Lithological mapping of Kanjamalai hill using hyperspectral remote sensing tools in Salem district, Tamil Nadu, India

Palanisamy Arulbalaji; Balasubramanian Gurugnanam

doi:10.1117/1.JRS.11.036027

19 September 2017 Lithological mapping of Kanjamalai hill using hyperspectral remote sensing tools in Salem district, Tamil Nadu, India

Palanisamy Arulbalaji, Balasubramanian Gurugnanam

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 11, Issue 3, 036027 (September 2017). https://doi.org/10.1117/1.JRS.11.036027

Abstract

This study uses advanced spaceborne thermal emission and reflection radiometer (ASTER) hyperspectral remote sensing techniques to discriminate rock types composing Kanjamalai hill located in the Salem district of Tamil Nadu, India. Kanjamalai hill is of particular interest because it contains economically viable iron ore deposits. ASTER hyperspectral data were subjected to principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF) to improve identification of lithologies remotely and to compare these digital data results with published geologic maps. Hyperspectral remote sensing analysis indicates that PCA (R∶G∶B=2∶1∶3), MNF (R∶G∶B=3∶2∶1), and ICA (R∶G∶B=1∶3∶2) provide the best band combination for effective discrimination of lithological rock types composing Kanjamalai hill. The remote sensing-derived lithological map compares favorably with a published geological map from Geological Survey of India and has been verified with ground truth field investigations. Therefore, ASTER data-based lithological mapping provides fast, cost-effective, and accurate geologic data useful for lithological discrimination and identification of ore deposits.

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Palanisamy Arulbalaji and Balasubramanian Gurugnanam "Lithological mapping of Kanjamalai hill using hyperspectral remote sensing tools in Salem district, Tamil Nadu, India," Journal of Applied Remote Sensing 11(3), 036027 (19 September 2017). https://doi.org/10.1117/1.JRS.11.036027

Received: 21 February 2017; Accepted: 5 July 2017; Published: 19 September 2017

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