## 3 Materials and Methods  
### Data Preparation  
A landslide inventory includes the locations of the past and recent landslides [21]. A landslide inventory can give insight into landslide location, dates, type, frequency of occurrence, state of activity, magnitude or size, failure mechanisms, causal factors, and damage caused [58,59]. In the present study, the landslide inventory map was prepared on the basis of satellite images (Google Earth and ZY03 images) and historical landslide records of the area, which were verified by GPS. A total of 202 landslides were identified to prepare the landslide susceptibility map, of which most of the landslides were slides (190), the others included 12 rock falls [60]. According to an analysis in the GIS environment, the smallest landslide was nearly 160 m\({}^{3}\), the largest landslide was more than 1,000,000 m\({}^{3}\), while the average was 33,000 m\({}^{3}\). Finally, 141 landslides were randomly selected  
Figure 2: Geological map of the study area. as training data and rest of them were used for the verification of the landslide susceptibility map (Figure 1). There are no universal guidelines for selecting landslide conditioning factors [33; 61]. A total of 16 landslide conditioning factors were used for landslide susceptibility mapping including slope angle, slope aspect, elevation, plan curvature, profile curvature, topographic wetness index (TWI), stream power index (SPI), sediment transport index (STI), distance to rivers, distance to roads, distance to faults, soil, land use, normalized difference vegetation index (NDVI), lithology, and rainfall, which are considered as controlling factors in the occurrence of landslides in the study area. Slope angle is an important factor that affects the stress state of slope mass, and these positions where stress exceeds failure strength may contribute to landslide hazards [62; 63]. In this case, as shown in Figure 3a, the thematic data layer of the slope angle was reclassified into seven categories with an interval of 10\({}^{\circ}\), namely, (0-10\({}^{\circ}\)), (10-20\({}^{\circ}\)), (20-30\({}^{\circ}\)), (30-40\({}^{\circ}\)), (40-50\({}^{\circ}\)), (50-60\({}^{\circ}\)), and (60-72.83\({}^{\circ}\)). Slope aspect is another common conditioning factor for the task of landslide susceptibility mapping [64; 65]. It has been proven that most landslides usually occur at a certain slope aspect for a given study area, but the mechanism has not been revealed clearly [66]. Therefore, slope aspect was also employed as a conditioning factor. Here, slope aspect categories include flat, north, northeast, east, southeast, south, southwest, west, and northwest (Figure 3b). Generally, it is considered that elevation has a firm relationship with landslide occurrence [67]. There is no denying that elevation can influence the topography, vegetation, temperature, humidity, human activities, and many other conditions that have a connection with slope stability [30; 68]. In Figure 3c, the elevation of the study area was divided into ten classes with an interval of 200 m, i.e., (442-600 m), (600-800 m), (800-1000 m), (1000-1200 m), (1200-1400 m), (1400-1600 m), (1600-1800 m), (1800-2000 m), (2000-2200 m), and (2200-2410 m). Plan curvature and profile curvature are two quantitative indices that embody topographic characteristics and trend from different perspectives [69]. Various curvature values indicate different runoff and erosion conditions of water. For instance, the upwardly convex surfaces have positive curvature values while negative curvature values mean upwardly concave surfaces [30]. In this study, the plan curvature and profile curvature values were both reclassified into three groups (Figure 3d,**e**). TWI was proposed to indicate the local groundwater potential by [PERSON] [70] in 1991. Currently, TWI is regarded as an extensively-used causative factor in landslide susceptibility assessment [71].