基于GIS与ANN模型的地震滑坡易发性区划GIS and ANN Model for Earthquake Triggered Landslides Susceptibility Zonation
许冲;徐锡伟;
摘要(Abstract):
基于遥感数据、地理信息系统(GIS)技术和人工神经网络(ANN)模型,开展地震滑坡易发性区划研究。2010年4月14日玉树地震后,基于航片与卫星影像目视解译,并辅以野外调查的方法,在地震区圈定了2036处地震诱发滑坡。选择高程、坡度、坡向、斜坡曲率、坡位、与水系距离、地层岩性、与断裂距离、与公路距离、归一化植被指数(NDVI)、与同震地表破裂距离、地震动峰值加速度(PGA)共12个因子作为地震滑坡易发性评价因子。这些因子均是应用GIS技术与遥感影像处理技术,基于地形数据、地质数据、遥感数据得到。训练样本中的滑动样本有两组,一组是滑坡区整个单滑坡体的质心位置,另一组是滑坡滑源区滑前的坡体高程最高的位置。应用这12个影响因子,分别采用这两组评价样本,基于ANN模型建立地震滑坡易发性索引图,基于GIS工具建立地震滑坡易发性分级图。分别应用训练样本中滑坡分布的点数据去检验各自的结果正确率,正确率分别为81.53%与81.29%,表明ANN模型是一种高效科学的地震滑坡易发性区划模型。
关键词(KeyWords): 地震滑坡;人工神经网络;滑坡易发性区划;地理信息系统
基金项目(Foundation): 科学技术部国际科技合作项目(2009DFA21280);; 国家自然科学基金项目(40821160550)
作者(Author): 许冲;徐锡伟;
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