• DocumentCode
    1996912
  • Title

    Simulation for Land Use Dynamic Change of Dian-Chi Lake Watershed Using Agent-Based Modeling

  • Author

    Quan-li Xu ; Kun Yang ; Jun-hua Yi ; Gui-lin Wang

  • Author_Institution
    Fac. of Tourism & Geographic Sci., Yunnan Normal Univ., Kunming, China
  • fYear
    2013
  • fDate
    3-4 Dec. 2013
  • Firstpage
    40
  • Lastpage
    44
  • Abstract
    The land use structure and biological service function of Dian-chi lake watershed are being changed by the rapid development of social economy and urbanization, which finally leads to the generation and aggravation of agriculture and urban non-point source pollution in whole basin. Thereby, it is necessary to study the relationship and spatiotemporal process between human activities and land use/cover change (LUCC) of watershed, which is hopeful to offer the scientific decision support for reasonable land planning and land use. Through being combined with GIS technologies of spatial analysis and using the artificial intelligence algorithm called Ant Colony Optimization(ACO) for optimizing, this paper has applied the method of Agent-based modeling to establish the spatiotemporal process model of LUCC in order to simulating the dynamic change of land use in whole watershed. Generally, what has been explored is as fellows. Firstly, make a choice and evaluation for impact factors of land dynamic use, and then create the classes of Agents and their rules in LUCC process. Based on the Java language and Repast platform of modeling, the program design, implementation and simulation of model are given in detail. And finally, the validation for model and analysis for the simulating results are also discussed clearly. We could infer three conclusions from the results of experience. Ant colony algorithm is effective to promote the science express for moving and decision of agents, and the simulating results have better accuracy in both mathematics and geometry than no using it. And the highest accuracy reaches 78.6% in numbers and 68.5% in shape similarity.
  • Keywords
    ant colony optimisation; artificial intelligence; geographic information systems; lakes; land use planning; simulation; socio-economic effects; ACO; Dian-Chi lake watershed; GIS technologies; LUCC; agent-based modeling; ant colony optimization; artificial intelligence; biological service function; land planning; land use dynamic change; land use structure; land use/cover change; rapid development; simulation; social economy; spatiotemporal process; urbanization; Analytical models; Biological system modeling; Computational modeling; Government; Mathematical model; Planning; Resistance; LUCC; REPAST; agent-based modeling; ant colony algorithm; simulating model; spatial analysis; watershed water environmental effect;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (GCIS), 2013 Fourth Global Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4799-2885-9
  • Type

    conf

  • DOI
    10.1109/GCIS.2013.13
  • Filename
    6805910