Abstract: To determine the origin of surface substrate for soil salinization and alkalization in the Songnen Plain, this study investigated Songyuan City based on Sentinel-2 multispectral images. Considering various commonly used indices like the soil salinity index (SSI), soil water index (SWI), and vegetation index (VI), this study constructed the optimal 3D spectral feature model to calculate the soil salinization-alkalization index (SSAI) for inversion of the soil salinization-alkalization status. Surface water and groundwater in areas subjected to soil salinization and alkalization were sampled to test their salt ion concentrations, followed by the analysis of salt ion sources according to the groundwater levels. The surface substrate was explored through planar grid layout and vertical stratified sampling. A total of 2 362 soil samples were collected in various layers within a depth of 5 m to test their pH and texture for the construction of a 3D surface substrate model. The results of this study reveal a positive linear correlation between the inversion result of remote sensing data and the topsoil salt content (coefficient of determination: R²=0.74). The study area was characterized by alkalization of sodium bicarbonate, with soil salt ions originating primarily from groundwater. The deep multilayer argillaceous soils acted as an aquiclude to prevent the downward infiltration, migration, and dilution of salt ions along with water. This surface substrate condition serves as the objective cause of soil salinization and alkalization in the study area.