An empirical comparison of the EO-1 Hyperion, EOS ASTER, and Landsat ETM sensors was performed to examine the utility of these three sensors for gold-associated lithologic mapping in the southeastern Chocolate Mountains area, California. Three images were evaluated with respect to three aspects: classification accuracy, matched filtering score index and separability of the five significant rock types in the study area. The results show that the classifications from Hyperion and ASTER data are mostly similar with an overall accuracy of over 85 percent and kappa coefficient 0.81. Due to the presence of more SWIR and thermal bands, the Hyperion and ASTER images can achieve better lithologic mapping than ETM. The assessment of matched filtering score index and the separability also supports these findings. Hyperion can discriminate more similar classes than ASTER and ETM, while the better availability and spatial coverage makes the ASTER sensor more suitable for large-area lithologic mapping.