首页 | 本学科首页   官方微博 | 高级检索  
   检索      

基于元胞自动机的城市空间动态模拟
引用本文:詹云军,朱捷缘,严岩.基于元胞自动机的城市空间动态模拟[J].生态学报,2017,37(14):4864-4872.
作者姓名:詹云军  朱捷缘  严岩
作者单位:武汉理工大学, 资源与环境工程学院, 武汉 430070,武汉理工大学, 资源与环境工程学院, 武汉 430070;中国科学院生态环境研究中心, 城市与区域生态国家重点实验室, 北京 100085,中国科学院生态环境研究中心, 城市与区域生态国家重点实验室, 北京 100085
基金项目:中央高校基本科研业务费专项资金资助(2014-IV-141);长江科学院开放基金(CKWV2016403/KY);国家重点研发计划项目(2016YFC0502102)
摘    要:城市空间动态的模拟与预测可以为城市可持续发展规划与管理提供重要的参考依据。SLEUTH元胞自动机模型在城市空间模拟中较强的适用性和可移植性,该模型通过对历史数据的蒙特卡洛迭代自动寻找城市增长误差最小的参数组合,解决了传统元胞自动机模型中转换规则不易确定的问题。以武汉市为研究案例,运用SLEUTH模型进行了城市空间动态模拟与情景预测。2007年至2011年的城市空间模拟结果显示,模拟结果与实际历史数据可以获得良好的空间匹配度,Lee-Sallee形状指数均在0.6以上,显示SLEUTH元胞自动机模型经过本地化校正后具有较强的适用性和满意的模拟精度。进而,设置了现状趋势、基本保护、严格保护等3种情景对武汉2025年城市空间动态进行了预测,结果显示,各情景模式下城市居住用地均明显增长,农业用地、林地、水域等均有所减少;现状趋势情景和基本保护情景下农田、林地、水域减少的幅度较大,会加剧区域的生境破碎、耕地功能下降、水资源匮乏、湖滨湿地萎缩等生态问题,说明这两种情景不能有效满足城市生态系统健康和可持续发展的需要。严格保护情景下,城市居住用地扩张的程度得到了明显的控制,水域和林地得到了有效的保护,对于重要的自然生态系统组分保护及其服务能力维持可以起到显著作用。

关 键 词:城市扩展  土地利用  模拟  元胞自动机(SLEUTH模型)  武汉
收稿时间:2016/4/25 0:00:00

Dynamic simulation of urban space based on the cellular automata model
ZHAN Yunjun,ZHU Jieyuan and YAN Yan.Dynamic simulation of urban space based on the cellular automata model[J].Acta Ecologica Sinica,2017,37(14):4864-4872.
Authors:ZHAN Yunjun  ZHU Jieyuan and YAN Yan
Institution:Wuhan University of Technology, School of Resource and environmental engineering, Wuhan 430070, China,Wuhan University of Technology, School of Resource and environmental engineering, Wuhan 430070, China;State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China and State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Abstract:The dynamic simulation and prediction of urban space can provide an important reference for the planning and management of sustainable urban development. The cellular automata model SLEUTH has strong universality and portability in urban spatial simulation. It is based on the Monte Carlo iteration of urban historical data and is capable of automatically identifying urban growth parameters with minimum error, which has effectively resolved the difficulties encountered in determining the conversion rules when using the traditional cellular automata models. In this study, we applied the SLEUTH model to perform urban spatial simulation and prediction under different scenarios in Wuhan City. Our findings revealed that the urban spatial simulation results for the period 2007 to 2011 showed a strong correlation with actual historical data. The Lee-Sallee shape index was greater than 0.6, which proves that the SLEUTH model exhibits a strong universality and suitable simulation accuracy after local correction. Moreover, the urban dynamic changes in Wuhan in 2025 were predicted under three scenarios, namely, the current development trend scenario, the basic protection scenario, and the strict protection scenario. The results of simulation under these three scenarios indicate that urban residential land will increase significantly, whereas agricultural land, woodland, water, and other land would decrease, particularly under the current development trend and basic protection scenarios. Under these two scenarios, considerable decreases are observed in agricultural land, woodland, and water, which may intensify habitat fragmentation, and result in a decline in the quality of cultivated land, water resource shortage, wetland shrinkage, and other ecological problems. Under the strict protection scenario, the rapid proliferation of construction land would be restricted to a large extent and water bodies and woodland would be transformed the least, which would effectively protect natural ecosystem components and maintain sustainable ecosystem services
Keywords:urban expansion  land use  simulation  cellular automata model (SLEUTH model)  Wuhan
本文献已被 CNKI 等数据库收录!
点击此处可从《生态学报》浏览原始摘要信息
点击此处可从《生态学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号