# Susceptibility Mapping on Urban Landslides Using Deep Learning Approaches in Mt. Umyeon
## 2 Study Area and Data
### Spatial Datasets
Curvature, a morphological characteristic in terms of affecting the erosion process and landslide evolution, is commonly used in landslide analysis, because it can account for local surface relief in the study area [58; 60] (Figure 3c). TWI was used to express the influence of terrain on the presence of a runoff-generated saturated area [61; 62], with higher values increasing the probability of landslide occurrence (Figure 3d) [63]. The erosive power of surface flow, measured by the SPI index, is one of the variables that influence landslides [64]. Higher SPI values indicate an increased likelihood of erosion that affects local stability [61], and allows a general determination of where soil conservation is needed to reduce the effects of surface runoff erosion (Figure 3e) [61]. SLF values refer to the ratio of soil loss to slope length, and were calculated through the revised universal soil loss equation (Figure 3f) [65]. The standardized height is calculated by multiplying the absolute height by the height of the study area normalized between 0 and 1 (Figure 3g). The standardized height yields parameters suitable for soil property prediction by simplifying complex terrain conditions using linear regression [66]. The standardized height represents a value suitable for predicting soil properties, by simplifying  
Figure 2: Landslide locations from aerial photographs after landslides in 2011: (**a**) Mt.Umyeon area after the landslides in 2011, (**b**) debris flows in northern part of Mt. Umyeon and (**c**) damage of residential areas including apartments. complex terrain conditions using linear regression [66]. Valley depth means the vertical distance at the basic level of the channel network [59]; valley depth has been used as a landslide-influencing variable in several studies (Figure 3h) [46,67]. The DDG is determined through quantitative hydrological gradient estimation and the downslope distance calculation when water loses a determined amount of energy due to precipitation (Figure 3i) [68]. The vegetation provides root strength to help stabilize the mountain slope. The effect of rainfall on the slope is likely to be mitigated by the degree of vegetation distribution. The attributes selected by several studies as landslide-influencing variables, including timber diameter, type, density, and age, were extracted from a digital vegetation map with a ratio of 1:25,000, provided by the Korea Forest Service (Figure 4a-d). As reported in numerous additional studies, landslides are strongly influenced by the geological structure and soil type covering the area [69,70]. Geological cover is one of the most used variables in the assessment of landslide susceptibility [58]; however, in this study, it was excluded, because it was mostly the same due to the size of the study area. Physical and organizational soil cover properties influence surface runoff and penetration processes [71]. Soil properties affect the flow of water, including surface and groundwater, in the way that landslides occur when the amount of water in the soil exceeds the drainage capacity and the cohesion drops sharply [72]. Therefore, forest and soil characteristics were considered as landslide-influencing variables in this study (Figure 4) [46]. Each variable was pre-processed into raster format with a grid size of 10 m and is illustrated in Table 1 with the source and scale. Figure 3: Topographical variables influencing landslides used in this study: (**a**) slope gradient, (**b**) slope aspect, (**c**) curvature, (**d**) topographic wetness index (TWI), (**e**) stream power index (SPI), (**f**) slope length factor (SLF), (**g**) standardized height, (**h**) valley depth, and (**i**) downslope distance gradient (DDG).