Many rainfall-triggered landslides occurred in the Chenyulan river watershed in Central Taiwan during
typhoon Morakot in 2009. In this study, the landslide susceptibility model of the Chenyulan river watershed was developed and evaluated using a binomial logistic regression model based on 249 slope units. The factors considered while developing the landslide susceptibility model were rainfall, topography, geology, and slope condition (i.e., presence or absence of previous landslide events). Next, we tested the goodness-of-fit of the regression. Moreover, we performed receiver operating characteristic curve analysis with loss function to determine the best cutoff point. The cutoff value of probability corresponding to the best cutoff point was used to calculate the accuracy of the model (77%).
Overall, the model effectively predicted landslides by using relatively few factors because of progressive modeling and analysis. In addition, the results showed a significant relationship between landslide susceptibility and geological factors(the orientation of the weak plane) and the condition of slope (presence or absence of previous landslide events).The present study can provide a reference for subsequent studies on this topic.
Keywords: Landslide susceptibility model, binomial logistic regression, loss function, orientation of the weak plane,
presence or absence of previous landslide events.