Shallow landslides are common in mountainous areas after intense rainfall. Of all landslide hazard assessment methods, deterministic methods provide the best quantitative information on landslide hazard. However, they require a large amount of detailed in situ data, derived from laboratory tests and field measurements, and therefore it is difficult to apply them over large areas. One of the most important input parameters is soil depth. For large areas, it is impossible to obtain soil depth through field measurements. To overcome this difficulty, a statistics-based regression analysis is used to evaluate soil depths. All the terrain attributes that control soil depths are selected as influential factors. By using multi-linear regression, the soil depths at each location can be predicted. Slope stability analysis can then be performed using deterministic methods with the evaluated soil depths. The study area is divided into slope units. For each slope unit, Monte-Carlo simulation and a GIS-based 3D limit equilibrium model are used to locate the critical slip surface and calculate the corresponding safety factor. The effectiveness of the proposed method has been tested by applying it to a mountainous area in Japan.
All Science Journal Classification (ASJC) codes
- Geotechnical Engineering and Engineering Geology
- Computer Science Applications