This study was planned to examine the use of LandSat ETM+ images to develop a model for monitoring spatial variability of soil cation exchange capacity in a semi-arid area of Neyshaboor. 300 field data were collected from specific GPS registered points, 277 of which were error free, to be analysed in the soil laboratory.The statistical analysis showed that therewas a small R-Squared value, 0.17, when we used the whole data set. Visual interpretation of the graphs showed a trend among some of the data in the data set. Forty points were filtered based on the trends, and the statistical analysis was repeated for those data. It was discovered that the 40 series were more or less in the same environmental conditions; most of them were located in disturbed soils or abandoned lands with sparse vegetation cover. The soil was classified into high and medium salinity, with variable carbon (1.0 to 1.6%), heavy textured and with high silt and clay. Finally it was concluded that two different models could be fitted in the data based on their spatial dependency. The current models are able to explain spatial variability in almost 45 to 65% of the cases.