Mapping of ferric ( and ferrous ( iron oxides distribution using band ratio techniques with ASTER data and geochemistry of Kanjamalai and Godumalai, Tamil Nadu, south India

P, Gopinathan ; S, Parthiban ; T, Magendran ; Fadhil Al-Quraishi, Ayad M. ; Singh, Ashok K. ; Singh, Pradeep K. (2020) Mapping of ferric ( and ferrous ( iron oxides distribution using band ratio techniques with ASTER data and geochemistry of Kanjamalai and Godumalai, Tamil Nadu, south India Remote Sensing Applications: Society and Environment, 18 . p. 100306. ISSN 23529385

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Official URL: http://doi.org/10.1016/j.rsase.2020.100306

Related URL: http://dx.doi.org/10.1016/j.rsase.2020.100306

Abstract

The iron ores found in Tamil Nadu State, South India, are major varieties that have been confined with banded magnetite quartzite. The occurrence, distribution, and grade of these deposits significantly vary according to their geological structure and geomorphologic control. In this article, presents a novel approach, based on spectral remote sensing and digital processing of ASTER data, to identify and characterize the iron ores of Kanjamalai and Godumalai areas located in Tamil Nadu, India. By analyzing the ASTER images, the abundance of iron oxides including ferric (Fe3+) and ferrous (Fe2+) components was determined. The band ratioing technique, a multiband analysis was used to generate the abundance of iron oxide content in various parts of the study area using different band combinations such as band 2/band 1 (for Fe3+) and band 5/band 3 + band 1/band 2 (for Fe2+). The geochemical analysis is an important part of this work to arrive with the outcome of band ratio techniques to decipher the relationship of the band ratio to the chemical composition of the ore samples. Accordingly, the correlation between the results of the geochemical analysis of the samples collected from the random locations was determined by Pearson's coefficient of correlation (ρ) and compared with the corresponding locations in the abundance image. In addition to ρ, various factors such as mean (μ), variance (σ2) and corresponding standard deviations (σ) were also analyzed for a comparative analysis. This comparative analysis indicated that most of the samples have considerably high iron oxide content in the locations. Thus, this study shows the possibility of detecting iron oxide content and its spatial distribution by using ASTER satellite images analysis. Hence, from the mapping results, it is evident that the band ratio technique of ASTER images can be used to map and characterize with limited fieldwork and geochemistry

Item Type:Article
Source:Copyright of this article belongs to Elsevier Science.
ID Code:125435
Deposited On:04 Feb 2022 13:30
Last Modified:04 Feb 2022 13:30

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