Can subsurface soil salinity be predicted from surface spectral information? - From the perspective of structural equation modelling

An efficient and reliable method for detecting soil salinity in deep saline soils using remote sensing is required to better manage soil salinization. In this study, a laboratory evaporation experiment was conducted to determine how subsurface soil salinity can be determined using soil surface spectra. Ten soil columns were observed, and measurements were taken at specific time intervals to monitor the variations in soil salinity and moisture content at depths of 5 cm and 15 cm relative to soil surface spectra during the evaporation process. The structural equation modelling (SEM) method was used to analyse the relationships between the spectral reflectance data and the salt content in the subsurface soil (15 cm). The results showed significant correlations (standard path coefficient = −0.37, t = −6.00) between the spectral reflectance of the soil surface and the subsurface soil salinity and between different types of multispectral data, such as the Landsat Thematic Mapper (TM) data, and the subsurface soil salinity. Overall, the results implied that surface soil spectral information can be used to capture some subsurface soil properties and that remote sensing images could provide an alternative method for monitoring changes in deeper soils.