TY - JOUR
T1 - Discrimination of iron ore deposits of granulite terrain of Southern Peninsular India using ASTER data
AU - Rajendran, Sankaran
AU - Thirunavukkarasu, A.
AU - Balamurugan, G.
AU - Shankar, K.
N1 - Funding Information:
The authors are thankful to Ministry of Science and Technology, Department of Science and Technology, New Delhi for the extended facilities to carry out this work through the sanctioned Projects – GEMIORD (SR/FTP/ES-01/2000) and SPECSIGNS (NRDMS/11/1153/06). The authors are sincerely thanking the anonymous reviewers for their constructive comments and suggestions.
PY - 2011/4/30
Y1 - 2011/4/30
N2 - This work describes a new image processing technique for discriminating iron ores (magnetite quartzite deposits) and associated lithology in high-grade granulite region of Salem, Southern Peninsular India using visible, near-infrared and short wave infrared reflectance data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Image spectra show that the magnetite quartzite and associated lithology of garnetiferrous pyroxene granulite, hornblende biotite gneiss, amphibolite, dunite, and pegmatite have absorption features around spectral bands 1, 3, 5, and 7. ASTER band ratios ((1 + 3)/2, (3 + 5)/4, (5 + 7)/6) in RGB are constructed by summing the bands representing the shoulders of absorption features as a numerator, and the band located nearest the absorption feature as a denominator to map iron ores and band ratios ((2 + 4)/3, (5 + 7)/6, (7 + 9)/8) in RGB for associated lithology. The results show that ASTER band ratios ((1 + 3)/2, (3 + 5)/4, (5 + 7)/6) in a Red-Green-Blue (RGB) color combination identifies the iron ores much better than previously published ASTER band ratios analysis. A Principal Component Analysis (PCA) is applied to reduce redundant information in highly correlated bands. PCA (3, 2, and 1 for iron ores and 5, 4, 2 for granulite rock) in RGB enabled the discrimination between the iron ores and garnetiferrous pyroxene granulite rock. Thus, this image processing technique is very much suitable for discriminating the different types of rocks of granulite region. As outcome of the present work, the geology map of Salem region is provided based on the interpretation of ASTER image results and field verification work. It is recommended that the proposed methods have great potential for mapping of iron ores and associated lithology of granulite region with similar rock units of granulite regions of Southern Peninsular India. This work also demonstrates the ability of ASTER's to provide information on iron ores, which is valuable for mineral prospecting and exploration activities.
AB - This work describes a new image processing technique for discriminating iron ores (magnetite quartzite deposits) and associated lithology in high-grade granulite region of Salem, Southern Peninsular India using visible, near-infrared and short wave infrared reflectance data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Image spectra show that the magnetite quartzite and associated lithology of garnetiferrous pyroxene granulite, hornblende biotite gneiss, amphibolite, dunite, and pegmatite have absorption features around spectral bands 1, 3, 5, and 7. ASTER band ratios ((1 + 3)/2, (3 + 5)/4, (5 + 7)/6) in RGB are constructed by summing the bands representing the shoulders of absorption features as a numerator, and the band located nearest the absorption feature as a denominator to map iron ores and band ratios ((2 + 4)/3, (5 + 7)/6, (7 + 9)/8) in RGB for associated lithology. The results show that ASTER band ratios ((1 + 3)/2, (3 + 5)/4, (5 + 7)/6) in a Red-Green-Blue (RGB) color combination identifies the iron ores much better than previously published ASTER band ratios analysis. A Principal Component Analysis (PCA) is applied to reduce redundant information in highly correlated bands. PCA (3, 2, and 1 for iron ores and 5, 4, 2 for granulite rock) in RGB enabled the discrimination between the iron ores and garnetiferrous pyroxene granulite rock. Thus, this image processing technique is very much suitable for discriminating the different types of rocks of granulite region. As outcome of the present work, the geology map of Salem region is provided based on the interpretation of ASTER image results and field verification work. It is recommended that the proposed methods have great potential for mapping of iron ores and associated lithology of granulite region with similar rock units of granulite regions of Southern Peninsular India. This work also demonstrates the ability of ASTER's to provide information on iron ores, which is valuable for mineral prospecting and exploration activities.
KW - ASTER image processing
KW - Granulite terrain of Southern India
KW - Iron ores
KW - Lithological mapping
KW - Remote sensing
UR - http://www.scopus.com/inward/record.url?scp=79952699159&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952699159&partnerID=8YFLogxK
U2 - 10.1016/j.jseaes.2011.01.004
DO - 10.1016/j.jseaes.2011.01.004
M3 - Article
AN - SCOPUS:79952699159
SN - 1367-9120
VL - 41
SP - 99
EP - 106
JO - Journal of Asian Earth Sciences
JF - Journal of Asian Earth Sciences
IS - 1
ER -