IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i7p1003-d853824.html
   My bibliography  Save this article

Land Use Optimization for Coastal Urban Agglomerations Based on Economic and Ecological Gravitational Linkages and Accessibility

Author

Listed:
  • Tingting Pan

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China)

  • Fengqin Yan

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Fenzhen Su

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China)

  • Vincent Lyne

    (IMAS-Hobart, University of Tasmania, Hobart, TAS 7004, Australia)

  • Chaodong Zhou

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Urban agglomerations (UA) are attracting increasing research attention as a global emergent phenomenon, whereby regional collaborative linkages between cities attracts and agglomerates development. However, these studies also acknowledge that ecological values may be negatively impacted by re-development, ecological fragmentation, and proximity or downstream impacts. Sustainable development, therefore, requires balancing forces from economic attraction and ecological repulsion. Forces similar to economic ones may also operate in attracting ecological enhancement towards higher-valued ecological regions; however, research regarding the role of the self-collaborative gravity-like forces shaping UA is limited in land use optimization. To assist planners, this study developed a new multi-objective land use optimization of UA that explored the intensity of economic ties and ecological gradients using the multi-objective NSGA-II algorithm. In this model, economic linkage intensity (ELI) and accessibility were used to calculate a modified GDP (gross domestic product), while the NDVI (normalized difference vegetation index) was used for the modified ESV (ecosystem services value). Spatial allocation with implicit economic accessibility relationships was enhanced through a two-step mutation operator, including a “gravity flip” spatial orientation factor. Compared to the standard NSGA-II algorithm, models of future land use of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in 2030 have shown that the modified GDP value in our model increased by 7.41%, while the conversion rate of high-density vegetation reduced by 7.92%. The results highlighted the importance of linkage and accessibility factors in enhancing the clustering of cities. In tandem, the modified ESV also enhances ecosystem services contributions of higher value vegetated land through decentralized built-up developments. The proposed model provides managers with a comprehensive and efficient land use solution model that accounts for intrinsic linkage factors shaping the development of compact urban agglomerations.

