## 4 Blending Ensemble Learning-Based Landslide Susceptibility Mapping and Risk Assessment
### Validation of Landslide Risk Zoning Results  
Based on the results of the landslide risk level zoning in the study area, 263 landslide points that occurred in Anhua County, Heshan District, and Taojiang County of Yiyang City in recent decades were extracted from the spatial distribution data of national geological disaster points released by the Chinese Academy of Sciences (CAS) for validation (as shown in Figure 19).  
A statistical table of susceptibility areas (Table 14) was obtained by applying the susceptibility analysis results to calculate the area, area proportion, and landslide proportion of each susceptibility zone. The table shows that historical landslides mainly occurred within the high susceptibility zone. The landslide densities for the very low, low, medium, high, and very high susceptibility zones are 0.009, 0.020, 0.030, 0.048, and 0.049, respectively. This indicates that as the susceptibility level increases, the landslide density gradually rises, and the likelihood of landslide occurrence also increases, demonstrating a positive correlation between landslide density and regional susceptibility levels. Similarly, the frequency ratio (FR) can be used to evaluate the contribution of regional landslides. An FR \(\geq\) 1 indicates a positive contribution, while an FR \(<\) 1 indicates a negative contribution. The study found that the frequency ratios (FR) for the high and very high susceptibility zones are 1.505 and 1.523, respectively, both greater than 1, indicating the consistency between the classification of susceptibility zones with the conditions for the occurrence of landslides.  
A comparison between the post-heavy rainfall landslide susceptibility zone ratios in Yiyang City and the historical susceptibility zone ratios revealed that their frequency ratios (FR) exhibited similar trends, with both high and extremely high susceptibility zones having FR values greater than 1 (Tables 12-14). This indicates a high consistency between  
\begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Prediction** & **Susceptibility** & **Grid Number** & **Area Ratios** & **Landslide** & **Landslide** & **Frequency Ratios** \\
**Model** & **Areas** & **(Unit)** & **(\%)** & **Ratios (\%)** & **Density** & **FR (Landslide** \\  & & & & **Ratio/Area Ratio)** \\ \hline  & Very low S.A. & 13,120 & 13.32 & 3.80 & 0.009 & 0.286 \\ Blending & Low S.A. & 23,408 & 23.76 & 14.45 & 0.020 & 0.608 \\ ensemble & Moderate S.A. & 22,873 & 23.22 & 21.67 & 0.030 & 0.934 \\ learning & High S.A. & 21,412 & 21.73 & 32.70 & 0.048 & 1.505 \\  & Very high S.A. & 17,709 & 17.97 & 27.38 & 0.049 & 1.523 \\ \hline \hline \end{tabular}
\end{table}
Table 14: Susceptibility area (SA) proportions.  
Figure 19: Distribution map of historical landslide points.  
the landslide susceptibility analysis results, the risk classification outcomes, and the actual distribution of historical landslide points, confirming the validity of the landslide risk zoning results. The landslide susceptibility analysis results can serve as a reference for landslide hazard risk identification and early warning in the Yiyang area and areas with similar geographical conditions.