研究目的
To study the relationship between shallow groundwater depth, soil moisture, and land surface temperature and investigate the possibility of using retrieved land surface temperature through Landsat 8 satellite imagery for estimating and mapping soil moisture and groundwater level in a semiarid region of Iran.
研究成果
There is a significant relationship between shallow groundwater depth, soil moisture, and land surface temperature. Groundwater depth and soil moisture can be estimated and mapped using LST from satellite imagery, with RMSE of 0.37 m for groundwater and 0.038 cm3/cm3 for soil moisture. This approach is useful for soil, water, and climate studies, reducing the need for costly field measurements.
研究不足
The study is limited to a specific semiarid region in Iran with 59 and 39 sample points, which may not be representative of other areas. The use of Landsat 8 imagery and specific algorithms (e.g., split window) may introduce errors in LST retrieval. Ground measurements were taken over a short period (56 days with no significant changes), potentially missing temporal variations.
1：Experimental Design and Method Selection:
The study involved field measurements of groundwater level and soil moisture, and retrieval of land surface temperature (LST) from Landsat 8 imagery using the split window algorithm. Linear regression was used to analyze relationships between variables.
2：Sample Selection and Data Sources:
Groundwater level was measured at 59 observation wells, and soil moisture was measured at 39 locations in the 0-5cm soil layer in a study area in southwest Iran. A Landsat 8 image (path/row 165-39) was used for remote sensing data.
3：List of Experimental Equipment and Materials:
Observation wells (diameter 2.5 cm, depth 2 meters), GPS for positioning, equipment for soil moisture measurement (not specified), Landsat 8 satellite imagery, MODIS atmosphere profiles product (MOD07) for water vapor content.
4：5 cm, depth 2 meters), GPS for positioning, equipment for soil moisture measurement (not specified), Landsat 8 satellite imagery, MODIS atmosphere profiles product (MOD07) for water vapor content.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: Installed wells and measured groundwater levels and soil moisture simultaneously with Landsat 8 overpass. Processed Landsat image with atmospheric correction using FLAASH, converted to surface reflectance, retrieved LST using split window algorithm. Extracted values at corresponding pixels for regression analysis.
5：Data Analysis Methods:
Used linear regression to find relationships between LST, groundwater depth, and soil moisture. Evaluated with coefficient of determination and RMSE. Generated maps using Kriging interpolation and applied regression models.
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