Evaluation of landslide susceptibility in southeast Tibet based on a random forest model
In this study,we investigated the main factors influencing the development of landslides in southeast Tibet by using the random forest model to determine the susceptibility of the area to them.We identified 306 landslides in the area through field investigations,the interpretation of remote sensing data,and the literature.Moreover,we used the frequency ratio model to quickly determine the susceptibility of the area to landslides,and chose non-landslide samples for regions with a low susceptibility to them to provide a suitable dataset to train the random forest model.The weights of the parameters were calculated to generate a map of the susceptibility of the area to landslides to analyze the main factors controlling their occurrence.The accuracy of the proposed model was verified by plotting its ROC curve and calculating the AUC of the offline curve.The results of predictions by the model showed that highly susceptible areas were mainly concentrated at the confluence of Yigong Zangbo and Palong Zangbo,and in the large bend of Yarlung Zangbo River.The density of faults,elevation,and slope were,respectively,the three most important features with regard to the susceptibility to landslides,and the AUC of 0.940 of the model showed that it was accurate.Our analysis showed that the study area had a complex geological structure owing to the long-term influence of tectonic action,with large faults on the east and west sides,and the Himalayan frontal fault zone on the south side.With the development of the fault zones,especially in the region that was highly susceptible to landslides,the faults intersected,and multiple extrusions led to the fragmentation of rocks and the development of joints.Therefore,the intersection of Yigong Zangbo and Palong Zangbo as well as the region containing the large bend of Yarlung Zangbo River were highly susceptible to landslides.The proposed model provided a theoretical basis for accurately predicting landslides and appropriately managing disasters in southeast Tibet.
southeast Tibetrandom forest modellandslide susceptibilityfault density
万方数据
维普
