DISCRIMINATION OF POORLY EXPOSED LITHOLOGIES IN IMAGING SPECTROMETER DATA

High spectral resolution imagery produced by imaging spectrometers ena bles the discrimination of geologic materials whose surface expression is subpixel in scale. Moreover, the use of such data makes it possibl e to distinguish materials which are characterized only by subtle diff erences in the spectral continuum. We define the ''continuum'' as the reflectance or radiance spanning the space between spectral features. The capability to distinguish subpixel targets will prove invaluable i n studies of the geology of the Earth and planets from airborne and sp aceborne imaging spectrometers. However, subpixel targets can only be uniquely identified in a truly optimal sense through the application o f data reduction techniques that model the spectral contribution of bo th target and background materials. Two such techniques are utilized h erein. They are a spectral mixture analysis approach and a low probabi lity detection routine based on orthogonal subspace projection. These techniques were applied to the problem of detecting two different volc anic tuff units, one basaltic and one rhyolitic, in two different scen es of data measured by the airborne visible/infrared imaging spectrome ter (AVIRIS). These tuff units have limited exposures from an overhead perspective and have spectral signatures which differ from those of b ackground materials only in terms of subtle slope changes in the refle ctance continuum. Of the two approaches, it was found that the low pro bability detection algorithm was more effective in highlighting those pixels that contained the target tuff units while suppressing the resp onse of undesired background materials.