# Correlation between Soil Moisture Change and Geological Disasters in E'bian Area (Sichuan, China)
## 4 Discussion
Lastly, remote sensing technology can provide long-term soil moisture monitoring data, which is useful for understanding and predicting long-term trends in geological disasters. This study is based on high-resolution remote sensing images from Landsat and captures subtle surface changes through detailed band data processing, providing high-precision foundational data for geological disaster monitoring and prediction. Additionally, terrain factors are extracted and classified using a digital elevation model (DEM), achieving the integration of multi-source data and providing more comprehensive and accurate foundational data support for geological disaster monitoring and prediction [73; 74; 75; 76]. On this basis, the NDVI-LST feature space was constructed, and the Temperature Vegetation Drought Index (TVDI) was calculated and analyzed for its trends, effectively reflecting the dynamic changes in soil moisture in the study area. Based on the evaluation of geological hazard susceptibility in this study area by some scholars using Geographic Information Systems and terrain factors, this paper added the classification criteria of soil moisture critical value, which could more accurately describe the promoting and hindering effects of soil moisture on geological hazards and put forward new and effective guiding ideas for the prevention and control of geological hazards in this region. This method not only considers the impact of vegetation coverage on soil moisture but also incorporates surface temperature as a key factor, making the assessment of soil moisture more comprehensive and accurate. This study reveals the changing trends and influencing factors of soil moisture in the study area. Through the analysis of the correlation coefficient (R\({}^{2}\)), it quantifies the high consistency between soil moisture and vegetation coverage. More importantly, by classifying the critical values of soil moisture, this study accurately describes the promoting and inhibiting effects of soil moisture on geological disasters, providing a scientific basis for the prevention and control of geological disasters. The research results showed that the variation in soil moisture in the study area is relatively stable, and the overall soil moisture content is high (0.18 < TVDI < 0.33). However, due to the large variation in topographic relief, it can provide power and be a source basis for geological disasters such as landslide and collapse, so the inversion value of TVDI is small. The minimum and maximum values of correlation coefficient (R\({}^{2}\)) are 0.60 and 0.72, respectively, indicating that the surface water content is relatively large, which is in good agreement with the calculated results of vegetation coverage, and is conducive to the restoration of ecological stability. Meanwhile, this method also can make up for the lack of geological engineering exploration data in the study area, resulting in a decrease in the accuracy of geological hazard assessment. The research results of this paper show that the special topographic characteristics of E'bian area are the basic conditions for the occurrence of geological disasters in this region. Rainfall and human activities affect the changes in soil moisture and vegetation coverage in this region. The lower the soil moisture is, the smaller the vegetation coverage is, and the surface is prone to wind and hydraulic denudation at this time, and the smaller the organic matter content is. This is not conducive to the formation of mineral rich areas with economic value. On the contrary, the higher the soil moisture, the greater the vegetation coverage, which makes it easier to form soil with a high decomposition of organic matter. Therefore, the innovation of this paper lies in the comprehensive application of high-resolution remote sensing images, DEM, NDVI-LST feature space, and TVDI to thoroughly analyze the relationship between soil moisture and geological disasters in the E'bian area.