# Lithological Mapping Research Based on Feature Selection Model of Relief-RF
## 4 Results
### Comparison between Lithological Maps of Different Optimisation Methods
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**PCA**} & \multicolumn{3}{c}{**MNF**} & \multicolumn{3}{c}{**ICA**} & \multicolumn{3}{c}{**GLCM**} \\ \cline{2-13} \cline{5-13} \multicolumn{1}{c}{**Lithological Classes**} & \multicolumn{3}{c}{**Overall Accuracy: 62.63\%**} & \multicolumn{3}{c}{**Overall Accuracy: 64.34\%**} & \multicolumn{3}{c}{**Overall Accuracy: 65.21\%**} & \multicolumn{3}{c}{**Overall Accuracy: 58.87\%**} \\  & \multicolumn{3}{c}{**Kappa Coefficient: 0.60**} & \multicolumn{3}{c}{**Kappa Coefficient: 0.61**} & \multicolumn{3}{c}{**Kappa Coefficient: 0.62**} & \multicolumn{3}{c}{**Kappa Coefficient: 0.56**} \\ \cline{2-13}  & \multicolumn{3}{c}{**Producer’s**} & \multicolumn{3}{c}{**User’s**} & \multicolumn{3}{c}{**Average**} & \multicolumn{3}{c}{**Producer’s**} & \multicolumn{3}{c}{**User’s**} & \multicolumn{3}{c}{**Average**} & \multicolumn{3}{c}{**Producer’s**} & \multicolumn{3}{c}{**User’s**} & \multicolumn{3}{c}{**Average**} \\ \hline \(Q_{4}^{pl}\) & 59.26 & _69.89_ & 64.58 & 63.90 & 76.20 & 70.05 & 70.78 & 74.87 & 72.83 & 57.60 & 54.37 & 55.99 \\ \(Q_{3}^{pl}\) & 75.14 & 85.12 & 80.13 & 83.02 & 85.01 & 84.02 & 78.52 & 85.06 & 81.79 & 83.11 & 86.44 & 84.78 \\ \(Q_{16}\) & 49.29 & 37.23 & 43.26 & 46.31 & 40.19 & 43.25 & 48.45 & 41.07 & 44.76 & 35.00 & 53.36 & 41.48 \\ \(N_{27}\) & 35.40 & 69.37 & 52.39 & 41.15 & 89.50 & 65.33 & 35.63 & 95.09 & 65.36 & 56.78 & 93.21 & 75.00 \\ \(E_{3g}\) & 86.33 & 52.82 & 72.28 & 86.80 & 59.49 & 73.15 & 86.33 & 56.63 & 71.48 & 87.85 & 50.64 & 69.25 \\ \(E_{1-2}\) & 38.05 & 38.37 & 38.21 & 39.48 & 40.59 & 40.44 & 43.88 & 45.39 & 44.64 & 36.03 & 21.34 & 28.69 \\ \(K_{\rm opt}\) & 67.84 & 49.79 & 57.91 & 71.11 & 49.88 & 60.50 & 67.84 & 49.11 & 58.48 & 80.23 & 55.32 & 67.78 \\ \(Z^{2}\),\(d_{\rm ch}\) & 80.47 & 71.00 & 75.74 & 81.09 & 68.28 & 74.69 & 82.79 & 71.77 & 72.08 & 50.08 & 47.85 & 48.97 \\ \(Z^{2}\),\(d_{\rm ch}\) & 60.94 & 70.50 & 67.52 & 55.67 & 63.21 & 59.44 & 66.67 & 70.89 & 68.78 & 64.68 & 86.00 & 75.34 \\ \(Z^{2}\),\(d_{\rm ch}\) & 67.24 & 63.24 & 65.24 & 70.23 & 60.32 & 65.28 & 67.13 & 63.83 & 65.48 & 50.92 & 64.30 & 57.61 \\ \(J_{1-2}\) & 61.38 & 67.33 & 64.36 & 60.77 & 78.07 & 69.42 & 59.44 & 66.08 & 62.76 & 29.06 & 69.77 & 49.42 \\ \(J_{1-2}\) & 70.29 & 95.55 & 82.92 & 70.88 & 86.00 & 79.74 & 69.01 & 92.62 & 80.82 & 60.47 & 87.93 & 74.20 \\ \(C_{3 zh}^{c}\) & 51.70 & 77.82 & 64.76 & 51.23 & 76.44 & 63.84 & 56.73 & 76.02 & 66.38 & 41.75 & 63.30 & 52.53 \\ \(C_{3 zh}^{c}\) & 59.84 & 60.32 & 60.08 & 66.98 & 66.14 & 66.56 & 65.56 & 74.28 & 69.92 & 87.14 & 61.69 & 74.42 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: The classification accuracies and kappa coefficients of PCA, MNF, ICA and GLCM. Figure 6: Lithological mapping results of different datasets classified by RF. (**a**) PCA datasets; (**b**) ICA datasets; (**c**) MNF datasets; (**d**) texture datasets of 9 \(\times\) 9 window size. Figure 8 presents the weights of 114 features calculated by the Relieff algorithm. Here, b1-b10 corresponds to the bands of Sentinel-2, b11-b17 corresponds to the PC1-PC7 components, b18-b27 corresponds to the ICA1-ICA10 components, b28-b34 corresponds to the MNF1-MNF7 components and b35-b114 corresponds to features of the mean, variance, homogeneity, contrast, difference, entropy, second moment and correlation of each spectral band. In the primary selection stage, 64 features with weight values of >0.005 were selected as the primary optimised datasets. In particular, the datasets included 1 spectral feature, 6 PC components, 8 IC components, 7 MNF components and 42 texture components. Then, the average accuracy reduction of each feature selected by [PERSON] was calculated using RF (Figure 9). The higher the MDA, the more important the variable. The MNF2 and MNF3 components were the most important features, with average precision reductions of 1212.28 and 905.12, respectively, followed by the mean of band2, the ICA3 component and the ICA2 component.