Application of the LAND-SUITE software with a benchmark dataset for landslide susceptibility zonation

We propose the usage of LAND-SUITE software to carry out 16 landslide susceptibility models exploiting the benchmark dataset provided by the session organizers. The software allows the application of Linear Discriminat Analysis (LDA), Logistic Regression (LR) and Quadratic Discriminant Analysis (QDA) as statistical methods, together with the Combination Forecast Model (CFM), which combines the outputs of the former three methods. Each of the mentioned models has been applied considering the two provided different landslide presence variables (presence1 and presence2), resulting in 8 susceptibility maps that takes into account the complete set of explanatory variables. Then, we have taken advantage of the variables analysis outputs provided by LAND-SUITE, and the process has been repeated with a reduced set of 10 explanatory variable. The variables selection has been carried out following the principles of independence between the explanatory variables, and trying to optimize the contribution of each of them to the model performance, for which leave-one-out tests and significance p-value of the LR outputs have been consulted. Results show a slight, but generalized, improvement of the model performances when the presence2 dataset is used, against the presence1. The model performance is also maintained or very sensitively decreased when the amount of explanatory variables is reduced from 26 to 10. However, the Area Under the ROC Curve (AUC) ranges between 0.75 and 0.82 in any of the tests. In addition, 9 out of the 10 selected variables are the same for both presence1 and presence2 tests. Uncertainty associated to each of the models has been also computed by means of the bootstrap resampling method.