Volume XL-8
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 455-461, 2014
https://doi.org/10.5194/isprsarchives-XL-8-455-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 455-461, 2014
https://doi.org/10.5194/isprsarchives-XL-8-455-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

  28 Nov 2014

28 Nov 2014

Sub-pixel mineral mapping using EO-1 Hyperion hyperspectral data

C. Kumar1, A. Shetty1, S. Raval2, P. K. Champatiray3, and R. Sharma3 C. Kumar et al.
  • 1Dept. of Applied Mechanics and Hydraulics, National Institute of Technology Karnataka, Mangalore 575025, India
  • 2School of Mining Engineering, The University of New South Wales, Sydney NSW 2052, Australia
  • 3Dept. of Geosciences and Geohazards, Indian Institute of Remote Sensing, Dehradun 248001, India

Keywords: Mineral exploration, Feature extraction, Hyper spectral, MTTCIMF algorithm, Sub-pixel

Abstract. This study describes the utility of Earth Observation (EO)-1 Hyperion data for sub-pixel mineral investigation using Mixture Tuned Target Constrained Interference Minimized Filter (MTTCIMF) algorithm in hostile mountainous terrain of Rajsamand district of Rajasthan, which hosts economic mineralization such as lead, zinc, and copper etc. The study encompasses pre-processing, data reduction, Pixel Purity Index (PPI) and endmember extraction from reflectance image of surface minerals such as illite, montmorillonite, phlogopite, dolomite and chlorite. These endmembers were then assessed with USGS mineral spectral library and lab spectra of rock samples collected from field for spectral inspection. Subsequently, MTTCIMF algorithm was implemented on processed image to obtain mineral distribution map of each detected mineral. A virtual verification method has been adopted to evaluate the classified image, which uses directly image information to evaluate the result and confirm the overall accuracy and kappa coefficient of 68 % and 0.6 respectively. The sub-pixel level mineral information with reasonable accuracy could be a valuable guide to geological and exploration community for expensive ground and/or lab experiments to discover economic deposits. Thus, the study demonstrates the feasibility of Hyperion data for sub-pixel mineral mapping using MTTCIMF algorithm with cost and time effective approach.