We present a method for identifying hyperspectral textures composed of a set of given materials. The algorithm is invariant to illumination and atmospheric conditions as well as the spatial sampling of the texture. Only the spectral reflectance functions for the materials in the texture are required by the algorithm. A texture analysis method based on minimizing the squared error between a pixel spectrum and a synthetic spectral mixture allows pixels to be ranked according to consistency with the texture model. Experimental results using HYDICE imagery demonstrate the use of the method to identify hyperspectral textures under different conditions.