Journal of Geographical Sciences

, Volume 29, Issue 8, pp 1300–1314 | Cite as

Identification and classification of resource-based cities in China

  • Jianhui Yu
  • Jiaming LiEmail author
  • Wenzhong Zhang


Resource-dependent cities are cities whose economic development depends on the exploitation and processing of natural resources. Their transformation and sustainable development are an important area of research on regional industrial development, regional economy and urban development. Since the Chinese government launched a pilot project to transform resource-dependent cities, starting with Fuxin in Liaoning Province in 2001, accurately identifying and classifying China’s resource-dependent cities has become a focus of geographical research. Based on previous studies, this paper uses the theory and methods of urban function classification to analyze indicators and threshold values for identifying and classifying resource-dependent cities. It has thus identified 262 cities as being resource-dependent. Looking at the development levels, problems, characteristics and developmental direction of such cities, this paper attempts to establish a comprehensive analytical framework using the two evaluation indicators of resource security and sustainable development. It also creates a model to classify the 262 cities identified as resource-dependent cities into four types: growing cities, mature cities, declining cities and regenerating cities. The different connotations and characteristics of the city types were then analyzed. The results of this research support the delineation of scopes and categories of resource-dependent cities set out in the National Sustainable Development Plan for Resource-Dependent Cities published by the State Council, and they serve as a foundation for formulating policies on planning, classification and guidance.


resource-dependent cities identification classification 


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Copyright information

© Science Press Springer-Verlag 2019

Authors and Affiliations

  1. 1.Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources ResearchCASBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

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