 This study presents a novel approach to shadow classification using bitemporal imagery that exploits spectral radiometric, SR, change signatures associated with transient shadows. The method uses changes in intensity and intensity normalised blue waveband values to classify transient shadows across different material types, while deriving classification thresholds for persistent shadows based on hue to intensity ratio, HI, images. The results show improved mean accuracy and versatility with different image sets compared to the conventional approach of thresholding individual HI images based on frequency distributions. Additionally, overlaying bitemporal imagery facilitates normalisation of intensity values in transient shadow areas as part of an integrated procedure for near real-time change detection. This article was authored by Emanuel A. Story, Douglas A. Stowe, Lloyd L. Colter and others.