A Study of Landslide Susceptibility Mapping Based on Factor Analysis and Bivariate Statistics—With a Case Study in Longnan Area of National Highway 212
Received date: 2008-04-16
Revised date: 2008-06-20
Online published: 2008-10-10
Longnan of National Highway 212 is one of the most serious areas of geo-disasters in China. Therefore, landslide susceptibility mapping is vitally necessary for disaster management and planning development activities in the area. Based on the field, laboratory and office studies in the study area, and with a study of the relationship between landslides and their causative factors, thematics date layers of petrofabrics types, slope, aspect, altitude, the distance to river, the distance to road, precipitation, land-use types and vegetation cover thematics data layers were used to create the landslide susceptibility map. In the study, a landslide susceptibility map of Longnan of National Highway 212 was produced using the Information Value (InforV) and Landslide Nominal Risk Factor (LNRF) of bivariate statistics with the help of Geographical Information Systems (GIS). The study area was classified into five classes of relative landslide susceptibility, namely, very low, low, moderate, high, and very high. To prove the practicality, the landslide susceptibility maps were compared with a landslide activity map containing 11 active landslides with sliding displacement. The outcome was that the overwhelming areas of the active landslide zones fit into the high and very high susceptibility classes. The results showed that both the InforV method and the LNRF method corresponded to the actual distribution of landslide susceptibility. At the same time, the InforV method gave a more realistic picture of the actual distribution of landslide susceptibility than LNRF method.
LIU Gao , HAN Wenfeng , Liang Shouyun , CHEN Wenwu , ZHANG Fanyu . A Study of Landslide Susceptibility Mapping Based on Factor Analysis and Bivariate Statistics—With a Case Study in Longnan Area of National Highway 212[J]. Advances in Earth Science, 2008 , 23(10) : 1037 -1042 . DOI: 10.11867/j.issn.1001-8166.2008.10.1037
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