## 4 Results and Discussion
### Landslide Susceptibility Maps
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Zoning**} & \multirow{2}{*}{**Area (km2)**} & \multirow{2}{*}{**Area Proportion**} & \multicolumn{2}{c}{**Number of**} & \multicolumn{2}{c}{**Landslide**} & \multicolumn{2}{c}{**Landslide**} \\  & & & & **Landslide Points** & **Point Proportion** & **Point Density** \\ \hline \multirow{4}{*}{NB-GLHM} & Very low & 195.74 & 8.84\% & 2 & 1.96\% & 0.0102 \\  & Low & 457.69 & 20.66\% & 23 & 22.55\% & 0.0503 \\  & Medium & 913.34 & 41.46\% & 23 & 22.55\% & 0.0250 \\  & High & 347.35 & 15.68\% & 25 & 24.51\% & 0.0720 \\  & Severe & 295.87 & 13.36\% & 29 & 28.43\% & 0.0980 \\ \hline \multirow{4}{*}{NB-Random} & Very low & 360.16 & 16.26\% & 1 & 0.98\% & 0.0028 \\  & Low & 618.49 & 27.92\% & 9 & 8.82\% & 0.0146 \\  & Medium & 745.53 & 33.66\% & 21 & 20.59\% & 0.0282 \\  & High & 397.30 & 17.94\% & 51 & 50.00\% & 0.1284 \\  & Severe & 93.51 & 4.22\% & 20 & 19.61\% & 0.2139 \\ \hline \multirow{4}{*}{SVM-GLHM} & Very low & 771.69 & 34.84\% & 1 & 0.98\% & 0.0013 \\  & Low & 396.21 & 17.89\% & 3 & 2.94\% & 0.0076 \\  & Medium & 252.14 & 11.38\% & 2 & 1.96\% & 0.0079 \\  & High & 252.83 & 11.41\% & 5 & 4.90\% & 0.0198 \\  & Severe & 542.13 & 24.48\% & 91 & 89.22\% & 0.1679 \\ \hline \multirow{4}{*}{SVM-Random} & Very low & 1170.48 & 52.84\% & 2 & 1.96\% & 0.0017 \\  & Low & 263.89 & 11.91\% & 2 & 1.96\% & 0.0076 \\  & Medium & 181.34 & 8.19\% & 4 & 3.92\% & 0.0221 \\  & High & 191.23 & 8.63\% & 12 & 11.76\% & 0.0628 \\  & Severe & 408.05 & 18.42\% & 82 & 80.39\% & 0.2010 \\ \hline \multirow{4}{*}{SVM-RF-GLHM} & Very low & 836.32 & 37.76\% & 1 & 0.98\% & 0.0012 \\  & Low & 408.70 & 18.45\% & 6 & 5.88\% & 0.0147 \\  & Medium & 329.52 & 14.88\% & 17 & 16.67\% & 0.0516 \\  & High & 350.06 & 15.80\% & 26 & 25.49\% & 0.0743 \\  & Severe & 290.40 & 13.11\% & 52 & 50.98\% & 0.1791 \\ \hline \multirow{4}{*}{SVM-RF-Random} & Very low & 934.45 & 42.19\% & 7 & 6.86\% & 0.0075 \\  & Low & 589.61 & 26.62\% & 18 & 17.65\% & 0.0305 \\  & Medium & 358.73 & 16.20\% & 40 & 39.22\% & 0.1115 \\  & High & 181.34 & 8.19\% & 14 & 13.73\% & 0.0772 \\  & Severe & 150.86 & 6.81\% & 23 & 22.55\% & 0.1525 \\ \hline \multirow{4}{*}{XGBoost-GLHM} & Very low & 428.50 & 19.35\% & 0 & 0.00\% & 0.000 \\  & Low & 613.06 & 27.68\% & 3 & 2.94\% & 0.0049 \\ \cline{1-1}  & Medium & 786.30 & 35.50\% & 44 & 43.14\% & 0.0560 \\ \cline{1-1}  & High & 230.71 & 10.42\% & 22 & 21.57\% & 0.0954 \\ \cline{1-1}  & Severe & 156.43 & 7.06\% & 33 & 32.35\% & 0.2110 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Zonal statistics of landslide susceptibility maps. Figure 9: Landslide susceptibility maps derived from: (**a**) NB-GLHM, (**b**) NB-Random; (**c**) SVM-GLHM, (**d**) SVM-Random; (**e**) SVM-RF-GLHM, (**f**) SVM-RF-Random; (**g**) XGBoost-GLHM, (**h**) XGBoost-Random. The XGBoost-GLHM model achieved the highest landslide point density (0.2110 point/km\({}^{2}\)) in the \"Severe\" zone, while predicting 0 points in the \"Very Low\" zone, suggesting effective discrimination. In contrast, models like NB-GLHM and NB-Random presented lower densities across all classes, with 0.0980 point/km\({}^{2}\) and 0.2139 point/km\({}^{2}\) in the \"Severe\" zone, respectively, indicating relatively weaker spatial prediction power compared to other models. Overall, models trained with the GLHM sampling strategy tend to result in a more concentrated landslide distribution in the \"High\" and \"Severe\" zones, effectively delineating high-risk areas. This highlights the advantages of the GLHM sampling method in capturing spatial heterogeneity and improving susceptibility map accuracy.