IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i11p1989-d1270337.html
   My bibliography  Save this article

Optimal Allocation of Territorial Space in the Minjiang River Basin Based on a Double Optimization Simulation Model

Author

Listed:
  • Ge Wang

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

  • Ziqi Zhou

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

  • Jianguo Xia

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

  • Dinghua Ou

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

  • Jianbo Fei

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

  • Shunya Gong

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

  • Yuxiao Xiang

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

Abstract

The unequal distribution of territorial space resources stands out as a leading cause of the human–land contradictions and environmental degradation. These issues are especially pronounced in the Minjiang River Basin, which exhibits significant regional disparities. In pursuit of solutions to these pressing problems and the identification of sustainable developmental pathways, this study presents an innovative territorial space double optimization simulation model. This model integrates quantity structure optimization and distribution pattern optimization, in order to comprehensively consider the optimization of territorial space allocation and build a new territorial space pattern for the Minjiang River Basin in 2030. On this basis, we employed the Patch-generating Land Use Simulation (PLUS) model and scenario analysis method to design the double optimization scenario and natural development scenario. By comparing these two scenarios, and calculating the ecological benefits (EB), economic benefits (ECB), carbon storage (CS), and comprehensive benefits (CB) achieved in different scenarios, the validity of the double optimization model was fully verified. The results indicated that: ① the loss of sub-ecological space (PeS) under the natural development scenario was significantly larger than that under the double optimization scenario, and the loss should be mainly attributed to the large expansion of production space (PS) and living space (LS); ② the area of ecological space (ES) has reduced since 2020, but less area was lost and the retention rate was higher under the double optimization scenario; ③ the natural development scenario made the research region gain more ECB, but it also resulted in the loss of more EB and CS, whereas the Minjiang River Basin under the double optimization scenario was able to effectively balance the relationship among the three, thus achieving the best CB. The research findings provide strong scientific support for alleviating the human–land contradictions, protecting the ecological security in the basin, and promoting the sustainable development of the region.

Suggested Citation

  • Ge Wang & Ziqi Zhou & Jianguo Xia & Dinghua Ou & Jianbo Fei & Shunya Gong & Yuxiao Xiang, 2023. "Optimal Allocation of Territorial Space in the Minjiang River Basin Based on a Double Optimization Simulation Model," Land, MDPI, vol. 12(11), pages 1-26, October.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:11:p:1989-:d:1270337
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/11/1989/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/12/11/1989/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Weimin YANG, 2020. "Ecological Civilization is a New State of Civilization Featuring the Harmony between Man and Nature," Chinese Journal of Urban and Environmental Studies (CJUES), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 1-3, June.
    2. Muhammad Fahad Baqa & Fang Chen & Linlin Lu & Salman Qureshi & Aqil Tariq & Siyuan Wang & Linhai Jing & Salma Hamza & Qingting Li, 2021. "Monitoring and Modeling the Patterns and Trends of Urban Growth Using Urban Sprawl Matrix and CA-Markov Model: A Case Study of Karachi, Pakistan," Land, MDPI, vol. 10(7), pages 1-17, July.
    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. Milad Asadi & Amir Oshnooei-Nooshabadi & Samira-Sadat Saleh & Fattaneh Habibnezhad & Sonia Sarafraz-Asbagh & John Lodewijk Van Genderen, 2022. "Urban Sprawl Simulation Mapping of Urmia (Iran) by Comparison of Cellular Automata–Markov Chain and Artificial Neural Network (ANN) Modeling Approach," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    2. Oznur Isinkaralar & Kaan Isinkaralar & Dilara Yilmaz, 2023. "Climate-related spatial reduction risk of agricultural lands on the Mediterranean coast in Türkiye and scenario-based modelling of urban growth," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(11), pages 13199-13217, November.
    3. Yanan Li & Linghua Duo & Ming Zhang & Zhenhua Wu & Yanjun Guan, 2021. "Assessment and Estimation of the Spatial and Temporal Evolution of Landscape Patterns and Their Impact on Habitat Quality in Nanchang, China," Land, MDPI, vol. 10(10), pages 1-19, October.
    4. Sajjad Hussain & Linlin Lu & Muhammad Mubeen & Wajid Nasim & Shankar Karuppannan & Shah Fahad & Aqil Tariq & B. G. Mousa & Faisal Mumtaz & Muhammad Aslam, 2022. "Spatiotemporal Variation in Land Use Land Cover in the Response to Local Climate Change Using Multispectral Remote Sensing Data," Land, MDPI, vol. 11(5), pages 1-19, April.
    5. Mirza Waleed & Muhammad Sajjad & Anthony Owusu Acheampong & Md. Tauhidul Alam, 2023. "Towards Sustainable and Livable Cities: Leveraging Remote Sensing, Machine Learning, and Geo-Information Modelling to Explore and Predict Thermal Field Variance in Response to Urban Growth," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    6. Umer Khalil & Umar Azam & Bilal Aslam & Israr Ullah & Aqil Tariq & Qingting Li & Linlin Lu, 2022. "Developing a Spatiotemporal Model to Forecast Land Surface Temperature: A Way Forward for Better Town Planning," Sustainability, MDPI, vol. 14(19), pages 1-21, September.
    7. Jing Liu & Chunchun Hu & Xionghua Kang & Fei Chen, 2023. "A Loosely Coupled Model for Simulating and Predicting Land Use Changes," Land, MDPI, vol. 12(1), pages 1-19, January.
    8. Xiaoxiao Wang & Huafu Zhao & Jiacheng Qian & Xiao Li & Congjie Cao & Zhe Feng & Yiqing Cui, 2024. "Sustainable Land Use Diagnosis Based on the Perspective of Coupling Socioeconomy and Ecology in the Xiongan New Area, China," Land, MDPI, vol. 13(1), pages 1-22, January.
    9. Hoyong Kim & Donghyun Kim, 2022. "Changes in Urban Growth Patterns in Busan Metropolitan City, Korea: Population and Urbanized Areas," Land, MDPI, vol. 11(8), pages 1-18, August.
    10. Iwona Cieślak & Andrzej Biłozor & Luca Salvati, 2022. "Land as a Basis for Recent Progress in the Study of Urbanization Dynamics," Land, MDPI, vol. 11(1), pages 1-4, January.
    11. Fahad Ahmed Shaikh & Mir Aftab Hussain Talpur & Imtiaz Ahmed Chandio & Saima Kalwar, 2022. "Factors Influencing Residential Location Choice towards Mixed Land-Use Development: An Empirical Evidence from Pakistan," Sustainability, MDPI, vol. 14(21), pages 1-25, November.
    12. Sandeep Kumar & Fulena Rajak, 2023. "Assessment of Urban Green Open Spaces of Micro- and Meso-Level Zones, Based on the Growth Pattern: Case of Patna City," Sustainability, MDPI, vol. 15(2), pages 1-29, January.

    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:12:y:2023:i:11:p:1989-:d:1270337. 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.