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Volume-5, Issue-2, April-2015
International Journal of Engineering and Management Research
Page Number: 712-718
Application of Principal Components Analysis for Exploration of
Alteration Mapping of Inland Placer Minerals between Kayalpatinam and
Ovari: Southern Tamilnadu coast, India
Kanimoli.V1, Sankar.R2, Saraswathi.P.L3, Rajamanickam.M4, Vijaya Sarathy.R5, Jose Ravindra Raj.B6
1,2,3
Post Graduate Scholar, Department of Civil Engineering, Prist University, Trichy-Thanjavur Highway,Vallam, Thanjavur, INDIA
4,5,6
Assistant Professor, Department of Civil Engineering, Prist University, Trichy-Thanjavur Highway,Vallam, Thanjavur, INDIA
ABSTRACT
The digital image processing plays an significant role in inland placer mineral resource assessment. The IRS-P6-LISS III imagery is used to identify the hydrothermal alteration zones for inland placer mineral exploration. Principal component analysis (PCA) is one of the most commonly adopted feature reduction techniques in image processing. By use of this technique to precisely map the inland placer minerals like ilmenite, rutile, sillimanite, zircon, monazite, garnet and almandine in southern Tamilnadu coastal stretch.PCA based band ratio of obtained from the image spectra (PCA bands I,II,III &IV in RGB)and verified against other conventional methods. The spectral signatures are used to construct new PCA band ratio are validated through field observation as well a USGS mineral spectrum. The derived PCA based analyzed output and field survey results indicates that the method is suitable for identifying alteration zones of inland placer mineral deposits and it is a complementary tool for inland placer mineral exploration in similar areas elsewhere.
Keywords---- IRS-P6, LISSIII, PCA, USGS, Placer, exploration
I.
INTRODUCTION
The word “Teri”, which means red. Inland red Teri sands of originated from weathering in situ of coastal dune sands. Teri sands of the southeast coast of Tamilnadu reveals high concentration of placer minerals like ilmenite,zircon,monazite,rutile,garnet,sillimanite,amphibol e,pyroxene and magnetite. The Concentration levels of total placer minerals in the different coastal segments are
vary from place to place.The Teri sands account for nearly 83% of the resources of placer Titaniamminerals assessed so far in Tamilnadu. The beach sands of Ovari region contain 3.2 million tonnes (Mt) of garnet at an average rating of 10.7%.zircon,monazite and sillimanite are found in both the beach and coastal Teri sands and hold potential as co-products or by-products. The major objective of Principal component analysis is reducing a huge set of variables to a little set that still contains most of the information on the huge data set. It's often used to sort data easy to explore and visualize.The multispectral satellite imagery has been enhanced through advanced digital image processing methods like principal component analysis (PCA) [1].The main objective of the study is to explore and detect placer mineral concentration from teri sand deposits.To identify with the alternation zones of inland placer minerals for the future exploration and management of mineral resources in a sustainable manner. The results observed in current work can be the scientific database for future detailed investigation for placer mineral exploration.
“This paragraph of the first footnote will contain the date on which you submitted your paper for review. It will also contain support information, including sponsor and financial support acknowledgment. For example, “This work was supported in part by the U.S. Department of Commerce under Grant BS123456”.
Dr.M.Rajamanickam,Assistant Professor, Center for Disaster Management,PristUniversity,Thanjavur,Vallam,Tamilnadu,India (e-mail: [email protected]).
R.Vijay Sarathy,Prof & Head.,Civil Engineering Department,Prist University,Thanjavur,Tamilnadu (e-mail:
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the National Research Institute for Metals, Tsukuba, Japan (e-mail: [email protected]).”
A. STUDY AREA
The study area is located southeast of Tamilnadu
coast, and lies between longitudes 77o40’ and
78o20’east,latitudes 08o10’and 08o
B. DATA USED
50’North as shown in Fig.1.The total length of the coast is about 60kmThe climate of the study area is considered by a hot summer and general dryness except during the southwestern monsoon.Theaverage annual rainfall at Port Tuticorin is 453.6mm.The main geomorphic units are beaches, cliffs, sanddunes, saltmarshes, reefs and other coastal landforms are noticed.The most of beaches are depositional in nature
with low to medium wave energy condition. The sand is
reddish in colour and contains 0.5%.moisture.It may be distinguished here that the name “Teri” is regional language of Tamilnadu, which means Red. Hencef,red sands are known as Teri sands at Tamilnadu. Widespread of Teri sand deposits with placer minerals occur as, coastal dune fields comprising barchan and transverse dunes and blowouts (of varying sizes and orientations) near Sattankulam and Kudiramoli [2].Teri deposits are continuous in north of the study area and discontinuous in the south There are two headlands along the study area one at Manappad and another at Tiruchendur. Manappad is the only rocky coast along the study area situated at an elevated level from the mean sea level (~25m) due to tectonic uplift with an emergent beach [3] Besideserosional features, Manappadcoast displays also typical depositional features like sand spit, lagoon, bay mouth bar etc.
This study is based on satellite and ancillary data.IRS-P6 image (175/038), acquired on 30 January and 28 March 2001 the images are of fine resolution (30 m) In the present paper an integrated use of field data,multispectral satellite data, USGS mineral spectra and survey of India topographical sheets were utilized for generation of mineral database. The following procedure was followed for inland placer mineral assessment.
