## 5 Results and Discussion
### Leyte Province Results  
For the Leyte sites where both ReMi and HVSR surveys were conducted, the estimated Vs30 values were compared with the VS30 values obtained from ReMi. Similar to the GMMA dataset, a comparison of Vs profiles for two sample sites in Figure 9 shows that the HVSR inversion-derived and the ReMi-derived profiles have a strong agreement, with only minimal differences in layer depths and velocities. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Soil Profile** & **No. of** & **Match Rate** & **R\({}^{2}\)** & **r** & **RMSE** \\
**Type** & **Samples** & **(\%)** & **R\({}^{2}\)** & **r** & **RMSE** \\ \hline \(S_{C}\) & 5 & 80 & 0.376 & 0.614 & 59.517 \\ \(S_{D}\) & 16 & 68.75 & 0.835 & 0.914 & 28.411 \\ \(S_{E}\) & 4 & 100 & 0.920 & 0.920 & 8.402 \\ All & 25 & 76 & 0.885 & 0.941 & 37.584 \\ \hline \end{tabular}
\end{table} 
Table 6: Match Rate, R\({}^{2}\), r, and RMSE values for all soil profile types in GMMA. Figure 8: Correlation between site period and estimated Vs30 of GMMA sites using power regression. Figure 10 shows no clear pattern of overestimation or underestimation; however, the estimated Vs30 values deviate 10-30% away from the ReMi-derived Vs30 values. This shows reasonable agreement with the ReMi-derived Vs30 values and shows no consistent bias of results in one direction. The discrepancies are likely due to inherent differences in the methodology employed by ReMi Disper and the GA in estimating Vs30. Additionally, inconsistencies in the acquired HVSR data from the field may have also contributed to these variations, as HVSR surveys were not always centrally located along the ReMi array, unlike in GMMA sites. This was often due to unsuitable conditions for conducting the HVSR survey near the ReMi site or because noise interference prevented the HVSR survey from being conducted near and simultaneously with the ReMi survey. Figure 10: Comparison between ReMi-derived Vs30 (in blue) and estimated Vs30 (in orange) of Leyte sites. Figure 9: Vs profile comparison in sample sites between ReMi (in blue) and HVSR inversion (in orange) in sample Leyte sites. The match rate of soil profile types between ReMi and estimated VS30 values was also analyzed for Leyte sites (Table 7). Soil profile type \(S_{C}\) exhibits a 100% match rate, but a low R\({}^{2}\) indicates a weak correlation between estimated and ReMi-derived values. The r value suggests a moderate inverse relationship, with no consistent trends in over or underestimation, as illustrated in Figure 8. Despite this, the lower RMSE indicates that the inversion estimates ReMi-derived values better for type \(S_{C}\). Types \(S_{D}\) and \(S_{E}\) show match rates of 73.33% and 85.71%, respectively, with R\({}^{2}\) values also reflecting no clear trends. However, the r values indicate a moderate positive linear relationship for both classes, contrasting with type \(S_{C}\). Overall, the dataset reveals a strong positive correlation between ReMi-derived and estimated Vs30 values, supported by high R\({}^{2}\) and r values. Although the RMSE is higher than that observed for GMMA sites; this suggests that the inversion effectively captures the trend of ReMi-derived Vs30. As shown in Figure 11, the exploratory scatter plot demonstrates similarities with the performance of the method using the GMMA dataset, wherein the estimated Vs30 values generally align with the measured ReMi values, with most data points plotting near the 1:1 line. The majority of sites also exhibit matching soil profile types. In cases where the assigned profile type differs, the Vs30 values remain close, with discrepancies primarily occurring near classification boundaries. The power regression between the site period and the estimated Vs30 shows a strong inverse correlation, with an R\({}^{2}\) value of 0.707. As Vs30 decreases, the site period increases. Figure 11: Comparison of measured Vs30 from ReMi and estimated Vs30 for soil profile types Leyte Province data.