IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i14p8240-d856803.html
   My bibliography  Save this article

Estimation and Potential Analysis of Land Population Carrying Capacity in Shanghai Metropolis

Author

Listed:
  • Hefeng Wang

    (School of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, China)

  • Yuan Cao

    (School of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, China)

  • Xiaohu Wu

    (School of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, China)

  • Ao Zhao

    (School of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, China)

  • Yi Xie

    (School of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, China)

Abstract

It is of great practical significance to understand the current situation of urban land carrying capacity, explore its potential space, and continuously improve the economic adaptability and resilience and population carrying capacity of megacities. Based on the guiding principle of territorial spatial division and the concept of moderate-scale resilient cities, combined with GIS technology, this study aims to divide land spaces into three types and construct different index systems to evaluate the land carrying capacity of Shanghai in different spaces. Furthermore, we propose different schemes of estimating subspace land population carrying capacity, and the carrying potential of land population is analysed as well. The acquired results demonstrate three key points. Firstly, the total land population capacity of Shanghai is estimated at 25,476.61–32,047.27 people, with urban land space being the most dominant for the city’s population carrying capacity. Furthermore, the inner suburbs carry the largest population, and the urban centre carries a larger population density than other areas. Secondly, there are significant spatial differences in land population carrying potential. Compared with the demographic data from 2017, Shanghai still has a population carrying potential of 1293.30–7863.97 people and a suitable population carrying potential of 4578.64 people. The population of the urban centre is near the upper limit of the estimated population carrying capacity, and the suburbs, especially the outer suburbs, have large population carrying potential. Thirdly, the estimation method adopted in this study can effectively reveal the spatial differences in population carrying capacity and the potential of different land spaces and different regions in Shanghai, with the estimation results being highly credible. The results will provide references for the improvement of the multi-scenario population planning strategy in Shanghai, as well as enrich the research span and methods currently employed in land carrying capacity.

Suggested Citation

  • Hefeng Wang & Yuan Cao & Xiaohu Wu & Ao Zhao & Yi Xie, 2022. "Estimation and Potential Analysis of Land Population Carrying Capacity in Shanghai Metropolis," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:14:p:8240-:d:856803
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/14/8240/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/14/8240/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang Tang & Yongbo Yuan & Qingyu Zhong, 2021. "Evaluation of Land Comprehensive Carrying Capacity and Spatio-Temporal Analysis of the Harbin-Changchun Urban Agglomeration," IJERPH, MDPI, vol. 18(2), pages 1-19, January.
    2. 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.
    3. Ellison, Glenn & Glaeser, Edward L, 1997. "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," Journal of Political Economy, University of Chicago Press, vol. 105(5), pages 889-927, October.
    4. Arrow, Kenneth & Bolin, Bert & Costanza, Robert & Dasgupta, Partha & Folke, Carl & Holling, C.S. & Jansson, Bengt-Owe & Levin, Simon & Mäler, Karl-Göran & Perrings, Charles & Pimentel, David, 1996. "Economic growth, carrying capacity, and the environment," Environment and Development Economics, Cambridge University Press, vol. 1(1), pages 104-110, February.
    5. Shana Shi & Baoqing Hu & Yan Yan & Xiaoqing Li & Kaichun Zhou & Chuanyong Tang & Binggeng Xie, 2020. "Dynamic Evolution of the Ecological Carrying Capacity of Poverty-Stricken Karst Counties Based on Ecological Footprints: A Case Study in Northwestern Guangxi, China," IJERPH, MDPI, vol. 17(3), pages 1-20, February.
    6. Zhenbo Wang, 2018. "Land Spatial Development Based on Carrying Capacity, Land Development Potential, and Efficiency of Urban Agglomerations in China," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
    7. Kun Cheng & Qiang Fu & Song Cui & Tian-xiao Li & Wei Pei & Dong Liu & Jun Meng, 2017. "Evaluation of the land carrying capacity of major grain-producing areas and the identification of risk factors," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(1), pages 263-280, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cheng Zhan & Mingjing Guo & Jinhua Cheng & Hongxia Peng, 2022. "Evaluation of Resources and Environment Carrying Capacity Based on Support Pressure Coupling Mechanism: A Case Study of the Yangtze River Economic Belt," IJERPH, MDPI, vol. 20(1), pages 1-21, December.

