Military land platforms are often deployed around the world in very different climate zones. Procuring vehicles in a large range of camouflage patterns and colour schemes is expensive and may limit the environments in which they can be effectively used. As such this paper reports a modelling approach for use in the optimisation and selection of a colour palette, to support operations in diverse environments and terrains. Three different techniques were considered based upon the differences between vehicle and background in L*a*b* colour space, to predict the optimum (initially single) colour to reduce the vehicle signature in the visible band. Calibrated digital imagery was used as backgrounds and a number of scenes were sampled. The three approaches used, and reported here are a) background averaging behind the vehicle b) background averaging in the area surrounding the vehicle and c) use of the spatial extension to CIE L*a*b*; S-CIELAB (Zhang and Wandell, Society for Information Display Symposium Technical Digest, vol. 27, pp. 731-734, 1996). Results are compared with natural scene colour statistics. The models used showed good agreement in the colour predictions for individual and multiple terrains or climate zones. A further development of the technique examines the effect of different patterns and colour combinations on the S-CIELAB spatial colour difference metric, when scaled for appropriate viewing ranges.