城市化背景下双流县景观格局变化特征及趋势预测
Characteristics of landscape pattern changes and trend prediction of Shuangliu County in the context of urbanization
作者：王霞(四川大学建筑与环境学院)；干晓宇(中国科学院上海应用物理研究所)；李江林(四川省建筑设计研究院)；张清彦(成都市风景园林规划设计院)
Author：WANG Xia(College of Architecture and Environment, Sichuan University)；GAN Xiao-Yu(Laboratory of Physical Biology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences)；LI Jiang-Lin(Sichuan Provincial Architectural Design Institute)；ZHANG Qing-Yan(Chengdu Landscape and Planning Design Institue)
收稿日期：2013-04-24 年卷（期）页码：2015,52(3):651-656
期刊名称：四川大学学报: 自然科学版
Journal Name：Journal of Sichuan University (Natural Science Edition)
关键字：马尔科夫模型; 元胞自动机模型; 景观生态学; 土地利用格局; 双流县
Key words：Markov model; CA model; Landscape ecology; Land use pattern; Shuangliu County
基金项目：国家自然科学基金青年科学基金项目（51108284）; 四川华西集团科技项目（HXKX20121003）; 四川大学中央高校基本科研业务费研究专项基金（skqy201509）
中文摘要
以成都市双流县为研究区, 景观生态学为理论支持, 在GIS技术支持下, 分析了双流县2007~2009年间景观格局变化特征, 并利用Markov CA模型对研究区2015年土地利用空间格局进行预测.结果表明, 在研究期间, 双流县景观格局变化特征为: 整体景观呈现破碎化趋势, 斑块密度增加, 平均斑块面积减少.其中, 城市建设用地面积增加, 建设用地斑块呈现聚集现象, 绿地面积减少, 绿地斑块呈现破碎趋势, 绿地斑块数量上升, 平均斑块面积下降.利用Markov CA模型, 选用5×5滤波器作为邻域, 能够较好的模拟研究区景观格局动态.预计2015年, 双流县北部和西南部区域受城市化影响较大, 研究区中部和东南部地区在未来保护全县生态平衡中具有重要作用
英文摘要
By taking Shuangliu County of Chengdu city as study area, Landscape pattern changes of Shuangliu County has been analyzed from 2007~2009 with theoretic support of landscape ecology and technical support of GIS. Meanwhile, land use spatial pattern of the study area in 2015 has been predicted by applying Markov CA model. The results showed that the overall characteristics of Shuangliu County’s landscape pattern changes are presenting fragmentation trend, the patch density are increasing and the average patch area are reducing. The Urban Construction Land area increased which revealed aggregation phenomenon; the Green Space area reduced and the Green Space area patches presented trend of fragmentation with the number of Green Space patches increasing and the average patch area declining. Markov CA model has been applied to well simulate the landscape pattern dynamic in the study area by selecting 5 × 5 filter as neighbor. It is predicted that northern and south western Shuangliu County has greater impact of urbanization and the central and southeastern study area play important roles in protecting ecological balance of the county.
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