Hyperspectral imaging provides an efficient means of mapping surface mineralogy, however, mineralogic maps produced from these data do not rake into consideration other geologic characteristics such as surface morphology and texture. Similarly, while advanced SAR systems such as the multifrequency, multipolarization SIR-C/X-SAR are well suited to mapping surface morphology parameters, they do not provide any mineralogic information. A combined approach provides visible/infrared imaging spectrometer (AVIRIS) and shuttle imaging radar-C (SIR-C/X-SAR) data for geologic mapping. AVIRIS data were calibrated to reflectance, spectral endmembers were selected, and abundance images were generated for specific endmembers using spectral mixing and matched filtering. SIR-C images were synthesized from the complex scattering matrix data for selected frequency/polarization combinations and X-SAR data were co- registered to form a multifrequency, multipolarization data set. The SAR and AVIRIS data were map-referenced and analyzed together along with Landsat TM and thermal infrared multispectral scanner data using geometric visualization and analysis techniques developed for hyperspectral data analysis. The results provide an example of the viability of an extended spectral signature approach, segmenting the terrain i top distinct lithologic units on the basis of combined mineralogic and morphologic characteristics. This approach has significant implications for future remote sensing missions and sensors. The research also demonstrates that multispectral and hyperspectral techniques can be successfully applied to combined optical/SAR data sets.