IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i10p2786-d231450.html
   My bibliography  Save this article

Exploring the Spatial Pattern and Influencing Factors of Land Carrying Capacity in Wuhan

Author

Listed:
  • Nana Yang

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

  • Jiansong Li

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

  • Binbin Lu

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

  • Minghai Luo

    (Monitoring of Wuhan Geographical Conditions group in Wuhan Geomatics Institute, Wuhan 430079, China)

  • Linze Li

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
    School of Public Health, University of Maryland, College Park, MD 20742-2611, USA)

Abstract

Land carrying capacity is an important factor for urban sustainable development. It provides essential insights into land resource allocation and management. In this article, we propose a framework to evaluate land carrying capacity with multiple data sources from the first geographical census and socioeconomic statistics. In particular, an index, Land Resource Pressure ( LRP ), is proposed to evaluate the land carrying capacity, and a case study was carried out in Wuhan. The LRP of Wuhan was calculated on 250 m * 250 m grids, and showed a circularly declining pattern from central to outer areas. We collected its influencing factors in terms of nature resources, economy, transportation and urban construction, and then analyzed its causes via geographically weighted (GW) models. Firstly, pair-wise correlations between LRP and each influencing factor were explored via the GW correlation coefficients. These local estimates provide an important precursor for the following quantitative analysis via the GW regression (GWR) technique. The GWR coefficient estimates interpret the influences on LRP in a localized view. Results show that per capita gross domestic product (PerGDP ) showed a higher absolute estimate among all factors, which proves that PerGDP has a relieving effect on LRP , especially in the southwestern areas. Overall, this study provides a technical framework to evaluate land carrying capacity with multi-source data sets and explore its localized influences via GW models, which could provide practical guidance for similar studies in other cities.

Suggested Citation

  • Nana Yang & Jiansong Li & Binbin Lu & Minghai Luo & Linze Li, 2019. "Exploring the Spatial Pattern and Influencing Factors of Land Carrying Capacity in Wuhan," Sustainability, MDPI, vol. 11(10), pages 1-16, May.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:10:p:2786-:d:231450
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/10/2786/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/10/2786/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. Stewart Fotheringham & Taylor M. Oshan, 2016. "Geographically weighted regression and multicollinearity: dispelling the myth," Journal of Geographical Systems, Springer, vol. 18(4), pages 303-329, October.
    2. Cairns, Robert D. & Martinet, Vincent, 2014. "An environmental-economic measure of sustainable development," European Economic Review, Elsevier, vol. 69(C), pages 4-17.
    3. Zhang, Jianjun & Fu, Meichen & Zhang, Zhongya & Tao, Jin & Fu, Wei, 2014. "A trade-off approach of optimal land allocation between socio-economic development and ecological stability," Ecological Modelling, Elsevier, vol. 272(C), pages 175-187.
    4. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    5. Shijie Li & Chunshan Zhou & Shaojian Wang & Shuang Gao & Zhitao Liu, 2019. "Spatial Heterogeneity in the Determinants of Urban Form: An Analysis of Chinese Cities with a GWR Approach," Sustainability, MDPI, vol. 11(2), pages 1-16, January.
    6. Gollini, Isabella & Lu, Binbin & Charlton, Martin & Brunsdon, Christopher & Harris, Paul, 2015. "GWmodel: An R Package for Exploring Spatial Heterogeneity Using Geographically Weighted Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i17).
    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. 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. 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.
    3. Huimin Ji & Yunlong Peng & Wowo Ding, 2019. "A Quantitative Study of Geometric Characteristics of Urban Space Based on the Correlation with Microclimate," Sustainability, MDPI, vol. 11(18), pages 1-13, September.
    4. Alexandre B. Gonçalves, 2021. "Spatial Analysis and Geographic Information Systems as Tools for Sustainability Research," Sustainability, MDPI, vol. 13(2), pages 1-3, January.
    5. Huicong Jia & Fang Chen & Donghua Pan, 2019. "Disaster Chain Analysis of Avalanche and Landslide and the River Blocking Dam of the Yarlung Zangbo River in Milin County of Tibet on 17 and 29 October 2018," IJERPH, MDPI, vol. 16(23), pages 1-12, November.
    6. 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.
    7. Xinhao Min & Yanning Wang & Jun Chen, 2022. "Resource Carrying Capacity Evaluation Based on Fuzzy Evaluation: Validation Using Karst Landscape Region in Southwest China," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
    8. Daxue KAN & Weichiao HUANG, 2019. "Empirical Study of the Impact of Outward Foreign Direct Investment on Water Footprint Benefit in China," Sustainability, MDPI, vol. 11(16), pages 1-16, August.
    9. Zhimin Zhang & Guoli Ou & Ayman Elshkaki & Ruilin Liu, 2022. "Evaluation of Regional Carrying Capacity under Economic-Social-Resource-Environment Complex System: A Case Study of the Yangtze River Economic Belt," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    10. 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.
    11. Yingying Zhang & Yigang Wei & Jian Zhang, 2021. "Overpopulation and urban sustainable development—population carrying capacity in Shanghai based on probability-satisfaction evaluation method," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 3318-3337, March.
    12. 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.