    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. Yang Tang & Yongbo Yuan & Qingyu Zhong, 2021. "Evaluation of Land Comprehensive Carrying Capacity and Spatio-Temporal Analysis of the Harbin-Changchun Urban Agglomeration," IJERPH, MDPI, vol. 18(2), pages 1-19, January.
    2. Haijun Bao & Chengcheng Wang & Lu Han & Shaohua Wu & Liming Lou & Baogen Xu & Yanfang Liu, 2020. "Resources and Environmental Pressure, Carrying Capacity, And Governance: A Case Study of Yangtze River Economic Belt," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    3. Wenzhu Luo & Liyin Shen & Lingyu Zhang & Xia Liao & Conghui Meng & Chi Jin, 2022. "A Load-Carrier Perspective Method for Evaluating Land Resources Carrying Capacity," IJERPH, MDPI, vol. 19(9), pages 1-21, May.
    4. Jia Gao & Rongrong Zhao & Yuxin Zhan, 2022. "Land Comprehensive Carrying Capacity of Major Grain-Producing Areas in Northeast China: Spatial–Temporal Evolution, Obstacle Factors and Regulatory Policies," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
    5. Yu Liu & Fangchen Shi & Hongman He & Liyin Shen & Wenzhu Luo & Lingyun Sun, 2021. "Study on the Matching Degree between Land Resources Carrying Capacity and Industrial Development in Main Cities of Xinjiang, China," Sustainability, MDPI, vol. 13(19), pages 1-17, September.
    6. 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.
    7. Maurizio Zanardi, 2004. "Antidumping law as a collusive device," Canadian Journal of Economics, Canadian Economics Association, vol. 37(1), pages 95-122, February.
    8. Zheng LU & Xiang DENG, 2017. "Regional Specialization: New Methods Of Measurement And The Trends In China 1987-2007," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 17(2), pages 119-134.
    9. Peng Wang & Xiaoyan Lin & Dajun Dai, 2017. "Spatiotemporal Agglomeration of Real-Estate Industry in Guangzhou, China," Sustainability, MDPI, vol. 9(8), pages 1-15, August.
    10. Gao, Ting, 2004. "Regional industrial growth: evidence from Chinese industries," Regional Science and Urban Economics, Elsevier, vol. 34(1), pages 101-124, January.
    11. Agarwalla, Astha, 2011. "Agglomeration Economies and Productivity Growth in India," IIMA Working Papers WP2011-01-08, Indian Institute of Management Ahmedabad, Research and Publication Department.
    12. Opschoor, J. (Hans) B., 1995. "Ecospace and the fall and rise of throughput intensity," Ecological Economics, Elsevier, vol. 15(2), pages 137-140, November.
    13. Wang, Xu & Zhang, Xiaobo & Xie, Zhuan & Huang, Yiping, 2016. "Roads to innovation: Firm-level evidence from China:," IFPRI discussion papers 1542, International Food Policy Research Institute (IFPRI).
    14. Adriano Borges Costa & Ciro Biderman, 2016. "A Dinâmica Da Concentração Do Emprego Industrial No Brasil (1991-2011) E O Ciclo De Vida Das Empresas," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 180, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    15. Kaika, Dimitra & Zervas, Efthimios, 2013. "The environmental Kuznets curve (EKC) theory. Part B: Critical issues," Energy Policy, Elsevier, vol. 62(C), pages 1403-1411.
    16. Mohamed Amara & Khaled Thabet, 2019. "Firm and regional factors of productivity: a multilevel analysis of Tunisian manufacturing," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 63(1), pages 25-51, August.
    17. Yanping Yang & Jianjun Chen & Renjie Huang & Zihao Feng & Guoqing Zhou & Haotian You & Xiaowen Han, 2022. "Construction of Ecological Security Pattern Based on the Importance of Ecological Protection—A Case Study of Guangxi, a Karst Region in China," IJERPH, MDPI, vol. 19(9), pages 1-22, May.
    18. Bahar, Dany & Rosenow, Samuel & Stein, Ernesto & Wagner, Rodrigo, 2019. "Export take-offs and acceleration: Unpacking cross-sector linkages in the evolution of comparative advantage," World Development, Elsevier, vol. 117(C), pages 48-60.
    19. Bradford David F. & Fender Rebecca A & Shore Stephen H. & Wagner Martin, 2005. "The Environmental Kuznets Curve: Exploring a Fresh Specification," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 4(1), pages 1-28, June.
    20. Ghimire, Narishwar & Woodward, Richard T., 2013. "Under- and over-use of pesticides: An international analysis," Ecological Economics, Elsevier, vol. 89(C), pages 73-81.

    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:jijerp:v:19:y:2022:i:14:p:8240-:d:856803. 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.