# Correlation between Soil Moisture Change and Geological Disasters in E'bian Area (Sichuan, China)
## 2 Materials and Methods
### Study Area
The complex interaction between slope aspect and surface relief creates a topographic effect, which can influence the occurrence and evolution of geological disasters. For instance, the degree of surface relief can affect the stability and mobility of landslides. This topographic effect can lead to significant differences in surface temperatures for different slope gradients in the geographical environment, thereby affecting the Temperature Vegetation Dryness Index (TVDI). TVDI is calculated based on the empirical relationship between surface temperature and the Normalized Difference Vegetation Index (NDVI). Surface relief can influence both surface temperature and NDVI, and changes in local weather conditions can also affect surface temperature, thereby impacting the quality of TVDI. Moreover, TVDI is one of the effective means for assessing the risk of geological disasters, such as monitoring and predicting the development of landslides and debris flows. The ups and downs of terrain directly affect the sunlight exposure and the distribution of surface temperature. Therefore, the influence of the terrain effect must be taken into account when studying slope direction. Changes in surface form fluctuations may cause local temperature differences, which is closely related to the terrain effect. On steeper slopes, direct sunlight  
Figure 6: Aspect map of study region from 2018 to 2023.  
is more concentrated, resulting in relatively high surface temperatures, while on gentler slopes, sunlight is relatively uniform and surface temperatures may be stable. Therefore, in the context of surface fluctuation, slope orientation is not only a simple direction of surface inclination but also involves the regulation of temperature distribution by topographic effects, which also has an impact on the surface temperature reflection of TVDI (Figure 7). Terrain undulation analysis is a method that uses digital elevation models (DEMs) to gain more information about terrain features, which helps to understand the impact of various surface factors such as geological structure and geomorphological shaping processes. In addition, it can automatically detect terrain features (such as ridges, noses, cliffs, and peaks) by controlling the height and orientation of the light source and use an edge detection filter based on azimuth on the light relief to identify specific terrain features [36; 37]. In the process of terrain undulation analysis, this article adopts a more accurate analysis method based on the traditional method of terrain undulation analysis, that is, moving window analysis technology. Moving window analysis is a method of sliding window statistics on multidimensional data in a specified dimension. This method can calculate different statistics according to different window sizes and directions, divide the terrain surface into a small area, and combine the scale of terrain features in the study area to achieve high-resolution data selection through different algorithms and parameters. In the process of dealing with terrain smoothness and noise reduction, one can reduce noise and sharp transitions by analyzing each small area, making the terrain look more  
Figure 7: Fluctuation map of study region from 2018 to 2023.  
natural and real (Equation (1)). The calculation of the window size in terrain undulation analysis is based on statistical information within the region. Moving window analysis has many advantages in the field of Geographic Information Systems (GISs) and terrain analysis. It can analyze geographic data within local areas, which helps to capture the features of local terrain, landforms, and other geographic phenomena, making the analysis more detailed and meticulous [38; 39]. In terrain undulation analysis, the choice of window size is crucial. According to research findings [40; 41], for drainage basins, a window of 7 \(\times\) 7 units (217 \(\times\) 217 m) is most suitable. For mountainous areas, a window of 9 \(\times\) 9 units (90 \(\times\) 90 m) works best.