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Journal of Applied Remote Sensing

Application of ASTER and Landsat 8 imagery data and mathematical evaluation method in detecting iron minerals contamination in the Chadormalu iron mine area, central Iran
Author(s): Arsia Moghtaderi; Farid Moore; Hojjatollah Ranjbar
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Paper Abstract

Satellite images are widely used to map geological and environmental features at different map scales. The ability of visible to near-infrared (VNIR) scanner systems to map gossans, rich in iron and associated with weathered sulfide occurrences, as well as to characterize regoliths, is perhaps one of the most important current applications of this technology. Initial results of this study show that advanced space-borne thermal emission and reflection (ASTER), VNIR, and short-wave infrared radiometer scanner systems can be used successfully to map iron ores. By applying internal average relative reflectance, false color composite, minimum noise fraction transform, and mathematical evaluation method (MEM) techniques, iron contaminations were successfully detected in the Chadormalu iron mine area of central Iran. An attempt was also made to discriminate between the geogenic and anthropogenic iron contaminations in the vicinity of the Chadormalu iron deposit. This research compares ASTER and Landsat 8 data images and the MEM with the band ratio method in a full scope view scale and demonstrates ASTER image data capability in detecting iron contaminations in the Chadormalu area. This indicates that ASTER bands 3, 2, and 1 have a higher spatial (15 m) resolution compared with sensors used in previous works. In addition, the capability of the MEM in detecting Fe-contaminants, unlike the color judgments of the band ratio method, can discriminate between iron pollution in an alluvial plain and the Fe-contents of the host and country rocks in the study area. This study proved that Landsat 8 data illustrate exaggeration both in the MEM and band ratio final results (outputs) and cannot display iron contamination in detail.

Paper Details

Date Published: 14 February 2017
PDF: 22 pages
J. Appl. Rem. Sens. 11(1) 016027 doi: 10.1117/1.JRS.11.016027
Published in: Journal of Applied Remote Sensing Volume 11, Issue 1
Show Author Affiliations
Arsia Moghtaderi, Payame Noor Univ. (Iran, Islamic Republic of)
Farid Moore, Shiraz Univ. (Iran, Islamic Republic of)
Hojjatollah Ranjbar, Shahid Bahonar Univ. of Kerman (Iran, Islamic Republic of)


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