A recent study focused on landslide susceptibility evaluation in Xichang City, Sichuan Province, an area known for its geological hazards, particularly landslides.

The study area spans approximately 2,889.8 square kilometers and is characterized by mountainous terrain and a history of significant geological activity.

Xichang City has experienced major earthquakes, including a devastating M7 earthquake in 1850, which contributed to its ongoing landslide risk.

Key factors influencing landslide susceptibility were identified, including NDVI, distance from faults, slope, and proximity to rivers, after removing terrain relief evaluation.

The research emphasizes the importance of identifying high-risk areas for landslides to inform disaster prevention policies and protect community infrastructure.

Rainfall-triggered landslides pose a significant risk due to their sudden nature, highlighting the need for improved hazard prediction methods.

Simulations indicated that extreme rainfall scenarios could trigger slope failures, with a failure probability of 92.5%, compared to 82.9% for earthquakes.

The study analyzed extreme rainfall scenarios using Gumbel distribution, revealing critical rainfall amounts over three days, which are essential for understanding landslide triggers.

To enhance predictive accuracy, the study proposes a framework that combines UAV remote sensing and numerical simulation, addressing limitations in current methodologies.

Increased activity in the fault zone has raised concerns about potential landslides, prompting the need for thorough assessments to mitigate disaster risks.

The findings from this research provide a new alternative for timely disaster management and control implementation in landslide-prone areas.

The final landslide susceptibility zoning classified areas into varying levels of risk, offering a crucial tool for effective risk assessment and management.