| 集成遥感和GIS的元胞自动机城市生长模拟 |
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| 引用本文： | 冯永玖,刘妙龙,韩震.集成遥感和GIS的元胞自动机城市生长模拟[J].长江流域资源与环境,2011,20(1):9-13. |
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| 作者姓名： | 冯永玖 刘妙龙 韩震 |
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| 作者单位： | (1.上海海洋大学海洋科学学院,上海 201306；2.上海海洋大学海洋科学研究院,上海 201306；3.同济大学测量与国土信息工程系,上海 200092) |
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| 基金项目： | 上海市教育委员会科研创新项目(11YZ154); 上海市科学技术委员会重点项目(08230510700); 上海高校选拔培养优秀青年教师科研专项基金(SSC09018); 上海海洋大学博士启动基金及环境工程重点学科基金(A-2400-10-0134) |
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| 摘 要： | 元胞自动机（Cellular Automata, CA）因其“自下而上”的自组织性能够呈现复杂的全局结构，越来越多地应用于城市生长和演化模拟。从历史遥感影像中提取了对城市生长影响较大的空间距离变量，结合实测数据和规划数据，挖掘基于Logistic回归的地理CA转换规则，建立了Logistic CA模型。在自主开发的基于GIS的地理模拟框架下，以中小尺度城市上海市嘉定区为例，利用该Logistic CA模型模拟和重建了该区1989~2006年城市生长过程。将模拟结果与遥感影像分类的结果进行逐象元比较，获取混淆矩阵和Kappa系数，从而对模型模拟结果进行评价。研究表明:Logistic CA模型适合于中小尺度城市生长模拟，模拟结果与城市实际形态相符，精度较好。最后，基于嘉定区城市发展态势不变的假设，预测了其2010年城市生长的可能情景。
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| 关 键 词： | 元胞自动机 城市生长模拟 遥感 GIS |
REMOTE SENSING AND GIS INTEGRATED SIMULATION OF URBAN GROWTH BASED ON CELLULAR AUTOMATA——A CASE STUDY OF JIADING DISTRICT,SHANGHAI |
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| FENG Yong-jiu,LIU Miao-long,HAN Zhen.REMOTE SENSING AND GIS INTEGRATED SIMULATION OF URBAN GROWTH BASED ON CELLULAR AUTOMATA——A CASE STUDY OF JIADING DISTRICT,SHANGHAI[J].Resources and Environment in the Yangtza Basin,2011,20(1):9-13. |
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| Authors: | FENG Yong-jiu LIU Miao-long HAN Zhen |
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| Institution: | (1.College of Marine Sciences,Shanghai Ocean University,Shanghai 201306,China;2.Institute of Ocean Sciences,Shanghai Ocean University,Shanghai 201306,China;3.Department of Surveying and Geo informatics,Tongji University,Shanghai 200092,China) |
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| Abstract: | Because the complex global patterns could be structured frombottom-uporiented self-organization,cellular automata(CA)have been increasingly applied in the simulation of urban growth and evolution.Spatial distances variables(driving forces)impacting urban growth were extracted from the multi-temporal remotely sensed data,which were used to discover the transition rules of CA,with the auxiliary of field surveyed topographic maps and land use planning data.Based on the method of logistic regression,the logisti... |
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| Keywords: | cellular automata urban growth simulation remote sensing GIS |
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