    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. Paul Harris & Bruno Lanfranco & Binbin Lu & Alexis Comber, 2020. "Influence of Geographical Effects in Hedonic Pricing Models for Grass-Fed Cattle in Uruguay," Agriculture, MDPI, vol. 10(7), pages 1-17, July.
    2. Alexis Comber & Paul Harris, 2018. "Geographically weighted elastic net logistic regression," Journal of Geographical Systems, Springer, vol. 20(4), pages 317-341, October.
    3. Li, Mengya & Kwan, Mei-Po & Hu, Wenyan & Li, Rui & Wang, Jun, 2023. "Examining the effects of station-level factors on metro ridership using multiscale geographically weighted regression," Journal of Transport Geography, Elsevier, vol. 113(C).
    4. Yigong Hu & Binbin Lu & Yong Ge & Guanpeng Dong, 2022. "Uncovering spatial heterogeneity in real estate prices via combined hierarchical linear model and geographically weighted regression," Environment and Planning B, , vol. 49(6), pages 1715-1740, July.
    5. Rémy Le Boennec & Julie Bulteau & Thierry Feuillet, 2022. "The role of commuter rail accessibility in the formation of residential land values: exploring spatial heterogeneity in peri-urban and remote areas," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 69(1), pages 163-186, August.
    6. Xin Lao & Hengyu Gu, 2020. "Unveiling various spatial patterns of determinants of hukou transfer intentions in China: A multi‐scale geographically weighted regression approach," Growth and Change, Wiley Blackwell, vol. 51(4), pages 1860-1876, December.
    7. Chen Xie & Dexin Yu & Ciyun Lin & Xiaoyu Zheng & Bo Peng, 2022. "Exploring the Spatiotemporal Impacts of the Built Environment on Taxi Ridership Using Multisource Data," Sustainability, MDPI, vol. 14(10), pages 1-24, May.
    8. Sisman, S. & Aydinoglu, A.C., 2022. "A modelling approach with geographically weighted regression methods for determining geographic variation and influencing factors in housing price: A case in Istanbul," Land Use Policy, Elsevier, vol. 119(C).
    9. Ghislain Geniaux, 2024. "Speeding up estimation of spatially varying coefficients models," Journal of Geographical Systems, Springer, vol. 26(3), pages 293-327, July.
    10. Alexis Comber & Khanh Chi & Man Q Huy & Quan Nguyen & Binbin Lu & Hoang H Phe & Paul Harris, 2020. "Distance metric choice can both reduce and induce collinearity in geographically weighted regression," Environment and Planning B, , vol. 47(3), pages 489-507, March.
    11. Chang-Lin Mei & Feng Chen & Wen-Tao Wang & Peng-Cheng Yang & Si-Lian Shen, 2021. "Efficient estimation of heteroscedastic mixed geographically weighted regression models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 66(1), pages 185-206, February.
    12. Pulugurtha, Srinivas S. & Mathew, Sonu, 2021. "Modeling AADT on local functionally classified roads using land use, road density, and nearest nonlocal road data," Journal of Transport Geography, Elsevier, vol. 93(C).
    13. Yanzhao Wang & Jianfei Cao, 2023. "Examining the Effects of Socioeconomic Development on Fine Particulate Matter (PM2.5) in China’s Cities Based on Spatial Autocorrelation Analysis and MGWR Model," IJERPH, MDPI, vol. 20(4), pages 1-23, February.
    14. Cairns, Robert D. & Del Campo, Stellio & Martinet, Vincent, 2019. "Sustainability of an economy relying on two reproducible assets," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 145-160.
    15. Cairns, Robert D. & Martinet, Vincent, 2021. "Growth and long-run sustainability," Environment and Development Economics, Cambridge University Press, vol. 26(4), pages 381-402, August.
    16. Wang, Xiaoxi & Zhang, Yaojun & Yu, Danlin & Qi, Jinghan & Li, Shujing, 2022. "Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China," Land Use Policy, Elsevier, vol. 119(C).
    17. Bingkui Qiu & Shasha Lu & Min Zhou & Lu Zhang & Yu Deng & Ci Song & Zuo Zhang, 2015. "A Hybrid Inexact Optimization Method for Land-Use Allocation in Association with Environmental/Ecological Requirements at a Watershed Level," Sustainability, MDPI, vol. 7(4), pages 1-25, April.
    18. Hengyu Gu & Hanchen Yu & Mehak Sachdeva & Ye Liu, 2021. "Analyzing the distribution of researchers in China: An approach using multiscale geographically weighted regression," Growth and Change, Wiley Blackwell, vol. 52(1), pages 443-459, March.
    19. Shichao Lu & Zhihua Zhang & M. James C. Crabbe & Prin Suntichaikul, 2024. "Effects of Urban Land-Use Planning on Housing Prices in Chiang Mai, Thailand," Land, MDPI, vol. 13(8), pages 1-13, July.
    20. Jin, Peizhen & Mangla, Sachin Kumar & Song, Malin, 2021. "Moving towards a sustainable and innovative city: Internal urban traffic accessibility and high-level innovation based on platform monitoring data," International Journal of Production Economics, Elsevier, vol. 235(C).

    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:11:y:2019:i:10:p:2786-:d:231450. 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.