Spatial Distribution of Active Landslides and Identification of Dominant Driving Factor in the Main Urban Area of Lanzhou City

Objectives: With accelerating urbanization and the increasing frequency of extreme climate events, active landslides in urban areas have intensified, posing serious threats to human life and property. This study focuses on the main urban area of Lanzhou City, Gansu Province, to identify active landslides and analyze their dominant driving factors. Methods: Firstly, surface deformation rates in the satellite radar line of sight (LOS) were derived using generic atmospheric correction online service for InSAR (GACOS) assisted InSAR Stacking, and then projected along the slope direction. Active landslides were automatically identified through clustering methods, and an active landslide density map was constructed. Secondly, a comprehensive analysis of driving factors, including topography, geology, climate, hydrology, land cover, and anthropogenic activities, was conducted. Spearman correlation analysis and multicollinearity diagnostics were performed to identify and eliminate redundant variables, while retaining those with high independence. Finally, dominance Analysis was employed to quantitatively evaluate the relative importance of each factor in controlling the spatial distribution of active landslides. Results: A total of 331 active landslides were detected in the main urban area of Lanzhou, exhibiting clustered spatial distribution patterns, primarily concentrated in the Guanshangou–Xujiawan, Yanjia Ping, Agan Town–Liushuwan, and Dashaping–Fuergou regions. Dominance analysis revealed that distance to rivers, human activity intensity index (HAII), and slope are the top three driving factors influencing the spatial distribution of active landslides in the study area. Conclusions: These findings help clarify the spatial distribution mechanisms of active landslides in loess-covered urban areas, providing scientific support for landslide disaster mitigation and urban planning in Lanzhou City.