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A Land Spatial Optimization Approach for the Reutilization of Abandoned Mine Land: A Case Study of Ningbo, China

Author

Listed:
  • Chenglong Cao

    (College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China)

  • Liu Yang

    (College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China)

  • Wanqiu Zhang

    (College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China)

  • Wenjun Zhang

    (The Second Geological and Mineral Exploration Institute of Gansu Provincial Bureau of Geology and Mineral Exploration and Development, Lanzhou 730020, China)

  • Gang Lin

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    Key Laboratory of Coupling Processes and Effects of Natural Resource Elements, Ministry of Natural Resources, Beijing 100055, China)

  • Kun Liu

    (Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China)

Abstract

As a mining country, China faces enormous challenges in the context of the global commitment to achieve carbon neutrality. In order to achieve this goal, the Chinese government is actively promoting the green and low-carbon transformation of the energy system. Consequently, an increasing number of mines with poor production capacity and depleted resources are being closed down or eliminated, leading to a large quantity of stranded land resources that are now idle. However, in the process of rapid economic development, China is facing serious problems, such as land shortage and land use conflicts. Abandoned mining land (AML), as a kind of reserve land resource, has an important regulating role in solving the dilemma of land resource tension faced by national land spatial planning. In order to realize the rational planning and utilization of AML, this study proposes a high-precision AML planning model and simulates the planning of AML in multiple policy scenarios, using Ningbo City as an example. The results show that AML has great economic and ecological potential; the economic development scenario (EDS) enhanced the economic benefits of the mine region by 396%, and the ecological protection scenario (EPS) enhanced the ecological benefits of the mine region by 74.61%, when compared with the baseline scenario (BAU). The overall level of optimization is as follows: EDS > EPS > BAU. In addition, the optimal utilization of AML in all three scenarios significantly enhanced the ecological quality of the mining region, and the enhancement effect was EPS > BAU > EDS. Therefore, AML, as a kind of free land resource, has an important supporting effect for the spatial planning of the national territory. Furthermore, it is of great significance to scientifically and reasonably guide the optimal utilization of AML, according to the policy planning for future development, in order to achieve efficient economic development and improve the quality of the ecological environment.

Suggested Citation

  • Chenglong Cao & Liu Yang & Wanqiu Zhang & Wenjun Zhang & Gang Lin & Kun Liu, 2025. "A Land Spatial Optimization Approach for the Reutilization of Abandoned Mine Land: A Case Study of Ningbo, China," Land, MDPI, vol. 14(2), pages 1-25, February.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:2:p:326-:d:1584659
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    References listed on IDEAS

    as
    1. Yan Long & Xi Liu & Shiqi Luo & Tianyue Luo & Siyu Hu & Yuqiao Zheng & Jingmei Shao & Xuejun Liu, 2023. "Evolution and Prediction of Urban Fringe Areas Based on Logistic–CA–Markov Models: The Case of Wuhan City," Land, MDPI, vol. 12(10), pages 1-30, October.
    2. Chunsheng Hu & Yong Zhao & Fangjuan Cheng & Zhiping Li, 2023. "Multi-Object Detection Algorithm in Wind Turbine Nacelles Based on Improved YOLOX-Nano," Energies, MDPI, vol. 16(3), pages 1-13, January.
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