Due to its negative impacts on land productivity and plant growth, soil salinization is a tough problem, particularly in arid and semi-arid regions of the world. Therefore, monitoring, mapping and predicting soil salinization are of utmost importance regarding lessening and/or preventing further increase in soil salinity through some protective measures. The current study proposes an evaluating and predicting approach that is based on remote sensing (e.g., Landsat TM images), near sensing technologies (e.g., electromagnetic induction device, EM38) and soil sampling data in typical zone of Xinjiang Automonous region. Firstly, maps of soil salinity were obtained from accurate interpretation model of soil salinity using multiple regression method in study area. The uniform distribution of 3D scatter data was modelled by grid sampling point on map of soil salinity. Then, a three-dimensional soil salt distribution was characterized by inverse distance weighting method. The results showed that the coefficient of variation of soil salinity, an indicative of strength intensity variation for different seasons, ranging from 1.281 to 1.527. The soil salinity remained at a low level and it decreased with increase of depth in the study area. Map of three-dimensional distribution of the regional soil salt demonstrated that severe soil salinity located in Midwestern region of the studied area. The synthesized method based spectral indices from remote sensing, soil apparent electrical conductivity from electromagnetic induction device and data of soil sampling in this study had 0.908 of high correlation coefficient for assessment of regional soil salinity. Thus the application of this technique provides a new method to interpret and evaluate regional soil salinity in the three-dimensional spatial distribution characteristics in Xinjiang.