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• EC e , SAR and ESP are highly correlated with the true electrical conductivity, σ. • σ is able to predict the in-depth soil salinity and sodicity from EC e , SAR and ESP. • 2-D maps show the vertical variation of the soil salinity and sodicity. • Electromagnetic conductivity imaging can be used for efficient soil monitoring. Salt related problems in soils can refer to an excess of soluble salts (saline soils), a dominance of exchangeable sodium in the soil exchange complex (sodic soils), or a mixture of both situations (saline-sodic soils). These categories are important because the impacts and management vary accordingly. Electromagnetic induction (EMI) methods and inversion techniques have been used to obtain electromagnetic conductivity images of the soil true soil electrical conductivity (σ) which can be used to estimate soil salinity and other soil properties in-depth and over large areas. However the potential to predict both soil salinity and sodicity with these methods has not been fully investigated. In this study, data collected with an EMI instrument (EM38) at two modes and heights and an inversion algorithm were used to obtain σ. Soil samples were collected at five layers to a depth of 1.35 m, at sampling sites along the EMI transects, and used for laboratory determination of the soil physico-chemical properties – electrical conductivity of the soil saturation paste extract (EC e), sodium adsorption ratio (SAR), pH, cation exchange capacity (CEC), exchangeable sodium percentage (ESP), volumetric water content (θ), and particle size distribution. A principal component analysis (PCA) was performed to analyze the correlation between σ and the soil physico-chemical properties. Correlations between σ and EC e , ESP and SAR could be established and prediction results were evaluated using the leave-one-out cross validation method and calculating the root mean square error of prediction (RMSEP). It was possible to predict EC e (RMSEP = 2.03 dS·m−1), SAR (RMSEP = 4.68 (mmol c ·L−1)0.5), and ESP (RMSEP = 3.83%) from σ and to classify the soil according to salinity and sodicity. The results show that it is possible to use EMI to monitor soil salinity and sodicity in risk areas rapid and efficiently, which is required to conserve and improve the soil functions. [ABSTRACT FROM AUTHOR]