Spatial distribution of near-fault landslides along Litang fault zones, eastern Tibetan Plateau.

Active fault zones are areas impacted by intense tectonic activity, where geohazards such as landslides occur and their distribution characteristics vary across segments. Using the Litang fault zone in the eastern Tibetan Plateau as an example, this study cataloged landslides within a 10 km range on both sides of the fault zone. The Litang fault zone was divided into four sections based on landform characteristics and the spatial distribution of active faults. A comprehensive analysis was conducted on the relationship between landslide distribution and topography, lithology, and active faults in different sections. Additionally, the study employed a random forest model to compare landslide susceptibility between the whole-region and its sub-regions. The results show that lithology and topography significantly influence the distribution of landslide types. The Upper Triassic sandstone, Slate exhibit more debris flows in areas with slopes ranging from 5° to 35°, while slopes >35° in the Upper Triassic sandstone, Slate are prone to unstable slopes. Rock avalanche occur in Upper Triassic sandstone, Slate, and Quaternary sand and gravel. Active faults play a key role in control ling landslides distribution through distance, hanging wall, locked segment, and direction effects. The number of landslides is positively correlated with the activity of faults. Additionally, the dip angle and motion characteristics of faults have significant influence on the distribution of landslides. The results of landslide susceptibility evaluation show that sub-region models have higher accuracy than the whole-region model. This study provides a new method for exploring the spatial distribution of landslides and can provide scientific reference for reducing landslide disasters in active fault zones. • Landslides is significantly influenced by distance, hanging wall, locked section, and directionality of the active fault • Fault activity is positively correlated with landslide numbers, while the dip angle and motion affect distribution pattern • Sub-regional model can effectively reveal the spatial differences in landslide susceptibility along the active fault zone [ABSTRACT FROM AUTHOR]