IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i23p13383-d694100.html

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/23/13383/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/23/13383/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guastella, Gianni & Pareglio, Stefano & Sckokai, Paolo, "undated". "A Spatial Econometric Analysis of Land Use Efficiency in Large and Small Municipalities," SAS: Society and Sustainability 253216, Fondazione Eni Enrico Mattei (FEEM).
    2. 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.
    3. 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.
    4. 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.
    5. Liu, Yansui & Zhou, Yang, 2021. "Territory spatial planning and national governance system in China," Land Use Policy, Elsevier, vol. 102(C).
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jia Gao & Rongrong Zhao & Ge Song & Yuxin Zhan & Yaohui Zhu, 2022. "Spatial–Temporal Evolution Patterns and Regulatory Strategies for Land Resource Carrying Capacity of China’s Major Grain-Producing Areas," Land, MDPI, vol. 11(12), pages 1-17, November.
    2. Kazem Yavari & Mina Mehrnoosh, 2005. "The Welfare Cost of Inflation in Iran," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 10(2), pages 111-117, fall.
    3. Apostolos Serletis & Ricardo Rangel-Ruiz, 2007. "Testing for Common Features in North American Energy Markets," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 14, pages 172-187, World Scientific Publishing Co. Pte. Ltd..
    4. Prabheesh, K.P. & Anglingkusumo, Reza & Juhro, Solikin M., 2021. "The dynamics of global financial cycle and domestic economic cycles: Evidence from India and Indonesia," Economic Modelling, Elsevier, vol. 94(C), pages 831-842.
    5. Daniya Tlegenova, 2015. "Forecasting Exchange Rates Using Time Series Analysis: The sample of the currency of Kazakhstan," Papers 1508.07534, arXiv.org.
    6. Shuangqing Sheng & Wei Song & Hua Lian & Lei Ning, 2022. "Review of Urban Land Management Based on Bibliometrics," Land, MDPI, vol. 11(11), pages 1-25, November.
    7. Na Lu & Tiantian Shan & Wen Li & Xuan Liu & Weidong Wang, 2025. "Does the Digital Economy Promote Green Land Use Efficiency?," Sustainability, MDPI, vol. 17(16), pages 1-22, August.
    8. Camarero, Mariam & Flores, Renato Jr. & Tamarit, Cecilio R., 2006. "Monetary union and productivity differences in Mercosur countries," Journal of Policy Modeling, Elsevier, vol. 28(1), pages 53-66, January.
    9. Broberg, Thomas, 2014. "Relative income and the WTP for public goods - A case study of forest conservation in Sweden," CERE Working Papers 2014:6, CERE - the Center for Environmental and Resource Economics.
    10. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    11. Yujin Lu & Xingmeng Xu & Gaoru Zhu & Yuting Peng & Yi Li & Xueyan Zhao, 2024. "Land Space and High-Speed Transportation Coordinated Development Evaluation in the Beijing–Tianjin–Hebei Urban Agglomeration of China," Land, MDPI, vol. 13(10), pages 1-27, October.
    12. Davidson, Russell & Trokić, Mirza, 2020. "The fast iterated bootstrap," Journal of Econometrics, Elsevier, vol. 218(2), pages 451-475.
    13. Jaroslava Hlouskova & Martin Wagner, 2006. "The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 85-116.
    14. Chen, Fangxin & Li, Yurui & Liu, Yansui, 2025. "Bottom-up hierarchical detection of territorial spatial pattern based on multi-source heterogeneous data," Land Use Policy, Elsevier, vol. 158(C).
    15. Lijuan Zhang & Tatyana Ponomarenko, 2023. "Directions for Sustainable Development of China’s Coal Industry in the Post-Epidemic Era," Sustainability, MDPI, vol. 15(8), pages 1-32, April.
    16. Jiao Zhang & Qian Wang & Yiping Xia & Katsunori Furuya, 2022. "Knowledge Map of Spatial Planning and Sustainable Development: A Visual Analysis Using CiteSpace," Land, MDPI, vol. 11(3), pages 1-24, February.
    17. Yunheng Zhou & Weizhen Wang & Yiming Chen & Jiaai Tian & Kevin Tu, 2025. "Evaluating Eurasian countries’ global energy governance: a framework for analysis," Asia Europe Journal, Springer, vol. 23(2), pages 193-208, September.
    18. Xiaoyang Liu & Weihao Shi & Sen Zhang, 2022. "Progress of Research on Urban Growth Boundary and Its Implications in Chinese Studies Based on Bibliometric Analysis," IJERPH, MDPI, vol. 19(24), pages 1-18, December.
    19. Yiwen Shao & Yao Sun & Zhiru Zheng, 2023. "How Do Comprehensive Territorial Plans Frame Resilience? A Content Analysis of Plans by Major Cities in China," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    20. Hayashi, Naotsugu, 2005. "Structural changes and unit roots in Japan's macroeconomic time series: is real business cycle theory supported?," Japan and the World Economy, Elsevier, vol. 17(2), pages 239-259, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13383-:d:694100. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.