Spectral radiance data from Landsat's Thematic Mapper (TM) sensor were used to evaluate its effectiveness in differentiating among surface soils of similar properties and to identify the TM spectral band combination useful in estimating selected soil properties. Correlation, regression, and discriminant analyses were used in analyzing the data. The overall accuracy of the TM sensor in differentiating the surface soils was 97.2%. The order of importance of the TM bands that contributed the most in differentiating the soils was TM 6, TM 4, TM 5, TM 2, TM 7, TM 1, and TM 3, respectively. Significant correlations were found among the spectral radiance data and soil variables studied; however, the amount of variance explained was quite low. The prediction equation for estimating soil properties accounted for less than 40% of the variability in the data. The low percentages were attributed to atmospheric particles such as moisture, CO2, dust, etc. that affect the electromagnetic energy sensed from airborne and space platforms. It was concluded that even though the TM sensor is adequate for differentiating among similar soil types from the same soil order, the spatial resolution of the data (30 m) is still too coarse to be effectively used in generating equations for predicting soil properties such as clay percentages, iron oxide, and organic matter content.