多源数据支持下的三峡库区滑坡灾害空间智能预测

武雪玲, 任福, 牛瑞卿

武雪玲, 任福, 牛瑞卿. 多源数据支持下的三峡库区滑坡灾害空间智能预测[J]. 武汉大学学报 ( 信息科学版), 2013, 38(8): 963-968.
引用本文: 武雪玲, 任福, 牛瑞卿. 多源数据支持下的三峡库区滑坡灾害空间智能预测[J]. 武汉大学学报 ( 信息科学版), 2013, 38(8): 963-968.
WU Xueling, REN Fu, NIU Ruiqing. Spatial Intelligent Prediction of Landslide Hazard Based on Multi-source Data in Three Gorges Reservoir Area[J]. Geomatics and Information Science of Wuhan University, 2013, 38(8): 963-968.
Citation: WU Xueling, REN Fu, NIU Ruiqing. Spatial Intelligent Prediction of Landslide Hazard Based on Multi-source Data in Three Gorges Reservoir Area[J]. Geomatics and Information Science of Wuhan University, 2013, 38(8): 963-968.

多源数据支持下的三峡库区滑坡灾害空间智能预测

基金项目: 国家自然科学基金资助项目(41271455/D0108); 数字制图与国土信息应用工程国家测绘地理信息局重点实验室开放研究基金资助项目(GCWD201101); 地理空间信息工程国家测绘地理信息局重点实验室经费资助项目(201115); 中央高校基本科研业务费专项资金资助项目(CUGL120207)
详细信息
    作者简介:

    武雪玲,博士,副教授,现主要从事滑坡灾害预测研究。

  • 中图分类号: P237.9;P208

Spatial Intelligent Prediction of Landslide Hazard Based on Multi-source Data in Three Gorges Reservoir Area

Funds: 国家自然科学基金资助项目(41271455/D0108); 数字制图与国土信息应用工程国家测绘地理信息局重点实验室开放研究基金资助项目(GCWD201101); 地理空间信息工程国家测绘地理信息局重点实验室经费资助项目(201115); 中央高校基本科研业务费专项资金资助项目(CUGL120207)
  • 摘要: 针对传统空间分析技术不易发掘多源、海量滑坡数据中隐藏的模式、趋势和关系等问题,以三峡库区为研究对象,通过多源数据融合提取滑坡孕灾环境和影响因素信息,进而利用动态构建算法建立BP神经网络模型,定量预测滑坡空间易发性,生成滑坡易发性分区图。采用成功率曲线分析预测结果,三层BP神经网络的预测精度达到89.75%,预测结果与野外调查实际情况吻合较好。
    Abstract: Landslide hazard is influenced by many temporal and spatial factors.Traditional spatial analytical techniques cannot easily discover new and unexpected patterns,trends,and relationships that can be hidden deep within very large diverse geographic datasets.Focusing on Three Gorges Reservoir Area,environmental and triggering factors for landslide occurrences were extracted from multi-source data.Then,quantitative landslide susceptibility indices were calculated using the trained three-layered BP neural network,and the landslide susceptibility maps were generated.Finally,success rate curve was used to verify the results of landslide susceptibility mapping,and the results showed the best accuracy of 89.75%.The validation showed sufficient agreement between the prediction results and existing landslide.Therefore,the proposed model is an efficient method for landslide intelligent prediction,and can provide a significant reference for landslide hazard prediction and assessment.
  • [1] 牛瑞卿韩舸,. 利用数据挖掘的滑坡监测数据处理流程[J]. 武汉大学学报(信息科学版). 2012(07)[2] 陈德基满作武,. 三峡工程几个重大地质问题的研究与论证[J]. 中国工程科学. 2011(07)[3] 郑守仁. 三峡工程试验性蓄水175m水位运行的相关问题[J]. 人民长江. 2010(08)[4] 王尚庆徐进军,罗勉,. 三峡库区白水河滑坡险情预警方法研究[J]. 武汉大学学报(信息科学版). 2009(10)[5] Biswajeet PradhanAmruta Chaudhari,J. Adinarayana,Manfred F. Buchroithner. Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia[J] 2012,Environmental Monitoring and Assessment(2):715~727
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出版历程
  • 收稿日期:  2013-05-25
  • 修回日期:  2013-05-25
  • 发布日期:  2013-08-04

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