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Previous research by many groups has shown that broad-band thermal infrared (TIR) imagers can detect buried explosive threat devices, such as unexploded ordnance (UXO), landmines and improvised explosive devices (IEDs). Broad-band detection measures the apparent temperature - an average over the wave band of the product of the true soil surface temperature and the emissivity. Broad-band detection suffers from inconsistent performance (low signal, high clutter rates), due in part to diurnal variations, environmental and meteorological conditions, and soil surface effects. It has been suggested that hyperspectral TIR imaging might have improved performance since it can, in principle, allow extraction of the wavelength-dependent emissivity and the true soil surface temperature. This would allow the surface disturbance effects to be separated from the soil column (bulk) effects. A significant, and as yet unanswered, question is whether hyperspectral TIR images provide better detection capability (higher probability of detection and/or lower false alarm rate) than do broad-band thermal images. TIR hyperspectral image data of threat objects, buried and surface-laid in bare soil, were obtained in arid, desert-like conditions over full diurnal cycles for several days. Regions of interest containing threat objects and backgrounds were extracted throughout the time period. Simulated broad-band images were derived from the hyperspectral images. The diurnal variation of the images was studied. Hyperspectral was found to provide some advantage over broad-band imaging in detection of buried threat objects for the limited data set studied.