## 3 Materials and Methods
### Indicator Selection  
The selection of risk assessment indicators for debris flow mainly considers the primary conditions for forming and developing debris flow disasters. From the quantitative evaluation requirements perspective, specific indicators need to reflect the debris flow risk. Geological conditions, material conditions, and trigger conditions play a crucial role in the distribution and activity of debris flows. When selecting debris flow indicators, it is necessary to consider the scientific, representative, comprehensive, and regional differences between the indicators. Table 1 shows the indicators selected by researchers worldwide in recent years in the study of debris flow risk assessment. Table 1 shows specific differences in the selection of evaluation indicators in different regions. Considering that rainfall within the study area is the same, it is difficult to accurately obtain the debris flow frequency and soil particle size. At the same time, the lithology and fault length of the strata can be reflected to a certain extent by the amount of material sources. The study  
Figure 3: Remote sensing images of the research area (GF-2). area is located in a scenic area with a relatively dense population. Therefore, based on on-site geological surveys, combined with the analysis results of drone images and multiple remote sensing images, there are nine specific factors that are important and closely related to the occurrence of debris flow in the research area and can be used as essential indicators for debris flow risk assessment. These are drainage density, roundness, average gradient of main channel, maximum elevation difference, Bengding coefficient of main channel, loose-material supply length ratio, vegetation area ratio, population density, and loose-material volume of unit area. This article utilizes multiple remote sensing images, digital elevation models (DEM), drone stereo aerial photography, and field investigations (Figures 1-3 and 5) (Table 2) to ultimately obtain the size of various risk assessment indicators for debris flow in the study area through calculations and depictions. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Factors** & [25] & [26] & [27] & [28] & [29] & [30] & [31] & [32] & [33] & **Time** \\ \hline Rainfall intensity & & \(\surd\) & \(\surd\) & & & & \(\surd\) & 3 \\ Daily rainfall & & & \(\surd\) & & & & & \(\surd\) & 2 \\ Cumulative rainfall & & \(\surd\) & \(\surd\) & & & & \(\surd\) & 3 \\ Main channel length & \(\surd\) & \(\surd\) & \(\surd\) & & & \(\surd\) & \(\surd\) & \(\surd\) & 6 \\ Gully slope angle & \(\surd\) & \(\surd\) & \(\surd\) & & \(\surd\) & \(\surd\) & \(\surd\) & 6 \\ Drainage density & \(\surd\) & \(\surd\) & \(\surd\) & & & \(\surd\) & \(\surd\) & \(\surd\) & 6 \\ Soil particle size & & \(\surd\) & \(\surd\) & & & & \(\surd\) & 3 \\ Basin area & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & 9 \\ Average gradient of main channel & \(\surd\) & & & \(\surd\) & \(\surd\) & & & \(\surd\) & 5 \\ Slope direction & & & & & \(\surd\) & & & & 1 \\ Vegetation coverage & \(\surd\) & & & \(\surd\) & & \(\surd\) & & 4 \\ Loose material volume & \(\surd\) & & & & & & \(\surd\) & & 2 \\ Population density & \(\surd\) & & & & & & \(\surd\) & 2 \\ Maximum elevation difference & \(\surd\) & & & \(\surd\) & \(\surd\) & \(\surd\) & & 5 \\ Bengding coefficient of main channel & \(\surd\) & & & \(\surd\) & & & \(\surd\) & 3 \\ Fault length & & & & & & \(\surd\) & & & 1 \\ Frequency & & & & & & \(\surd\) & & \(\surd\) & 3 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Factors frequently used in risk assessment of debris flow. Figure 4: Debris Flow risk assessment process. Vegetation area ratio (F7) (%): Low vegetation coverage can cause severe soil erosion in the basin. The value is obtained through drone aerial photography and remote sensing images, and the vegetation coverage is estimated based on the depth of the color.