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Evaluation of Geo-Environment Carrying Capacity Based on Intuitionistic Fuzzy TOPSIS Method: A Case Study of China

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  • Yuanmin Wang

    (College of Management Science, Chengdu University of Technology, Chengdu 610059, China
    Institute of Artificial Intelligence, Leshan Vocational and Technical College, Leshan 614000, China)

  • Mingkang Yuan

    (College of Management Science, Chengdu University of Technology, Chengdu 610059, China)

  • Xiaofeng Zhou

    (College of Management Science, Chengdu University of Technology, Chengdu 610059, China)

  • Xiaobing Qu

    (College of Management Science, Chengdu University of Technology, Chengdu 610059, China)

Abstract

The resource environment is a fundamental prerequisite for the construction of ecological civilization and the realization of sustainable development goals. It is also a core guarantee for human production activities. Conducting an evaluation of regional geo-environmental carrying capacity has significant practical importance for achieving sustainable development in the region. However, the existing evaluation methods for geo-environmental carrying capacity fail to effectively integrate multi-source data, resulting in an incomplete reflection of the level of regional geological carrying capacity. To address this issue, this study introduces the intuitionistic fuzzy multi-attribute decision-making method into the geo-environmental carrying capacity evaluation, according to the unique topographic and geomorphological characteristics of the region. A complete analysis framework is established, which integrates the intuitionistic fuzzy and TOPSIS models to classify the geo-environmental carrying capacity evaluation into five grades: high, relatively high, medium, relatively poor, and poor. Using Meishan, China as an example, the region is divided into 33 geomorphological units based on its geographical features. The results show that: (a) the percentage of natural units with high carrying capacity is 17.27%, that of relatively high natural units is 14.07%, that of medium natural units is 31.70%, that of relatively poor natural units is 27.51%, and that of poor natural units is 9.45%; (b) the geo-environmental carrying capacity exhibits spatial differences and uneven distribution. Furthermore, the average annual rainfall and degree of karst development are the main factors affecting the geo-environmental carrying capacity. These research results and findings can provide technical support for urban planning, regional sustainable development, and ecological environmental protection.

Suggested Citation

  • Yuanmin Wang & Mingkang Yuan & Xiaofeng Zhou & Xiaobing Qu, 2023. "Evaluation of Geo-Environment Carrying Capacity Based on Intuitionistic Fuzzy TOPSIS Method: A Case Study of China," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8121-:d:1148626
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    References listed on IDEAS

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    1. Lin, Song-Shun & Shen, Shui-Long & Zhou, Annan & Xu, Ye-Shuang, 2021. "Novel model for risk identification during karst excavation," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Lei, Kampeng & Zhou, Shaoqi, 2012. "Per capita resource consumption and resource carrying capacity: A comparison of the sustainability of 17 mainstream countries," Energy Policy, Elsevier, vol. 42(C), pages 603-612.
    3. Majid Ebrahimi & Hamid Nejadsoleymani & Mohammad Reza Mansouri Daneshvar, 2019. "Land suitability map and ecological carrying capacity for the recognition of touristic zones in the Kalat region, Iran: a multi-criteria analysis based on AHP and GIS," Asia-Pacific Journal of Regional Science, Springer, vol. 3(3), pages 697-718, October.
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