## 4 Results
### Suitable Interpolation Method for Soil Salinity Prediction and Mapping  
The comparison of the accuracy of four interpolated methods in terms of model performance for soil salinity prediction in the two measuring modes, including ME, RMSE, R\({}^{2}\), and PBIAS, is reported in Table 16. As a result of ranking, the higher efficiency value  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Measuring Mode** & **ME (mS/m)** & **RMSE (mS/m)** & **R\({}^{2}\)** & **PBIAS (\%)** & **Number of Samples** \\ \hline HH & 570.6292 & 1318.1468 & 0.8280 & \(-\)37.5786 & 121 \\ VV & \(-\)420.6817 & 1218.4730 & 0.6665 & 16.8754 & 121 \\ \hline \hline \end{tabular}
\end{table}
Table 15: Statistical data for accuracy assessment of the RK method.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multirow{2}{*}{**Sub-District**} & \multicolumn{3}{c}{**ECe of HH in mS/m**} & \multicolumn{3}{c}{**ECe of VV in mS/m**} \\ \cline{3-6}  & & **Mean** & **SD** & **CV (\%)** & **Mean** & **SD** & **CV (\%)** \\ \hline
1 & [PERSON] & 837.43 & 431.67 & 51.55 & 2073.85 & 1001.59 & 48.30 \\
2 & Makha & 995.16 & 589.48 & 59.23 & 1480.68 & 1460.56 & 98.64 \\
3 & [PERSON] & 698.61 & 486.52 & 69.64 & 1168.52 & 1381.72 & 118.24 \\
4 & Non Thai & 3081.27 & 2102.41 & 68.23 & 3386.89 & 1381.89 & 40.80 \\
5 & [PERSON] & 2048.71 & 1210.99 & 59.11 & 1450.53 & 1228.26 & 84.68 \\
6 & Banlang & 1843.36 & 305.77 & 16.59 & 2767.41 & 637.71 & 23.04 \\
7 & [PERSON] & 2451.42 & 931.95 & 38.02 & 3111.81 & 1303.07 & 41.87 \\
8 & Khang Phlu & 5057.71 & 1097.99 & 21.71 & 2206.29 & 1430.69 & 64.85 \\
9 & Samrong & 1451.51 & 734.07 & 50.57 & 2336.91 & 803.41 & 34.38 \\
10 & Kampang & 1960.48 & 486.55 & 24.82 & 2624.89 & 425.50 & 16.21 \\ \hline \hline
**Non Thai District** & **2156.02** & **1574.99** & **73.05** & **2377.38** & **1405.83** & **59.13** \\ \hline \hline \end{tabular}
\end{table}
Table 14: Statistical data of soil salinity prediction using RK of two measuring modes by sub-district.  
yields a higher score for total score calculation using the rank-sum method, as reported in Table 17.  
Table 16 shows the lowest ME value of the four methods for HH mode is OK and that for VV mode is IDW. The lowest RMSE value of the four methods for HH mode is the OK, and that for the VV mode is IDW. The highest R\({}^{2}\) value of the four methods for HH mode is the CCK, and that for the VV mode is IDW. Besides, the lowest PBIAS value of the four methods for HH mode is OK, and that for the VV mode is IDW.  
After applying the rank-sum method as a summary in Table 17, it can be seen that the OK and CCK methods deliver the highest total score, with 12. However, CCK provides the RMSE and R\({}^{2}\) values better than OK, while there is no difference in the ME and PBIAS values between OK and CCK. So, CCK is chosen as a suitable spatial interpolation method for soil salinity prediction of HH measuring mode. Meanwhile, the IDW is a suitable spatial interpolation method for soil salinity prediction of the VV measuring mode because it delivers the highest total score, with a value of 16. The derived maps of suitable spatial interpolation methods of the two measuring modes are further used to classify soil salinity severity classes.