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

Abstract

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.

Keywords:

• AVIRIS-NG
• Igneous Layered Complex
• Index Image Composite
• Principal Component
• Spectral analysis
• Support Vector Machine

Disclosure statement

No potential conflict of interest was reported by the author(s).