The Use of Fuzzy Logic and Artificial Neural Network Algorithm in Landslide Susceptibility Mapping of Chalus River Basin

Landslide is a geophysical phenomenon that event led to the displacement along the steep slopes and it caused the huge human and financial losses. Raining, ice, and human irrational use of nature is one of the factors causing landslides. Height, slope, soil type, geological and hydrological parameters are the most important factors affecting landslides. Chalus basin with an area of 929.28 km is located along the Karaj-Chalus road. The basin due to overlook the busy road of Chalus, has particular importance. So evaluate the potential of landslides in the area of the basin is necessary. In this study, some factors such as slope, aspect, geology, vegetation, hydrology and soil drainage parameters are examined. After mapping a variety of factors, fuzzy intelligent algorithms and Artificial Neural Networks (ANN) were used for landslide zoning. By applying fuzzy method, it was found that 34.1 percent of the area has high and very high potential for accruing landslide, 35.5 percent of the area has medium potential and 30.3 percent of the area has low potential. Also by applying ANN method, it was shown that 34.4 percent of the area has high and very high potential for accruing landslide, 29.05 percent of the area has medium potential and 27.5 percent has low potential.