Abstract
Southeastern Tibet features a complex geological environment and a high incidence of earthquakes. Earthquake-induced chain disasters pose a great threat to engineering construction and public safety in this area, and landslides are among the most frequent postearthquake disasters. To investigate the impact of earthquakes on landslides, this study constructed a comprehensive database for landslide susceptibility analysis based on various factors, including elevation, slope, slope direction, distances from roads and rivers, proximity to faults, land use patterns, rainfall patterns, and seismic parameters. By integrating the frequency ratio (FR) model with the analytic hierarchy process (AHP) model, this work delineated landslide susceptibility zones in southeastern Tibet. Subsequently, the susceptibility zoning layer was overlaid with the magnitude sensitivity layer and validated using ROC curve analysis to identify the earthquake magnitudes that exerted the greatest influence on landslides. Finally, by incorporating the distance from earthquake epicentres into our refined model framework, different monitoring levels for landslide susceptibility zoning were established. The AHP results show the relative importance of the landslide-influencing factors in southeastern Tibet can be ranked as follows: elevation, slope direction, distance from road, land use, distance from river, slope, and rainfall. The ROC values of the landslide models with seismic sensitivities of 1, 2 and 3 are 0.876, 0.883 and 0.877, respectively, indicating that earthquakes of magnitude 4 and above have a great influence on landslides in the study area. Through the overlay of the landslide susceptibility zoning map and the vector map of distance from seismic focal points, a correlation with the distance between landslide-prone areas and seismic focal points is identified. Within the extremely high susceptibility area and within 40 km of the focal point, there are 220 landslide points, accounting for approximately 34 % of the total landslides in the study area. Additionally, 133 landslide points are located in the extremely susceptible area and within 40–80 km of the focal point, representing approximately 20 % of the total landslides in the study area. The susceptible areas were assessed based on grades, resulting in the production of 4 maps depicting different levels of monitoring for landslide-prone areas. These maps are valuable tools for implementing landslide disaster prevention measures within the study area.
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