Landslide hazards mapping using uncertain Naive Bayesian classification method
来源期刊：中南大学学报(英文版)2015年第9期
论文作者：MAO Yi-min ZHANG Mao-sheng WANG Gen-long SUN Ping-ping
文章页码：3512 - 3520
关键词：uncertain Bayesian model; landslide; hazard assessment
Key words：uncertain Bayesian model; landslide; hazard assessment
Abstract: Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Na？ve Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Na？ve Bayesian classification method in Baota district of Yan’an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Na？ve Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves (AUC) in NBU and Na？ve Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.
MAO Yi-min(毛伊敏)1, 2, 3, ZHANG Mao-sheng(张茂省)1, WANG Gen-long(王根龙)1, SUN Ping-ping(孙萍萍)1
(1. Key Laboratory for Geo-hazard in Loess Area, Ministry of Land and Resources (MLR), Xi’an 710086, China;
2. School of Geology Engineering and Geomatics, Chang’an University, Xi’an 710064, China;
3. Applied Science Institute, Jiangxi University of Science and Technology, Ganzhou 341000, China)
Abstract:Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Na？ve Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Na？ve Bayesian classification method in Baota district of Yan’an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Na？ve Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves (AUC) in NBU and Na？ve Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.
Key words:uncertain Bayesian model; landslide; hazard assessment
