## 3 Performance Analysis of SEM-LEWS Based on the Simulation Results of 8-Year Histories
### Establishment of Historical Landslide Database Using Indirect Field-Checks
This included analyses associated with susceptibility zonation as well as rainfall-threshold derivation and validation at the regional- or national-scale. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**Number of GIS**} & \multicolumn{2}{c}{**Number of Classified Data Points According to Spatial Precision**} \\ \cline{3-5}
**Occurrence Date** & **Landslide Data Points** & **1 st Class** & **2 nd Class** & **3 rd Class** \\ \hline
2 July 1999 & 1 & - & - & 1 \\
10 September 1999 & 1 & 1 & - & - \\
14 July 2000 & 1 & - & - & 1 \\
9 August 2002 & 1 & - & - & 1 \\
10 August 2002 & 2 & 1 & - & 1 \\
11 August 2002 & 1 & - & - & 1 \\
12 September 2003 & 3 & - & - & 3 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Classification of historical landslide data according to occurrence date and spatial precision. Figure 8: Historical landslide database in the form of GIS point feature classes including the distribution of (**a**) data recorded from 1999 to 2016 and classified by spatial precision and (**b**) 1 st and 2 nd class spatial precision data recorded from 2009 to 2016 and reclassified by landslide type. The established historical landslide database included data on various types of landslides that could be classified as \"slope failure\" and \"debris flow.\" Figure 8b depicts the distribution of debris flow and slope failure data recorded from 2009 to 2016 with 1 st and 2 nd class spatial precision. Due to the lack of detailed event descriptions for each slope failure, it was not feasible to further categorize the data. Therefore, the slope failure category included landslides caused by the failure of both natural slopes as well as artificial slopes, such as embankments, retaining walls, and cut or fill slopes. However, as the source area of the majority of debris flows was located at the head of gullies in mountainous areas, the majority of recorded debris flows are highly likely to have been spontaneously induced by rainfall with negligible influence of human activities. Table 3 specifies the numbers of slope failures and debris flows depicted in Figure 8b according to the respective IC zone. This dataset includes 222 data points and was used to analyze the performance of SEM-LEWS in our study. Notably, as indicated in Figure 8, the majority of historical landslides are distributed in the south-central part of Busan (i.e., IC zones 3 and 4), which is the most populated and urbanized region of the city. This implies that the primary data sources showed a bias towards recording damage-causing landslide events, which, in turn, indicates that regions with sparsely distributed historical landslide data (e.g., IC zones 1, 2, and 8) do not necessarily represent areas of more stable geological or meteorological conditions. The relatively sparse distribution of historical landslide data in the northeastern and southwestern areas of Busan may be because landslides triggered in outer areas or deep mountainous areas had a lower chance of being reported, as they are unlikely to have a significant impact on society.