II.
MATERIALS AND METHODSThe methodology involves various steps includes field observations, satellite image processing and mineral spectrum matching with conventional data as well as USGS mineral spectra.
A. Sample Collection
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A. Satellite DataThe exploration for inland placer mineral alteration zones in the studied district form the essential objective of this work.IRS LISS III has four spectral bands. These comprise of multi-spectral LISS III images corresponding to four spectral bands, namely, visible green band (0.52–0.59µm), visible red band (0.62-0.68µm),NIR band (0.77-0.86 µm) and short wave infrared band (1.55– 1.70µm).IRS-P6-LISS III image processing tools and softwares includes ENVI 3.2 and Arc GIS10.1used for analysis. Satellite image scenes (Path 101,Row68,Date,2010) covering the study area.The preliminary process of the images includes geometric correction, boundary tracking and radiometric correction. False color composite images (FCC) for the studied district were used to classify alteration zones in study area. Geometric correction has been applied with adequate number of ground control points taken from 1:50,000 scale topographic maps. Cubic convolution resampling method has been used to project the image according to Universal Transverse Mercator (UTM) system,WSG84,using topographic maps at scale 1:50,000with an output pixel size of 30 meters. Resampling process is carried out to determine the pixel values and to fill into the output image from the original image matrix. Radiometric balancing has been done to achieve a homogenous radiometric set of data. Mosaicing between the scenes has been conducted to have one set of composite image that is geometrically corrected and radiometrically balanced.
A. Principal Component Analysis
The extraction of spectral information related to this type of target the Linear Imaging Self Scanning (LISS-III) imagery has been accomplished through the use of image processing methods such as principal component analysis(PCA)[6].The foremost purpose of PCA study is to eliminate redundancy in multispectral LISS IIIdata. Principal component analysis of satellite images used foridentification and mapping of alteration in metallogenic provinces [7]-[10].Fig shows 4 multi-spectral LISS III images corresponding to four spectral bands; visible green(0.52–0.59 µm),visible red(0.62-0.68µm),NIR(0.77-0.86 µm) and short wave infrared (1.55–1.70 µm).The three images can be transferred as a unit by expressing each group of three corresponding pixels as vector (X1,X2,X3
(1)
The covariance matrix of the vector population is defined as
C
) respectively be the values of pixels in each three RGB component images.
x=E{(x-mx) (x-mx)T
T are matrixes of order n * n
}(2)
X – n dimensional (xand (x-x) (xx)
E {.}Cx is covariance of X
T-Denotes transpose
1
Fig.2 leads to the formation of a four element vector x= (x1, x2…..x4)T from each set of corresponding pixels in the images, the image size 564*564 pixels, so the population considered of (564)2 =318096 vectors from which the mean vector, covariance matrix and corresponding eigenvalues and often vectors were compared. The eigenvectors were then used as the rows of matrix A, and set of Y vectors using
Y=A (x-mx) x (3) A- Transformation matrix Similarly, we used
CY = A CXAT(4)
CY denotes diagonal matrix,
Cx Covariance to obtain C
III.
RESULTS
AND
DISCUSSIONS
Y
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The red teri sand-dunes have enriched
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India [11]The white dunes are found along the modern shoreline, whereas red dunes sit inland in huge patches, stratigraphically above the marine calcareous grit of Pleistocene age[12].Based on the PCA analysis four component images are derived Shown in figures (4.A,B,C,D).
Figure.3.A.LISS III visible green band (0.52– 0.59µm) band showing blunder view of land cover details, unable to find teri sand dunes and vegetation.Furthermore, PCA Band II visible red(0.62-0.68µm) showing distict variation in sandy patches from vegetative cover shown in Figure.3.B. In additionally NIR(0.77-0.86 µm) region we can identify teri sand dune with reds sand patches seen in figure 3.C.Similartly short wave infrared (1.55–1.70 µm) band region it showing the obvious depiction of placer mineral deposit patches are observed in Figure.4.D.
The PCA images shows that a large amount of garnet is deposited along the coastal dune of the study area. The PCA band III and band IV images (Fig.C& D) able to easily identified teri sand dune swith concentration of iron riched garnet and alamandine mineral deposits. Ilmenite is also deposited along the coast. The eigen values of LISS III four spectral bands statistics are shown in table.1.Similarly the covariance matrix obtain from different bands of images are shown in Table.2.The correlation matrix values ranges from minimum 0.117 to maximum 1.00.It indicates the the minus value of pure pixel derived from the image data set. Table.3. eigen vectors derived from the correlation matrix. The negative eigen value indicates-- 0.130 -0.194 showing the large amount of variance in the data unable to get pure pixel index.
A set of principal component images was generated Spectral identification of prospective areas of hydrothermal alteration[13] minerals is a common application of remote sensing to mineral exploration The Endmember spectra were then extracted from the LISS IIII image at 23m spatial resolution using the PPI,MNF,n-D Visualizer approach.Extracted mineral spectra were compared with a spectral library developed by the USGS and worked by various reseachers[14] to [22] for mineral identification.The end member spectra shown in Figure 4 are typical for those seen in placer mineral deposits.
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