Suggested Citation

  • Tingting Pan & Fengqin Yan & Fenzhen Su & Vincent Lyne & Chaodong Zhou, 2022. "Land Use Optimization for Coastal Urban Agglomerations Based on Economic and Ecological Gravitational Linkages and Accessibility," Land, MDPI, vol. 11(7), pages 1-18, July.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:7:p:1003-:d:853824
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/7/1003/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/7/1003/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bowen Chen & Changyan Wu & Xianjin Huang & Xuefeng Yang, 2020. "Examining the Relationship between Urban Land Expansion and Economic Linkage Using Coupling Analysis: A Case Study of the Yangtze River Economic Belt, China," Sustainability, MDPI, vol. 12(3), pages 1-21, February.
    2. Md. Mostafizur Rahman & György Szabó, 2021. "A Geospatial Approach to Measure Social Benefits in Urban Land Use Optimization Problem," Land, MDPI, vol. 10(12), pages 1-23, December.
    3. Xiaoe Ding & Minrui Zheng & Xinqi Zheng, 2021. "The Application of Genetic Algorithm in Land Use Optimization Research: A Review," Land, MDPI, vol. 10(5), pages 1-21, May.
    4. Gao, Xin & Zhang, Anlu & Sun, Zhanli, 2020. "How regional economic integration influence on urban land use efficiency？ A case study of Wuhan metropolitan area, China," Land Use Policy, Elsevier, vol. 90(C).
    5. Daniel Caparros‐Midwood & Stuart Barr & Richard Dawson, 2017. "Spatial Optimization of Future Urban Development with Regards to Climate Risk and Sustainability Objectives," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2164-2181, November.
    6. Liping Liu, 2020. "Use Case Optimization," World Scientific Book Chapters, in: REQUIREMENTS MODELING AND CODING An Object-Oriented Approach, chapter 11, pages 255-278, World Scientific Publishing Co. Pte. Ltd..
    7. Shiqi Huang & Furui Xi & Yiming Chen & Ming Gao & Xu Pan & Ci Ren, 2021. "Land Use Optimization and Simulation of Low-Carbon-Oriented—A Case Study of Jinhua, China," Land, MDPI, vol. 10(10), pages 1-18, September.
    8. Dan Su & Xiaoqian Fang & Qing Wu & Yu Cao, 2022. "Exploring the Spatiotemporal Integration Evolution of the Urban Agglomeration through City Networks," Land, MDPI, vol. 11(4), pages 1-18, 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. Zhen Wang & Xupeng Zhang & Chaozheng Zhang & Qing Yang, 2022. "How Regional Integration Affects Urban Green Development Efficiency: Evidence from Urban Agglomeration in the Middle Reaches of the Yangtze River," IJERPH, MDPI, vol. 19(13), pages 1-16, June.
    2. Xujing Yu & Liping Shan & Yuzhe Wu, 2021. "Land Use Optimization in a Resource-Exhausted City Based on Simulation of the F-E-W Nexus," Land, MDPI, vol. 10(10), pages 1-22, September.
    3. Xinxin Fu & Xiaofeng Wang & Jitao Zhou & Jiahao Ma, 2021. "Optimizing the Production-Living-Ecological Space for Reducing the Ecosystem Services Deficit," Land, MDPI, vol. 10(10), pages 1-17, September.
    4. Ke Huang & Martin Dallimer & Lindsay C. Stringer & Anlu Zhang & Ting Zhang, 2021. "Does Economic Agglomeration Lead to Efficient Rural to Urban Land Conversion? An Examination of China’s Metropolitan Area Development Strategy," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    5. Lisha Pan & Hangang Hu & Xin Jing & Yang Chen & Guan Li & Zhongguo Xu & Yuefei Zhuo & Xueqi Wang, 2022. "The Impacts of Regional Cooperation on Urban Land-Use Efficiency: Evidence from the Yangtze River Delta, China," Land, MDPI, vol. 11(6), pages 1-16, June.
    6. Ma, Wen & Fang, Zhuoqiong & Zhang, Xiangfeng, 2023. "Comparative analysis of structural characteristics of China's 18 typical urban agglomerations based on flows of various elements," Ecological Modelling, Elsevier, vol. 479(C).
    7. Bin Duan & Xuanming Ji, 2021. "Can Carbon Finance Optimize Land Use Efficiency? The Example of China’s Carbon Emissions Trading Policy," Land, MDPI, vol. 10(9), pages 1-18, September.
    8. Yin Ma & Minrui Zheng & Xinqi Zheng & Yi Huang & Feng Xu & Xiaoli Wang & Jiantao Liu & Yongqiang Lv & Wenchao Liu, 2023. "Land Use Efficiency Assessment under Sustainable Development Goals: A Systematic Review," Land, MDPI, vol. 12(4), pages 1-21, April.
    9. Xinhai Lu & Zhenxing Shi & Jia Li & Junhao Dong & Mingjie Song & Jiao Hou, 2022. "Research on the Impact of Factor Flow on Urban Land Use Efficiency from the Perspective of Urbanization," Land, MDPI, vol. 11(3), pages 1-17, March.
    10. Chao Wang & Jianing Wang & Le Ma & Mingming Jia & Jiaying Chen & Zhenfeng Shao & Nengcheng Chen, 2024. "Prediction Modeling and Driving Factor Analysis of Spatial Distribution of CO 2 Emissions from Urban Land in the Yangtze River Economic Belt, China," Land, MDPI, vol. 13(9), pages 1-21, September.
    11. Aurel Pera, 2020. "Assessing Sustainability Behavior and Environmental Performance of Urban Systems: A Systematic Review," Sustainability, MDPI, vol. 12(17), pages 1-19, September.
    12. Mengchao Yao & Yihua Zhang, 2021. "Evaluation and Optimization of Urban Land-Use Efficiency: A Case Study in Sichuan Province of China," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    13. Yao Lu & Min Zhou & Guoliang Ou & Zuo Zhang & Li He & Yuxiang Ma & Chaonan Ma & Jiating Tu & Siqi Li, 2021. "Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty," IJERPH, MDPI, vol. 18(24), pages 1-19, December.
    14. Menghan Zhang & Suocheng Dong & Fujia Li & Shuangjie Xu & Kexin Guo & Qian Liu, 2022. "Spatial–Temporal Evolution and Improvement Measures of Embodied Carbon Emissions in Interprovincial Trade for Coal Energy Supply Bases: Case Study of Anhui, China," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    15. You, Lie & Li, Yurui & Wang, Rui & Pan, Haozhi, 2020. "A benefit evaluation model for build-up land use in megacity suburban districts," Land Use Policy, Elsevier, vol. 99(C).
    16. Wenli Dong & Xinyue Gao & Xiaowei Chen & Lihan Lin, 2023. "Industrial Park Renovation Strategy in a Poverty-Alleviated County Based on Inefficient Land Evaluation," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    17. Gregory Levitin & Liudong Xing & Yuanshun Dai, 2020. "Mission Abort Policy for Systems with Observable States of Standby Components," Risk Analysis, John Wiley & Sons, vol. 40(10), pages 1900-1912, October.
    18. Tingting Pan & Yu Zhang & Fengqin Yan & Fenzhen Su, 2023. "Collaborative Optimal Allocation of Urban Land Guide by Land Ecological Suitability: A Case Study of Guangdong–Hong Kong–Macao Greater Bay Area," Land, MDPI, vol. 12(4), pages 1-17, March.
    19. Xinhai Lu & Yifeng Tang & Shangan Ke, 2021. "Does the Construction and Operation of High-Speed Rail Improve Urban Land Use Efficiency? Evidence from China," Land, MDPI, vol. 10(3), pages 1-15, March.
    20. Tian Liang & Fei Yang & Yinchen Luo & Mengying Fang & Xi Huang & Zhiyong Zhang & Chuanhao Wen & Xiaohong Ren, 2022. "The Synchronous Development Pattern and Type Division of Functional Coupling Coordination and Human Activity Intensity Based on the “Production–Living–Ecological” Space Perspective: A Case Study of Wa," Land, MDPI, vol. 11(11), pages 1-17, October.

    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:jlands:v:11:y:2022:i:7:p:1003-:d:853824. 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.