IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v75y2015i1p95-118.html
   My bibliography  Save this article

Agent-based modeling and simulations of land-use and land-cover change according to ant colony optimization: a case study of the Erhai Lake Basin, China

Author

Listed:
  • Xu QuanLi
  • Yang Kun
  • Wang GuiLin
  • Yang YuLian

Abstract

The land-use structure and ecological service functions of the Erhai Lake Watershed are being altered by rapid socioeconomic development and urbanization, which will ultimately lead to the generation and aggravation of agricultural and urban non-point source pollution over the entire region. Therefore, the relationships between human activities and land-use/land-cover changes (LUCCs) must be studied to support scientific decisions regarding reasonable land planning and land use. This paper combines geographic information system technology for spatial analysis and the ant colony optimization artificial intelligence algorithm. Moreover, this study applies agent-based modeling to establish a spatiotemporal process model for LUCCs that effectively simulates the dynamic land-use changes in the basin. A selection is first made and evaluated for dynamic land-use change impact factors. Then, the agent classes and their rules in the LUCC processes are established. The program is designed using the Java programming language, and the model is implemented based on the Repast modeling platform. Finally, the models are validated, and the simulated results are analyzed and discussed. Some conclusions were drawn from the experiments, as well as some policies on land use were suggested. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Xu QuanLi & Yang Kun & Wang GuiLin & Yang YuLian, 2015. "Agent-based modeling and simulations of land-use and land-cover change according to ant colony optimization: a case study of the Erhai Lake Basin, China," 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. 75(1), pages 95-118, January.
    • Handle: RePEc:spr:nathaz:v:75:y:2015:i:1:p:95-118
    DOI: 10.1007/s11069-014-1303-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-014-1303-4
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11069-014-1303-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nina Schwarz & Daniel Kahlenberg & Dagmar Haase & Ralf Seppelt, 2012. "ABMland - a Tool for Agent-Based Model Development on Urban Land Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-8.
    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. Opelele Omeno Michel & Yu Ying & Fan Wenyi & Chen Chen & Kachaka Sudi Kaiko, 2021. "Examining Land Use/Land Cover Change and Its Prediction Based on a Multilayer Perceptron Markov Approach in the Luki Biosphere Reserve, Democratic Republic of Congo," Sustainability, MDPI, vol. 13(12), pages 1-24, June.
    2. Bhanage Vinayak & Han Soo Lee & Shirishkumar Gedem, 2021. "Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model," Sustainability, MDPI, vol. 13(2), pages 1-22, January.
    3. Huafei Yu & Yaolong Zhao & Yingchun Fu, 2019. "Optimization of Impervious Surface Space Layout for Prevention of Urban Rainstorm Waterlogging: A Case Study of Guangzhou, China," IJERPH, MDPI, vol. 16(19), pages 1-28, September.
    4. Ghazali, Mahboubeh & Honar, Tooraj & Nikoo, Mohammad Reza, 2018. "A hybrid TOPSIS-agent-based framework for reducing the water demand requested by stakeholders with considering the agents’ characteristics and optimization of cropping pattern," Agricultural Water Management, Elsevier, vol. 199(C), pages 71-85.

    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. Yajun Ma & Ping Zhang & Kaixu Zhao & Yong Zhou & Sidong Zhao, 2022. "A Dynamic Performance and Differentiation Management Policy for Urban Construction Land Use Change in Gansu, China," Land, MDPI, vol. 11(6), pages 1-31, June.
    2. SeHoon Lee & Jeong Hee Hong & Jang Won Bae & Il-Chul Moon, 2015. "Impact of Population Relocation to City Commerce: Micro-Level Estimation with Validated Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-5.
    3. Ying Long & Yongping Zhang, 2015. "Land-use pattern scenario analysis using planner agents," Environment and Planning B, , vol. 42(4), pages 615-637, July.

    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:spr:nathaz:v:75:y:2015:i:1:p:95-118. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.