We describe the development of a simulation framework for anomalous change detection that considers both the spatial and spectral aspects of the imagery. A purely spectral framework has previously been introduced, but the extension to spatio-spectral requires attention to a variety of new issues, and requires more careful modeling of the anomalous changes. Using this extended framework, we evaluate the utility of spatial image processing operators to enhance change detection sensitivity in (simulated) remote sensing imagery.