Application of Logistic Regression Model on the Wenchuan Earthquake Triggered Landslide Hazard Mapping and Its Validation
详细信息
- 责任者：Xu Chong (Key Laboratory of Active Tectonics and Volcano ; Institute of Geology ; China Earthquake Administration ; Beijing 100029 ; China) ; Dai Fuchu
- 刊名：Hydrogeology and Engineering Geology
- 出版年：2013
- 卷期：40(3)
- 关键词：滑坡 ; landslides ; 四川 ; Sichuan Province
- 页码：p.98-104
- 图表：illus., 1 table, 16 refs.
- 分类号：1702
- issnNo：ISSN1000-3665
- isbnNo：CN11-2202/P
摘要
The main purpose of this paper is to present the use of remote sensing images,GIS technology and Logistic Regression(LR) model for earthquake triggered landslide hazard mapping related to the 2008 Wenchuan earthquake.Landslide polygons were delineated in the study area from interpretation of aerial photographs and satellite images in high resolution,and the inventory of landslides triggered by the earthquake was constructed.Eight factors,including slope angle,slope aspect,elevation,distance from drainages,distance from roads,distance from main faults,seismic intensity and lithology were selected as controlling factors for earthquake triggered landslide hazard mapping.Both landsliding and non-landsliding samples were needed as training data for the LR model.Centroids of the 48007 initial landslide polygons were extracted for landsliding samples and a similar number of 48000 points were selected randomly from the regions of the high and the very high landslide hazard areas using weigh of evidence model as non-landsliding samples.Based on the eight landslide controlling factors,48007+48000 training samples and the LR model and landslide qualitative hazard probability index map were constructed using map overlaying techniques.The validation results show that a success rate of 81.739% exists between the hazard probability index map and the location of the initial 48007 landsliding samples.The predictive rate of 86.278% was obtained from comparison of the additional landslide polygons and the landslides hazard probability index map.
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