###### Abstract  
Because of the special geological conditions on the Loess Plateau, Landslide erosion is not only the main goal of prevention and control of geological disasters, but also an important erosion mode of soil and water loss in the basin. Thus, landslide susceptibility assessment before only considering landslide frequency is not far enough for a decision-maker. The study aims to consider both frequency and scale of landslides for a better landslide susceptibility evaluation. Taking the Yangou small watershed as an example, this study used a VR model, RIRA method, and the GIS method to comprehensively consider frequency and scale to analyze landslide susceptibility of the small watershed. Based on the detailed analysis of the existing literature, slope, elevation, NDVI, land-use, lithology, amount distant to road, amount distant to river, profile curvature, and rainfall as landslide are selected as the conditioning factors (CFs) of the landslide, to draw the sensitivity map. The map of landslide susceptibility was classified into five zones: very low, low, medium, high, and very high, and the cover areas occupy 6.90, 12.81, 12.83, 9.42, and 5.87 km\({}^{2}\), respectively. A total of 60% of the landslide occurred in the zones of high and very high susceptibility, accounting for 87% of the total volume in the study area. The very high susceptibility is the area with a larger relief and along the river and road. The findings will help decision makers to formulate scientific comprehensive policies that take into account disaster prevention and soil conservation measures in specific regions. L 2  
transport through river flows to the downhill [7]. On the Loess Plateau, the phenomenon is particularly serious, which is one of the reasons for the poor soil erosion in the region due to unmanageable, heavily containing sediment flow [8]. It can be seen that landslides have a great effect on water and soil loss in the basin. Older land use policies may not always reflect optimal planning for land use prone to landslides [9]. A reasonable zoning prediction of regional landslides can therefore assist planners and engineers in making decisions on the use of such lands [6]. Landslide susceptibility is recognized as the propensity of an area to generate landslides [10]. Generally, landslide occurrence in each region is a function of various factors. Each of the factors and function has a different influence. In order to assess susceptibility from gravity, it is, therefore, necessary to identify and analyze the factors leading to gravity [11]. The occurrence of landslides is controlled both by a series of predisposing factors, e.g., geological, geomorphological, climatic and hydro-geological, and triggering factors, including seismicity, heavy rainfall, human activities, and freeze-thaw [12]. Although it is still difficult to predict a landslide event in space and time, a region may be divided into sub-regions with homogenous properties, which are classified and ranked according to the potential hazard degrees of group movement considering the prerequisite factors explained above. A landslide susceptibility map is considered as an effective solution, and it is also an important task for decision making on regional planning and protection. A variety of methods can be employed to develop the landslide susceptibility assessment. There are two main types: a \"knowledge-driven model\" that uses relevant domain knowledge for analysis and a \"data-driven model\" that uses intelligent methods to automatically find patterns from data. The former methods include fuzzy logic [13], fuzzy comprehensive evaluation [14], and the analytic hierarchy process [15]. The latter methods include logistic regression analysis [16], decision tree [17], random forest [18], artificial neural network [19], and support vector machine [20].