IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i15p9281-d875105.html
   My bibliography  Save this article

Simulation of Land Use Pattern Based on Land Ecological Security: A Case Study of Guangzhou, China

Author

Listed:
  • Lesong Zhao

    (School of Public Administration, South China Agricultural University, Guangzhou 510642, China
    These authors have contributed equally to this work.)

  • Guangsheng Liu

    (School of Public Administration, South China Agricultural University, Guangzhou 510642, China
    Guangdong Province Key Laboratory of Land Use and Consolidation, Guangzhou 510642, China
    Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Guangzhou 510700, China
    These authors have contributed equally to this work.)

  • Chunlong Xian

    (School of Public Administration, South China Agricultural University, Guangzhou 510642, China)

  • Jiaqi Nie

    (School of Public Administration, South China Agricultural University, Guangzhou 510642, China)

  • Yao Xiao

    (School of Public Administration, South China Agricultural University, Guangzhou 510642, China)

  • Zhigang Zhou

    (School of Public Administration, South China Agricultural University, Guangzhou 510642, China)

  • Xiting Li

    (School of Public Administration, South China Agricultural University, Guangzhou 510642, China)

  • Hongmei Wang

    (School of Public Administration, South China Agricultural University, Guangzhou 510642, China
    Guangdong Province Key Laboratory of Land Use and Consolidation, Guangzhou 510642, China
    Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Guangzhou 510700, China)

Abstract

The process of rapid urbanization has intensified the conversion of different land use types, resulting in a substantial loss of ecological land and ecological security being threatened. In the context of China’s vigorous advocacy of an ecological civilization, it is important to explore future land use patterns under ecological security constraints to promote sustainable development. The insufficient consideration of land ecological security in existing land use pattern simulation studies makes it difficult to effectively promote improvement in the ecological security level. Therefore, we developed a land use simulation framework that integrates land ecological security. Taking the sustainable development of land ecosystems as the core, the land ecological security index (LESI) and ecological zoning (EZ) were determined by the pressure–state–response (PSR) model and the catastrophe progression method (CPM). Natural development (ND) and ecological protection (EP) scenarios were then constructed taking the LESI and EZ into consideration. The CA–Markov model was used to simulate the land use pattern of Guangzhou for 2030 under the two scenarios. The results showed that (1) the study area was divided into four categories: ecological core zone, ecological buffer zone, ecological optimization zone, and urban development zone, with area shares of 37.53%, 31.14%, 16.96%, and 14.37%, respectively. (2) In both scenarios, the construction land around the towns showed outward expansion; compared with the ND scenario, the construction land in the EP scenario decreased by 369.10 km 2 , and the woodland, grassland, and farmland areas increased by 337.04, 20.80, and 10.51 km 2 , respectively, which significantly improved the ecological security level. (3) In the EP scenario, the construction land in the ecological core zone, ecological buffer zone, and ecological optimization zone decreased by 85.49, 114.78, and 178.81 km 2 , respectively, and no new construction land was added in the ecological core zone, making the land use pattern of the EP scenario more reasonable. The results of the study have confirmed that the land use pattern simulation framework integrating land ecological security can effectively predict land use patterns in different future scenarios. This study can provide suggestions and guidance for managers to use in formulating ecological protection policies and preparing territorial spatial planning.

Suggested Citation

  • Lesong Zhao & Guangsheng Liu & Chunlong Xian & Jiaqi Nie & Yao Xiao & Zhigang Zhou & Xiting Li & Hongmei Wang, 2022. "Simulation of Land Use Pattern Based on Land Ecological Security: A Case Study of Guangzhou, China," IJERPH, MDPI, vol. 19(15), pages 1-20, July.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9281-:d:875105
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/15/9281/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/15/9281/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Wickramasuriya, Rohan Chandralal & Bregt, Arnold K. & van Delden, Hedwig & Hagen-Zanker, Alex, 2009. "The dynamics of shifting cultivation captured in an extended Constrained Cellular Automata land use model," Ecological Modelling, Elsevier, vol. 220(18), pages 2302-2309.
    3. Wang, Quan & Wang, Haijun & Chang, Ruihan & Zeng, Haoran & Bai, Xuepiao, 2022. "Dynamic simulation patterns and spatiotemporal analysis of land-use/land-cover changes in the Wuhan metropolitan area, China," Ecological Modelling, Elsevier, vol. 464(C).
    4. Li, Feixue & Li, Zhifeng & Chen, Honghua & Chen, Zhenjie & Li, Manchun, 2020. "An agent-based learning-embedded model (ABM-learning) for urban land use planning: A case study of residential land growth simulation in Shenzhen, China," Land Use Policy, Elsevier, vol. 95(C).
    5. Gomes, Eduardo & Abrantes, Patrícia & Banos, Arnaud & Rocha, Jorge, 2019. "Modelling future land use scenarios based on farmers’ intentions and a cellular automata approach," Land Use Policy, Elsevier, vol. 85(C), pages 142-154.
    6. Yong Zhu & Shihu Zhong & Ying Wang & Muhua Liu, 2021. "Land Use Evolution and Land Ecological Security Evaluation Based on AHP-FCE Model: Evidence from China," IJERPH, MDPI, vol. 18(22), pages 1-15, November.
    7. Xu, Hongtao & Song, Youcheng & Tian, Yi, 2022. "Simulation of land-use pattern evolution in hilly mountainous areas of North China: A case study in Jincheng," Land Use Policy, Elsevier, vol. 112(C).
    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. Mingyang Nan & Jun Chen, 2022. "Research Progress, Hotspots and Trends of Land Use under the Background of Ecological Civilization in China: Visual Analysis Based on the CNKI Database," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    2. Lindan Zhang & Wenfu Peng & Ji Zhang, 2023. "Assessment of Land Ecological Security from 2000 to 2020 in the Chengdu Plain Region of China," Land, MDPI, vol. 12(7), pages 1-28, July.

