Spectral decomposition can produce dozens of attributes for a single data set, far exceeding the ability for direct visualization. Some solutions have been proposed. The state-of-the-art approach is via the use of principal component analysis. However, this approach has significant inherent weaknesses, such as a lack of inclusion of spatial information and a tendency to inflate noise. Previous work has shown the ability of the image grand tour to construct lower-dimensional views of spectral information resulting in multiple images showing distinct architectural components. I propose a novel workflow for constructing color images to display multiple structures simultaneously. These images are constructed in a way that makes them complementary, leading to rich color images that are useful for interpretation. I demonstrate the value of this workflow though application to a land survey over Tertiary channels from south Texas.

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