## 2 Materials and Methods
### Thematic Layer Preparation  
We conducted an extensive literature review. Choropleth maps were not developed in this study. The chorochromatic and cartogram maps were developed using ArcGIS statistical software (Version 10.4, Environmental Systems Research Institute (Esri), Brisbane, Australia). The probabilistic study is quite challenging, especially with regard to data-dependent models. In this research, a 30 m spatial resolution DEM, geological data, estimated PGA, and intensity values were used to estimate causal factors. To prepare thematic layers, we implemented a world geodetic system (WGS) 1984 reference system. The derived thematic layers were elevation, slope, curvature, geology, fault density, Euclidean distance from faults, proximity to the epicenters, epicenters density, magnitude density, and depth variation (Figure 2). The obtained thematic layers of causal factors were presented in a stretched format. Table 1 provides detailed data used in the current study. By uncovering objective themes, emerging patterns, and insight logic, these layers can be understood. Preprocessing, processing, and post-processing were conducted to estimate probability [28]. Layers were converted to multiple values by points and each pixel value was estimated. Some negative and unexpected values were removed from the database. Prediction of classification was conducted and then post-processing was performed after the testing task [6]. The predicted exact values of each pixel were post-processed to remove irrelevant pixel values. Until the end, the point-to-raster conversion was performed in a GIS environment, which generated SSA and EPM. Figure 2: Several indicators used for susceptibility to seismic amplification (SSA) and probability assessment in this study. (**A**) Proximity to epicenter (km); (**B**) epicenter density(no./km\({}^{2}\)); (**C**) magnitude density (Mw/km\({}^{2}\)); (**D**) depth variation (km); (**E**) intensity variation; (**F**) peak ground acceleration (PGA) variation (g); (**G**) Curvature; (**H**) elevation (m); (**I**) slope (degree); (**J**) geology (amplification factor); (**K**) fault density (no/km\({}^{2}\)); (**L**) proximity to fault (km). Importance of Factors  
Slope and curvature [6; 29]: Landscape processes are affected by slope structure. Several geomorphological processes such as subsurface flow velocity, erosion potential, runoff rates, and overland flow are most affected by slope characteristics. Slopes are associated with crustal faults. Moreover, fault length and size depends on the slope inclination angles. Curvature is associated with slopes having either a positive, negative, or zero curvature. Basins have negative curvatures and their locations for sedimentary deposits are susceptible to seismic amplification. Elevation [30]: High elevation indicates erosion areas with complicated structures. The probability of earthquakes increases when elevation increases. Therefore, high-elevated areas (i.e., the Himalayan region) are extremely susceptible to earthquakes. Fault density and proximity to faults: Earthquake probability increases when fault density also increases. Earthquake occurrence is high if faults are active in a complex tectonic condition. Geology with amplification factor values [31]: Amplification factors of various rock types vary depending on composition. This information is useful to identify locations of high ground shaking. Epicenter density and proximity to epicenter [32]: Earthquake events are clustered at a location and are high density. However, areas with large events are considered as zones of high probability. Earthquake probability is high when zones are clustered. Earthquake probability decreases when distance from an earthquake epicenter increases. Magnitude and depth density [32]: Magnitude density indicates the likelihood of occurrence of a particular event. Density provides information for fault capacity and depth that could generate a particular magnitude event.