Soil salinization is one of the most critical eco-environmental problems in arid and semiarid regions, which constrains vegetation growth and, therefore, exerts crop yield and agricultural production. Integrated satellite remote sensing and near sensing technology based on electromagnetic induction instruments is an advanced method for monitoring and forecasting soil salinization. In this contribution, remote sensing and electromagnetic induction EM38 and its mobile sensing system are used to evaluate soil salinity at the delta oasis between the Weigan River and the Kuqa River in the north rim of the Tarim basin. Spatio-temporal variation of soil salinity in response to dry and wet seasons is analyzed by using GIS and geo-spatial statistics. Spatial variability of soil salinity is analyzed by Universal Kriging, Spectral Index Regression and Regression-Universal Kriging. Our results show that apparent soil electrical conductivity (EC_1:5) is significantly correlated with salinity, therefore, EC_1:5 can be used as a surrogate for salt content. The correlation coefficient between apparent electrical conductivity (EM38) and EC_1:5 is significance at P<0.01, indicates EC_1:5 can be estimated with multiple regression equation using EM_V and EM_H as independent variables. Soil electrical conductivity in dry and wet seasons in the study region shows strong spatial autocorrelation. Considering the scale dependency of spatial variation, the nested spherical models are fitted for semi-variance of top soil (0-10cm). Regression-Universal Kriging is identified as the best method in terms of the accuracy of predicting spatial variability of soil salinity. We conclude that this study may provide a theoretical reference for rapid and accurate assessment of soil salinity and prevention of soil re-salinization.