Assessment of shallow landslide susceptibility by means of multivariate statistical techniques

被引:324
|
作者
Baeza, C [1 ]
Corominas, J [1 ]
机构
[1] Univ Politecn Cataluna, Dept Geotech Engn & Geosci, E-08034 Barcelona, Spain
关键词
landslide susceptibility; multivariate techniques; discriminant analysis;
D O I
10.1002/esp.263
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Several multivariate statistical analyses have been performed to identify the most influential geological and Geomorphological parameters on shallow landsliding and to quantify their relative contribution. A data set was first prepared including more than 30 attributes of 230 failed and unfailed slopes. The performance of principal component analysis, t-test and one-way test, allowed a preliminary selection of the most significant variables, which were used as input variables for the discriminant analysis. The function obtained has classified successfully 88.5 per cent of the overall slope population and 95.6 per cent of the failed slopes. Slope gradient, watershed area and land-use appeared as the most powerful discriminant factors. A landslide susceptibility map, based on the scores of the discriminant function, has been prepared for Ensija range in the Eastern Pyrenees. An index of relative landslide density shows that the results of the map are consistent. Copyright (C) 2001 John Wiley & Sons, Ltd.
引用
收藏
页码:1251 / 1263
页数:13
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