Airborne imaging spectroscopy of igneous layered complex and their mapping using different spectral enhancement conjugated support vector machine models

We used Advanced Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral data for deriving automated layered igneous intrusion maps by implementing the support vector machine (SVM) algorithm. We proposed a spectral analysis based approach to identify a set of optimum input spectral bands for deriving SVM-based maps of layered rocks of Sittampundi Layered Complex, India. We used three SVM models: (a) in the first model, we implemented SVM using nine spectral bands for deriving spectral indices to delineate different rocks; (b) in the second model, we used three Principal Component (PC) bands, which suitably preserved the spectral variance of all the bands used for deriving spectral indices of rocks; and (c) In the third model, all the spectral bands of AVIRIS-NG were used as input for the SVM model. We found PC based SVM model was superior as compared to the other two models in deriving automated map of layered rocks.