Soil salinization has become a worldwide issue affecting agricultural development. Statistical methods and spatial analysis were used to analyze the degree and type of saline soils and their spatial distribution. The driving factors of soil salinity were explored using Geodetetcor models. In this study, 84 soil samples were collected from a 0–20 cm soil layer, and the total salt concentration and salt ion composition were measured. The results of statistical analysis and cluster analysis showed that SO₄²⁻ and Ca²⁺ had the highest concentrations of salt ions in terms of anion and cation contents, respectively. The interpolation results indicated that the study area was dominated by mild saline soils, with sulfate-type saline soils and chloride-sulfate-type soils dominating. Results of the factor detector suggested that the distance to the irrigation system (0.425), and distance to the drainage system (0.42), explained salinity more strongly in the Shardara district, and elevation (0.326) was the most important influencing factor for salinity in the Mahtaaral district. Results of the interaction detector indicate that human factors (distance to irrigation canals ∩ distance to drainage canals) had a stronger explanation both in the Shardara and Mahtaaral districts. This research provides a scientific basis for soil salinity regulation and management, which is crucial for sustainable agricultural development.