820/dlkxjz.2014.02.010

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Development level and coordination of highway networks of prefecture-level administrative regions in China

LIU Dong1,2,3, JIN Fengjun1   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. University of ChineseAcademy of Sciences, Beijing 100049, China;
    3. Transport Planning and Research Institute, MOT, Beijing 100028, China
  • Received:2013-04-01 Revised:2013-11-01 Online:2014-02-25 Published:2014-02-25
  • Contact: 金凤君(1961-),内蒙古赤峰人,研究员,博士生导师,主要从事经济地理与区域经济研究,E-mail:jinfj@igsnrr.ac.cn。 E-mail:leastar@sohu.com;jinfj@igsnrr.ac.cn
  • About author:K902

Abstract: The study of regional transport development in different scales is one of important areas in transport geography research. There are big differences among the regions of China in highway network development. Examining the differences in the scale of prefecture-level administrative region (PAR) is more accurate than in provincial scale. In this paper, taking the 333 PARs in China as a research object, we studied the differences among the regions in highway network development and evaluated the degree of coordination between highway network development and economic development. Firstly, we selected 9 indicators reflecting the scale, quality, accessibility and transportation volume of highway networks and, by using the weighted average method, established a comprehensive evaluation model to evaluate the levels of highway network development and calculate highway indicators for the 333 PARs. Secondly, we selected 7 economic indicators to establish a comprehensive evaluation model for the regional economic development, and calculated the economic indicators for the 333 PARs. Thirdly, by using Pearson formula, we calculated the correlation coefficient between the highway index and the economic index. Finally, we established a coordination evaluation model and calculated the coordination index between the highway network development and the economic development for each PAR. The results and conclusions are as follows. (1) There are big differences among the different regions in highway network development; the highway indicators of the 333 PARs varied from 0.361 to 5.992, with Dongguan City and Shenzhen City being the highest and Ngari Prefecture and Nagqu Prefecture the lowest. Based on the highway index, the 333 PARs are classified into three levels, including 104, 121 and 108 PARs respectively, which shows a ladder-like distribution in a large scale, corresponding to the spatial pattern of Eastern, Central and Western China. It is worth pointing out that the 108 PARs in the third, or the underdeveloped, level of highway network development are mainly located in Western China. (2) The correlation coefficient between the highway index and the economic index was calculated to be 0.8328, which shows a highly positive correlation between the two index systems. (3) The coordination index of the 333 PARs varied from 0.223 to 1.634, with Dongguan City being the highest and Alxa League the lowest. Based on the coordination index, the 333 PARs are classified into three categories, namely, the advanced, coordinated, and lagged, including 90, 85 and 158 regions respectively. Here "advanced" means that the highway network development is ahead of the regional economic development; "coordinated" means highway network development is coordinated with the regional economic development; "lagged" means the highway network development is lagged behind the regional economic development. The spatial distribution of the three categories is different from the distribution of the three levels, but 92 PARs are in both the lagged category and the third level, mainly located in West China. For the lagged and underdeveloped PARs, the measures should be taken to optimize and upgrade the highway networks and meet the needs of the regional economic development.

Key words: China, coordination, development level, highway network, prefecture-level administrative region

CLC Number: 

  • K902