# A Combined Method for Preparation of Landslide Susceptibility Map in Izmir (Turkije)
## 4 Results and Discussion
### Evaluation of Model Performance  
As can be seen from the table of the Pearson's correlation of coefficient matrix given below, all the correlation coefficients between different independent variables were less than abs (0.80). In essence, the parameters used in the construction of the models were carefully selected for susceptibility analysis, and these parameters can be considered not to be physically related with each other. The Pearson's correlation coefficient matrix proves that the independent variables did not have a multi-collinearity problem (Table 8). The basic statistics of the outputs obtained by use of five methods are given in Table 9. It can be seen that the mean of CM and IOE are close to each other. The variances of remaining three methods are close to each other. Negative kurtosis coefficients indicate that the distribution has a lighter tail than a normal distribution. The negative skewness coefficients prove that similar behavior is observed for all model outputs, skewed to the left. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Extremely Low** & **Low** & **Moderate** & **High** & **Extremely High** \\ \hline LR & 2.07\% & 8.84\% & 28.82\% & 25.57\% & 34.7\% \\ AHP & 0.19\% & 6.27\% & 12.01\% & 36.7\% & 44.84\% \\ FR & 0.18\% & 2.72\% & 10.93\% & 31.88\% & 54.29\% \\ IOE & 0.17\% & 1.32\% & 8.71\% & 24.69\% & 65.11\% \\ CM & 0\% & 0.65\% & 4.42\% & 18.09\% & 76.84\% \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Percentages of susceptibility classes according to the method used. Figure 12: (**a**) Landslide susceptibility distribution of five classes in landslide inventory, (**b**) Landslide susceptibility distribution of five classes for whole study area. \begin{table}
\begin{tabular}{l l l l l l l l l l} \hline \hline
**Parameter** & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** \\ \hline (1) Slope aspect & \(1\) & & & & & & & & \\ (2) Density of discontinuity & \(-0.16\) & \(1\) & & & & & & & \\ (3) Lithology & \(-0.40\) & \(0.65\) & \(1\) & & & & & & \\ (4) Slope & \(-0.55\) & \(0.66\) & \(0.47\) & \(1\) & & & & & \\ (5) SPI & \(0.46\) & \(0.59\) & \(-0.03\) & \(-0.03\) & \(1\) & & & & \\ (6) Slope curvature & \(0.68\) & \(0.05\) & \(-0.24\) & \(0.04\) & \(-0.04\) & \(1\) & & & \\ (7) Elevation & \(-0.48\) & \(0.45\) & \(0.15\) & \(0.65\) & \(-0.27\) & \(-0.61\) & \(1\) & & \\ (8) Land use & \(-0.31\) & \(-0.10\) & \(0.38\) & \(0.48\) & \(-0.68\) & \(0.47\) & \(0.30\) & \(1\) & \\ (9) Distance from stream & \(-0.43\) & \(-0.48\) & \(0.41\) & \(-0.41\) & \(-0.67\) & \(-0.69\) & \(0.23\) & \(0.18\) & \(1\) \\ \hline \hline \end{tabular}
\end{table} 
Table 8: [PERSON]’s correlation of coefficient matrix. 4,3,2. and 1 in LSM correspond to susceptibilities of extremely high, high, moderate, low and extremely low. In order to question if the means of five models are significantly different from each other, t-tests were performed. A null hypothesis was identified: the means of two outputs were the same. The results obtained from the CM were compared with the outputs of the four remaining models. The t-test values were 39.79, 9.72, 8.02 and 1.91 for the four pairs, CM/LR, CM/AHP, CM/FR and CM/IOE, respectively. The corresponding critical t-values were in the vicinity of 1.64. The null hypothesis was rejected in these four analyses. Moreover, Friedman tests were employed to determine whether there was a statistically significant difference between the means of the outputs. For our extremely large database, the p-values were extremely low, and the results were not sufficiently meaningful to present here. The AUC (Area Under the ROC curve) is an important parameter ([PERSON] et al. [122]; [PERSON] et al. [123]) which gives valuable information about the accuracy of any model. For a perfect application, this parameter should be equal to 1.0. The threshold for random chance is 1.5. Following the ROC curves obtained by the various methods reveals that CM outperformed the other four methods (Figure 13).