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Assessing the hazard of potential landslides is crucial for developing mitigation strategies for landslide disasters. However, accurate assessment of landslide hazard is limited by the lack of landslide inventory maps and difficulty in determining landslide run-out distance. To address these issues, this study developed a novel method combining the InSAR technique with a depth-integrated model. Within this new framework, potential landslides are identified through InSAR and their potential impact areas are subsequently estimated using the depth-integrated model. To evaluate its capability, the proposed method was applied to a landslide event that occurred on November 3, 2018 in Baige village, Tibet, China. The simulated results show that the area with a probability of more than 50% to be affected by landslides matched the real trimlines of the landslide and that the accuracy of the proposed method reached 85.65%. Furthermore, the main deposit characteristics, such as the location of maximum deposit thickness and the main deposit area, could be captured by the proposed method. Potential landslides in the Baige region were also identified and evaluated. The results indicate that in the event of landslides, the collapsed mass has a high probability to block the Jinsha River. It is therefore necessary to implement field monitoring and prepare hazard mitigation strategies in advance. This study provides new insights for regional-scale landslide hazard management and further contributes to the implementation of landslide risk assessment and reduction activities. [ABSTRACT FROM AUTHOR]

In this study, based on the frictional velocity-weakening law used in continuum modeling, an adapted Hertz-Mindlin contact model between particles and the ground surface is established to accurately simulate the landslide dynamics process. Moreover, the long-period seismic waves indicating the dynamic characteristics of large landslides are adopted to determine the computational parameters for the discrete element method (DEM). By combining the force-time functions obtained from the long-period seismic waves and numerical modeling, the dynamic parameters and reasonableness of the simulation results of the first Baige landslide on October 11, 2018, in eastern Tibet, China, have been validated. The friction coefficient obtained in this study is also in agreement with the relationship between the volume and friction coefficients reported in the literature. Taking the same model and parameters, the dynamic process leading to the second Baige landslide on November 3, 2018, is analyzed. The modeled profile and position of the maximum thickness of the deposits arising from the two landslides both match the observations well. It is demonstrated that this combination procedure is feasible for the prediction and identification of areas susceptible to large landslides. [ABSTRACT FROM AUTHOR]