Landsat TM and radar JERS-1 SAR (L-Band) imagery of the Itremo area, central Madagascar, were processed to emphasize structural geology features including folded quartzite ridges and plutons. TM band ratios 5/7, 5/1, 5/4∗3/4 were assigned to RGB. Band 5/7 highlights pelitic schist, band 5/1 emphasizes mafic igneous rocks, and 5/4∗3/4 distinguishes mafic from non-mafic rocks. In a second technique, band 5/7 was replaced with registered L-band radar imagery because radar is useful for differentiating between granite, granodiorite, diorite and serpentinite. The last technique evaluated in this study used the spectral information from the radar image as well as the 5/7, 5/1, 5/4∗3/4 band ratio bands. Supervised classification training sites were selected using nine classes (clouds, quartzite, schist, gneiss, gabbro and basalt, granite, vegetation, water, and cloud shadows). The band ratio classification results are fairly accurate (a confusion matrix shows an accuracy of 89.346) and correspond well with geologic maps of the area showing complexly refolded nappes of quartzite, carbonate, schist, gneiss and gabbro, intruded by late granites. The radar, 5/1, 5/4∗3/4 classification (accuracy of 89.04) shows significant differences from the band ratio classification, with fewer schist pixels displayed in the radar, 5/1, 5/4∗3/4 classification, but with greater resolution of structural features including faults, fold nappes, and foliations. More pixels are displayed as mafic gneiss, and fewer quartzites appear in the radar classification. Some areas classified as quartzite in the first classification (and on the geologic maps) were classified as clouds in the radar/band ratio classification. This indicates that the 5/7 band contains significant spectral information that the radar band does not contain, which aided in mapping quartzite. This comparison illustrates that combined use of TM band ratioing merged with radar imagery can emphasize both spectral and textural features that aid geologic mapping using supervised classifications. A third technique was examined where a supervised classification was performed on an image containing the 5/7, 5/1, 5/4∗3/4, and radar bands. The confusion matrix for this classification produced an accuracy of 91.23 which was better than either the 5/7, 5/1, 5/4∗3/4 or the radar, 5/1, 5/4∗3/4. It is preferable to keep all band ratio bands and the radar band to produce the most complete supervised classification image for geological feature discrimination.