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Analysis and Prediction of Land Resources’ Carrying Capacity in 31 Provinces of China from 2008 to 2016

Author

Listed:
  • Chuqiao Han

    (College of Resource and Environment Sciences, Institute of Arid Ecology Environment, Xinjiang University, Xinjiang 830046, China)

  • Binbin Lu

    (College of Resource and Environment Sciences, Institute of Arid Ecology Environment, Xinjiang University, Xinjiang 830046, China
    School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China)

  • Jianghua Zheng

    (College of Resource and Environment Sciences, Institute of Arid Ecology Environment, Xinjiang University, Xinjiang 830046, China)

Abstract

The rapid development of urbanization, population growth, and unreasonable use of land resources have made the contradiction between human beings and land increasingly prominent, and the carrying capacity of land resources has become an important factor affecting the sustainable development of a city or even a country. Based on the carrying capacity of agricultural land, construction land, and ecological land in 31 provinces of China, this paper analyzed the spatiotemporal characteristics of the carrying capacity of land resources in 31 provinces of China from 2008 to 2016 by using single-factor carrying capacity evaluation and comprehensive carrying capacity evaluation methods. The evaluation results were divided into six levels (No pressure, Lower pressure, Low pressure, Medium pressure, High pressure, Higher pressure), and the ArcGIS10.2 software was used for visualization, and the carrying capacity prediction model was constructed to predict the development trend of the comprehensive carrying capacity of land resources in 2020 and 2025. The results showed that China’s land carrying capacity is extremely unbalanced. Whether from the evaluation results of single-factor carrying capacity or comprehensive carrying capacity, we showed the characteristics of high pressure in the east and low pressure in the west, and that the regional land resources have a deteriorating trend. Through the prediction of the future land resource carrying capacity index, it was found that the comprehensive carrying capacity index of land resources in 31 provinces of China will still show an upward trend in the future.

Suggested Citation

  • Chuqiao Han & Binbin Lu & Jianghua Zheng, 2021. "Analysis and Prediction of Land Resources’ Carrying Capacity in 31 Provinces of China from 2008 to 2016," Sustainability, MDPI, vol. 13(23), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13383-:d:694100
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    References listed on IDEAS

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    1. Gianni Guastella & Stefano Pareglio & Paolo Sckokai, 2017. "A Spatial Econometric Analysis of Land Use Efficiency in Large and Small Municipalities," Working Papers 2017.03, Fondazione Eni Enrico Mattei.
    2. Kaiyuan Li & Xiaolong Jin & Danxun Ma & Penghui Jiang, 2019. "Evaluation of Resource and Environmental Carrying Capacity of China’s Rapid-Urbanization Areas—A Case Study of Xinbei District, Changzhou," Land, MDPI, vol. 8(4), pages 1-17, April.
    3. Meyar-Naimi, H. & Vaez-Zadeh, S., 2012. "Sustainable development based energy policy making frameworks, a critical review," Energy Policy, Elsevier, vol. 43(C), pages 351-361.
    4. Ediger, Volkan S. & Akar, Sertac & Ugurlu, Berkin, 2006. "Forecasting production of fossil fuel sources in Turkey using a comparative regression and ARIMA model," Energy Policy, Elsevier, vol. 34(18), pages 3836-3846, December.
    5. Guangming Cui & Xuliang Zhang & Zhaohui Zhang & Yinghui Cao & Xiujun Liu, 2019. "Comprehensive Land Carrying Capacities of the Cities in the Shandong Peninsula Blue Economic Zone and their Spatio-Temporal Variations," Sustainability, MDPI, vol. 11(2), pages 1-12, January.
    6. Liu, Yansui & Zhou, Yang, 2021. "Territory spatial planning and national governance system in China," Land Use Policy, Elsevier, vol. 102(C).
    7. Panxing Zhang, 2021. "Estimation of Population Carrying Capacity of Land Resources: A Case Study of Chongqing," Springer Books, in: Gui Ye & Hongping Yuan & Jian Zuo (ed.), Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate, pages 355-364, Springer.
    8. Wei Zhou & Ayman Elshkaki & Shuai Zhong & Lei Shen, 2021. "Study on Relative Carrying Capacity of Land Resources and Its Zoning in 31 Provinces of China," Sustainability, MDPI, vol. 13(3), pages 1-13, January.
    9. Chong Zhao & Yong Zhou & Xigui Li & Pengnan Xiao & Jinhui Jiang, 2018. "Assessment of Cultivated Land Productivity and Its Spatial Differentiation in Dongting Lake Region: A Case Study of Yuanjiang City, Hunan Province," Sustainability, MDPI, vol. 10(10), pages 1-15, October.
    10. MacKinnon, James G, 1994. "Approximate Asymptotic Distribution Functions for Unit-Root and Cointegration Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 167-176, April.
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