# Correlation between Soil Moisture Change and Geological Disasters in E'bian Area (Sichuan, China)
## 5 Conclusions  
Landsat satellite imagery, with its long coverage period and continuous data, is well-suited for long-term monitoring and change detection, enabling detailed capturing of surface changes. Additionally, it can capture temporal variations in the development of geological hazards. Due to the multiple bands covered by Landsat imagery, it provides rich spectral information that aids in extracting different surface features such as vegetation, water bodies, and soil and supports the calculation of various remote sensing indices. This study focuses on E'bian Yi Autonomous County as the research target area. Based on Landsat remote sensing imagery from 2018 to 2023, combined with in-depth analysis of digital elevation models (DEMs), a pixel binary model was used to retrieve the vegetation cover change pattern (FVC) in the study area, followed by mean statistical analysis. The key topographic factors influencing the occurrence of geological hazards were successfully extracted and finely classified. On this basis, an NDVI-LST feature space was constructed, where each pixel corresponds to an NDVI value and an LST value, visually presenting the relationship between vegetation cover and surface temperature, and further analyzing the spatial distribution of soil moisture. By fitting the obtained dry and wet edge equations, TVDI values were calculated, and ultimately, these were integrated with the development patterns of geological hazards for comprehensive study. The innovative methods adopted in this study and their integration with the development patterns of geological hazards are mainly reflected in the following two aspects:  
* Geological Hazard Identification: By combining TVDI data and DEM data, potential geological hazard areas were identified. High TVDI values (indicating low soil moisture) and unfavorable topographic conditions (such as steep slopes and gullies) are often high-risk areas for geological hazards. * Development Process Analysis: Using long-term series of Landsat imagery data, the development process of geological hazards at different time points was analyzed. By comparing TVDI values and DEM characteristics at different time points, the evolution patterns and triggering mechanisms of geological hazards can be revealed. This innovative method greatly enhances the monitoring accuracy and analytical capability of soil moisture dynamic changes in the research target area. Through a series of scientifically rigorous data processing and analysis methods, the following main conclusions were drawn:1. Compared with traditional data, remote sensing images of Landsat high-resolution data can better reflect soil moisture variation rules in the study area and are highly consistent with vegetation coverage variation rules. 2. FVC in the study area showed an overall growth trend from 2018 to 2022, and the composition structure of FVC significantly improved, with the improvement area of higher-grade FVC (45% < FVC < 65%) being 1501 km\({}^{2}\) and that of higher-grade FVC (65% < FVC < 100%) being 1715 km\({}^{2}\). In general, the area increased by FVC is greater than the area decreased by FVC. 3. The soil moisture variation in E'bian Yi Autonomous County is relatively stable, with the overall soil moisture content at a high level (TVDI values ranging between 0.18 and 0.33). This indicates that the region maintains certain moisture conditions, which are conducive to vegetation growth and ecological stability. 4. The calculated correlation coefficient (R\({}^{2}\)) ranges from 0.60 to 0.72, strongly demonstrating a significant positive correlation between surface water content and vegetation cover. This finding not only validates the accuracy of remote sensing in monitoring soil moisture but also reveals the important role of vegetation in soil and water conservation and climate regulation. 5. TVDI can accurately reflect the spatial distribution of soil moisture in the study area.