Accurate characterization and monitoring of complex subsurface environments require the integration of all the available geophysical, geochemical and geological information. I developed a generalized cross-gradient procedure that seeks multiple geometrically similar images that simplify the integration of cross-property subsurface information. I jointly invert near-surface P-wave, S-wave, DC resistivity and magnetic data sets recorded at a field site and compound an integrated subsurface (geospectral) image based on the multiple property images found. It is shown that, by analogy to applications in satellite imagery, the geospectral image assembles the multiple subsurface parameter values under a common structural framework that facilitates their visualization and analysis.