## 2 Materials and Methods
### Sources of Data and Preprocessing  
The data used in this study encompass topography, geological structures, engineering geology (lithology), climate (precipitation), and geological hazard records, as summarized in Table 1. To ensure the scientific validity of the model analysis and the accuracy of spatial representation, all datasets were projected to the WGS84 coordinate system during preprocessing and were standardized through spatial verification to ensure consistency and suitability for spatial analysis and modeling. (1) Topographic data: A geomorphological classification system based on Digital Elevation Model (DEM) data, developed by [PERSON] et al. (2020) [20] and [PERSON] (2022) [21], was employed. This method integrates multi-scale  
Figure 1: Overview map of the Qinghai–Tibet Plateau. geomorphic factor analysis, allowing for the accurate delineation of complex landform units across various spatial scales on the Plateau. The refined classification supports the investigation of potential associations between geomorphic features and geological hazards. (2) Geological structure data: Structural data are derived from the 1:1,500,000 Geological Map of the Qinghai-Tibet Plateau compiled by [PERSON] et al. (2013) [22]. This dataset includes information on active faults, fault density, and structural boundaries. Tectonic activity, as a fundamental internal driving force within the disaster-inducing environment, influences both rock fragmentation and the spatial patterns of hazards such as landslides and collapses. (3) Engineering geology (lithology) data: Lithological data are extracted from the ISRIC-WISE Global Soil Database (ISRIC, 2008), with a focus on lithological classifications specific to the Qinghai-Tibet Plateau. The spatial distributions of various lithological combinations were analyzed. Given the differing physical and chemical properties of rock types--such as weathering susceptibility, permeability, and structural stability--this factor significantly influences hazard sensitivity. Accordingly, spatial layers for engineering geology were developed to evaluate their contributions to hazard formation across the study area. (4) Climate (precipitation) data: Climate data are sourced from precipitation zoning results based on long-term meteorological observations (1978-2018) across Plateau stations, as reported by [PERSON] et al. (2022) [23] and [PERSON] et al. (2018) [24]. This dataset captures regional precipitation patterns, including annual totals, intensity, and seasonal variation, facilitating the quantitative analysis of precipitation as a trigger under varying geomorphic and tectonic contexts. (5) Geological hazard data: Hazard records were obtained from the national geological disaster census released by the Chinese Academy of Sciences, covering the period 2000-2020. This dataset includes 13,837 validated records of landslides, debris flows, and collapses (CLD) across the Qinghai-Tibet Plateau. Notably, disaster records are sparse in the northwestern and central Plateau due to lower population density and limited monitoring. After conducting topological validation and coordinate standardization, a temporally and spatially consistent hazard database was constructed. This database serves as the core for model validation, factor response analysis, and zoning assessment. (6) Study area boundary: The boundary of the Qinghai-Tibet Plateau was defined based on the delineation proposed by [PERSON] et al. (2014), which accurately represents the region's topographic extent and geological context while ensuring administrative alignment [25]. Preprocessing and standardization methods: On the GIS platform, the spatial zoning of topography, tectonics, lithology, and climate was conducted based on their natural