Salt-affected landscapes are highly sensitive to changes in climatic, edaphic and hydrological conditions in time and space in semi-arid regions such as Arsanjan plain, southern Iran. The objective of this study was to combine digital satellite data with ground based measurements of ECe by cokriging method to possibility improve the soil salinity maps of study area. Soil samples in the 85 sampling site (10187 ha)were collected from 0-30 cm depths, georefrenced using GPS receiver, analyzed for ECe in a saturated soil paste. The data analyses were conducted in three stages for ordinary and cokriging interpolation: (a)normality tests were applied (Kolmogrov-Smirnov); (b)distribution was analyzed by classical statistics; (c)geostatistical parameters were calculated for each variable as a result of corresponding semivariogram analysis. A promising approach for the spatial prediction of soil property distribution taking into account secondary information ,from remotely sensed data from LISS-III receiver of IRS-P6 satellite, as application of cokriging methods that is given at a finer resolution than the sampled soil data. The results indicated that ECe is highly passively (p≤ 0.01)correlated with spectral values of band 1 of LISS-III receiver. Therefore, we used the spectral values of band 1 as secondary information for applying the cokriging method to predicate ECe in the study area. Mean square error (MSE)was used to evaluate the performance of the map prediction quality. The best prediction method for mapping ECe was cokriging in combination with the spectral data from spectral value of first band of IRS satellite with the smallest MSE indicating the highest precision. There was some similarity in the map pattern of pH and ECe as produced by ordinary kriging and cokriging methods. However, ordinary kriging was over-smoothed the spatial variability of ECe than cokriging. Comparatively, it seems that cokriging soil ECe map reflects local variation more than ordinary kriging.