Preliminary Results – Hyperspectral Image Analysis for Dolomite Identification in Tarbela Dam Region of Pakistan
Jibran Khan

Jibran Khan, Institute of Space & Planetary Astrophysics (ISPA), Department of Science, University of Karachi, Karachi, Pakistan.
Manuscript received on 07 February 2013 | Revised Manuscript received on 21 February 2013 | Manuscript Published on 28 February 2013 | PP: 30-34 | Volume-2 Issue-3, February 2013 | Retrieval Number: C0409022313/2013©BEIESP
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Abstract: The blessings of hyperspectral remote sensing are manifold and it has enabled researchers to locate, map and identify different materials on the surface of Earth. Hyperspectral remote sensing play a key role in mineral mapping activities and it can be a much powerful and cost effective tool for mineral development activities in a developing country like Pakistan where there are rich mineral resources but lack of means of extraction is still a constraint in their efficient usage for betterment of country’s economy. In this paper we investigate the adequacy of the hyperspectral remote sensing data acquired by Earth Observing -1 (EO-1) hyperspectral sensor, over an area of Tarbela Dam region (Lat. 320 05’N, Long. 720 41’ E), which is a rich mineral resource of Pakistan. Many notable minerals have been found in this region among which analysis of identification of dolomite through hyperspectral imagery of Tarbela Dam region is the major aspiration of this research article. The results presented in this paper may refer to the preliminary steps that can be taken for minerals identification using hyperspectral imaging in Pakistan. The analysis of spectral signature of the dolomite which is a sedimentary carbonate rock and a mineral both composed of calcium magnesium carbonate is described through software Erdas IMAGINE®. However large noise ratio showed to represent a constraint for dolomite identification as it is likely to conceal spectral information due to rocks and vegetation cover. In the end, we suggest some techniques to help improve these analyses.
Keywords: Hyperspectral remote sensing, Tarbela Dam, spectral information, noise ratio, mineral mapping

Scope of the Article: Remote Sensing