Estimat ing spatial variability of saline soil electrical conductivity (EC) which was intensely correlative with salinity content is an important issue in costal region.In this study, semivariogram was firstly used to explore the spatial correlation of EC for four depths of 0~20 cm layer, 20~40 cm layer, 40~60 cm layer and 60~100 cm layer on a 20 m by 20 m sampling grid, EC distribution at the four layers were then est imated using ordinary kriging, and then cross-semivariogram was analysed to explore coregionalized relationship between top layer and deeper layers.Finally cokriging was used to improve saline soil EC estimation at deeper layers by treating the samples of 0~20 cm depth as auxiliary variable and the original and reduced samples of the other three layers as primary variable.Compared with the ordinary kriging, the root-mean-square error produced by cokriging decreased by 9% to 25.1%, the average standard error decreased by 9.4% to 21.9%, correlation coefficient between the predicted value and the observed value increased by 46% to 85%.The analysis results indicated the reduction of the original sampling density of 40% would have resulted in no evident loss of spatial information.Cokriging was shown to be a more accurate and economic method, and it allowed easily obtained variables to be used to estimate the difficultly obtained variable based on the correlation on between two variables, and not only can greatly improve prediction accuracy, but also can save the sampling cost.