    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. Yue Wu & Zexu Han & Auwalu Faisal Koko & Siyuan Zhang & Nan Ding & Jiayang Luo, 2022. "Analyzing the Spatio-Temporal Dynamics of Urban Land Use Expansion and Its Influencing Factors in Zhejiang Province, China," IJERPH, MDPI, vol. 19(24), pages 1-24, December.
    2. 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.
    3. Xinbei Huang & Chengming Ye & Hongyu Tao & Junjie Zou & Yuzhan Zhou & Shufan Zheng, 2024. "Integrating Future Multi-Scenarios to Evaluate the Effectiveness of Ecological Restoration: A Case Study of the Yellow River Basin," Land, MDPI, vol. 13(7), pages 1-19, July.
    4. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    5. Han, Yu & Jia, Haifeng, 2017. "Simulating the spatial dynamics of urban growth with an integrated modeling approach: A case study of Foshan, China," Ecological Modelling, Elsevier, vol. 353(C), pages 107-116.
    6. Ustaoglu, E. & Sisman, S. & Aydınoglu, A.C., 2021. "Determining agricultural suitable land in peri-urban geography using GIS and Multi Criteria Decision Analysis (MCDA) techniques," Ecological Modelling, Elsevier, vol. 455(C).
    7. Changqing Sun & Yulong Bao & Battsengel Vandansambuu & Yuhai Bao, 2022. "Simulation and Prediction of Land Use/Cover Changes Based on CLUE-S and CA-Markov Models: A Case Study of a Typical Pastoral Area in Mongolia," Sustainability, MDPI, vol. 14(23), pages 1-21, November.
    8. Xiaochang Yang & Sinan Li & Congmou Zhu & Baiyu Dong & Hongwei Xu, 2021. "Simulating Urban Expansion Based on Ecological Security Pattern—A Case Study of Hangzhou, China," IJERPH, MDPI, vol. 19(1), pages 1-20, December.
    9. Zhang, Yan & Chang, Xia & Liu, Yanfang & Lu, Yanchi & Wang, Yiheng & Liu, Yaolin, 2021. "Urban expansion simulation under constraint of multiple ecosystem services (MESs) based on cellular automata (CA)-Markov model: Scenario analysis and policy implications," Land Use Policy, Elsevier, vol. 108(C).
    10. Ming Zhang & Xiaojie Liu & Dan Yan, 2023. "Land Use Conflicts Assessment in Xiamen, China under Multiple Scenarios," Land, MDPI, vol. 12(2), pages 1-16, February.
    11. Cláudia M. Viana & Jorge Rocha, 2020. "Evaluating Dominant Land Use/Land Cover Changes and Predicting Future Scenario in a Rural Region Using a Memoryless Stochastic Method," Sustainability, MDPI, vol. 12(10), pages 1-28, May.
    12. Marra, Alessandro & Antonelli, Paola & Agostinone, Stefano & Raucci, Domenico, 2018. "Opening Pandora's box of twenty years of research on energy policies: On the rise of a ‘technology-driven’ debate," Energy Policy, Elsevier, vol. 122(C), pages 542-550.
    13. Li, Long & Huang, Xianjin & Yang, Hong, 2023. "Optimizing land use patterns to improve the contribution of land use planning to carbon neutrality target," Land Use Policy, Elsevier, vol. 135(C).
    14. van Vliet, Jasper & Hagen-Zanker, Alex & Hurkens, Jelle & van Delden, Hedwig, 2013. "A fuzzy set approach to assess the predictive accuracy of land use simulations," Ecological Modelling, Elsevier, vol. 261, pages 32-42.
    15. Jiang, Xue & Li, Bingxin & Zhao, Hongyu & Zhang, Qiqi & Song, Xiaoya & Zhang, Haoran, 2022. "Examining the spatial simulation and land-use reorganisation mechanism of agricultural suburban settlements using a cellular-automata and agent-based model: Six settlements in China," Land Use Policy, Elsevier, vol. 120(C).
    16. Fengqiang Wu & Caijian Mo & Xiaojun Dai, 2022. "Analysis of the Driving Force of Land Use Change Based on Geographic Detection and Simulation of Future Land Use Scenarios," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    17. Luoman Pu & Jiuchun Yang & Lingxue Yu & Changsheng Xiong & Fengqin Yan & Yubo Zhang & Shuwen Zhang, 2021. "Simulating Land-Use Changes and Predicting Maize Potential Yields in Northeast China for 2050," IJERPH, MDPI, vol. 18(3), pages 1-21, January.
    18. Xiufeng Cao & Zhaoshun Liu & Shujie Li & Zhenjun Gao, 2022. "Integrating the Ecological Security Pattern and the PLUS Model to Assess the Effects of Regional Ecological Restoration: A Case Study of Hefei City, Anhui Province," IJERPH, MDPI, vol. 19(11), pages 1-19, May.
    19. Ge Song & Hongmei Zhang, 2021. "Cultivated Land Use Layout Adjustment Based on Crop Planting Suitability: A Case Study of Typical Counties in Northeast China," Land, MDPI, vol. 10(2), pages 1-19, January.
    20. Haixia Zhao & Binjie Gu & Xin Li & Mingjie Niu, 2024. "Evolution and Optimization Simulation of Coastal Chemical Industry Layout: A Case Study of Jiangsu Province, China," Land, MDPI, vol. 13(4), pages 1-18, March.

    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:15:p:9281-:d:875105. 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.