JOURNAL ARTICLE

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

Chandan KumarAmba ShettySimit RavalP. K. ChampatirayRam P. Sharma

Year: 2014 Journal:   ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences Vol: XL-8 Pages: 455-461   Publisher: Copernicus Publications

Abstract

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.

Keywords:
Endmember Hyperspectral imaging Pixel Remote sensing Geologic map Illite Geology Mineral exploration Mineralogy Computer science Artificial intelligence Clay minerals Geochemistry

Metrics

22
Cited By
1.93
FWCI (Field Weighted Citation Impact)
20
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Geochemistry and Geologic Mapping
Physical Sciences →  Computer Science →  Artificial Intelligence
Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology
Mineral Processing and Grinding
Physical Sciences →  Engineering →  Mechanical Engineering

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