Using mixture analysis for soil information extraction from an AVIRIS scene at the Walnut Gulch

Spectral Mixture Analysis (SMA) has been used to extract qualitative and quantitative information about common features in an imagery at the subpixel level. At the Walnut Gulch Experimental Watershed (Arizona) this technique was used to produce the soil spectral map and quantify the fractions of each soil endmember on an AVIRIS image. SMA was applied on the base of image and reference endmembers. Four image endmembers (McAllister and Stronghold soils, green vegetation, and shade) were needed to model AVIRIS data on the base of image endmembers. There was a general agreement between field observation and the delineation of the boundaries of McAllister and Stronghold soil series through the spectral map generated by SMA. Dark soils (Graham and Epitaph soil series) and shade fractions was separated only in the spatial context. A technique called target test was used to detect for the presence of reference endmembers on AVIRIS data. On the base of six detected reference endmembers SMA was successfully applied for subset of image pixels.