Acta Geographica Sinica ›› 2013, Vol. 68 ›› Issue (2): 199-208.doi: 10.11821/xb201302005

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Quantifying location condition of resources-exhausted cities in China

SUN Wei1,2, LI Hongsheng1,3   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Key Laboratory of Regional Sustainable Development Modeling, CAS, Beijing 100101, China;
    3. State Key Laboratory of Resources and Environmental Information System, IGSNRR, CAS, Beijing 100101, China
  • Received:2012-05-03 Revised:2012-11-01 Online:2013-02-20 Published:2013-02-20
  • Supported by:

    National Key Technology R&D Program, No.2008BAH31B01; National Natural Science Foundation of China, No.40701044

Abstract: It has been widely acknowledged amongest domestic scholars that resources-based cities on a whole are located in remote and peripheral areas, which has become a major obstacle to successful transformation of these cities to sustainable development. Yet little attention has so far been given to quantitatively estimate whether these resources-based cities suffered from being remote and peripheral location, and how far. In this paper, we use 78 resources-exhausted cities identified by the State Council as the case cities to evaluate the location condition of resources-exhausted cities under different resources types and regions, based on the calculation method of spatial distance and time distance. The distance is how far these resources-exhausted cities are from the corresponding provincial capital cities and three regional central cities (Beijing, Shanghai, and Guangzhou) to which are closely linked resources-exhausted cities. The research findings include that: (1) From the perspective of overall sample cities, the location of resources-exhausted city is really remote. In the term of spatial distance, the location remoteness degree α1 is 1.36 (relative to the provincial capital city) and β1 is 1.14 (relative to regional center city), and in the term of of time distance, the location remoteness degree α2 = 1.65 (relative to provincial capital city) and β2 = 1.16 (relative to regional central city). (2) From the perspective of classification, location remoteness degrees of resources-exhausted cities show significant differences among different provinces and different resource types. The location remoteness degrees of resources-exhausted cities located in Western China and forestry-based cities are the largest. (3) From an integrated analysis of spatial distance and time distance, the number of resources-exhausted cities whose locations are very remote, namely α > 1.5 ∩ β > 1.5, respectively is 18 and 23, accounting for 23.1% and 29.5% of the total resouces-exhausted cities. The number of resources-exhausted cities whose location remoteness degrees are α ≤ 1.0 ∩ β ≤ 1.0, is 30 and 35 respectively, accounting for 38.5% and 44.9% of the total in China.

Key words: resources-exhausted city, location, identification method, China