Remote sensing can be used to recognize altered rocks because their reflectance
spectra differ from those of the unaltered rocks (Sabins, 1999). Hydroxyl-bearing
minerals (in sericite, argillic and alunitic zones) and iron oxides (in
gossan zone) can be detected by remote sensing techniques. ETM+,
ASTER, SPOT and AVIRIS data have been widely used for mineral exploration
associated with hydrothermal alteration (Abrams et al., 1977, 1983;
Buckingham and Sommer, 1983; Goetz et al., 1983; Conradsen and
Harpoth, 1984; Amos and Greenbaum, 1989; Drury and Hunt, 1989; Swayze
et al., 1998; Ramadan et al., 2001; Rowan et al.,
2003; Ranjbar et al., 2004; Chen et al., 2007). Porphyry
copper and epithermal gold deposits can be clearly enhanced by remote
sensing methods due to extensive hydrothermal alteration such as potassic,
sericitic, silicification, argillic, alunitic and propylitic (Sinclair,
2004). At the same time, iron oxide minerals are developing over many
of the porphyry and epithermal deposits due to oxidation sulfide minerals.
In this study, we have processed Enhanced Thematic Mapper Plus (ETM+)
data from Landsat 7, which was launched in April 1999. Bands 1 to 7 are
in blue, green, red, near infrared and shortwave infrared with 30 m ground
resolution. The thermal infrared band (band 6) of ETM+ has
a ground resolution of 60 m. The panchromatic 8 band has a resolution
of 15 m (Gupta, 2003). The TM bands spectral ranges are shown in Table
In addition to ETM+ data analysis, interpretation of airborne
geophysics data (magnetometery and radiometry) can also be used for porphyry
and epithermal systems exploration (Dickson et al., 1996; Ranjbar
et al., 2001; Ranjbar and Honarmand, 2004).
|| TM spectral passband
The aim of this study is to process ETM+ images using different
techniques and analyze airborne geophysics data (magnetometry and radiometry)
for locating porphyry copper and epithermal gold prospects in Eastern
Iran. The study area is located 70 km Southwest of Birjand city, the center
of South Khorasan province in Eastern Iran. The climate in the district
is arid to semi-arid and vegetation is very weakly developed, optimizing
the possibility for observation of bedrock alteration from satellite imagery.
The investigated area is situated within the eastern part of the so-called
Lut block of eastern Iran. Eastern Iran and particularly the Lut block,
has a great potential for different types of mineralization as a result
of its past subduction zone tectonic setting, which lead to extensive
magmatic activity forming igneous rocks different geochemical compositions.
The Lut block is characterized by extensive exposure Tertiary volcanic
and subvolcanic rocks formed due to subduction prior to the collision
of the Arabian and Asian plates (Camp and Griffis, 1982; Tirrul et
al., 1983; Berberian et al., 1999).
Most of the study area is covered by upper Eocene-Oligocene altered volcanic
rocks including andesite, dacite, tuff and ignimbrite. These rocks are
intruded by porphyritic felsic to intermediate intrusive rocks consisting
of monzonite, diorite and microgranodiorite porphyry stocks. Sedimentary
rocks in this area consist of conglomerates, minor middle Eocene to upper
Eocene tuffaceous marls in the southeastern to eastern area and Quaternary
sediments (Fig. 1).
Different types of metal ore bodies, such as porphyry Cu, Cu-Au-Fe-oxide
(IOCG), vein type, massive sulfide, Au-epithermal, intrusion-related gold
systems and Sn-W-skarns and also non-metal deposits (bentonite, kaoline)
have already been documented in the Lut block. Four porphyry copper and
epithermal gold prospects in this region (Fig. 1) are
named Maherabad, Sheikhabad, Khopik and Hanich. Each is associated with
a well- developed area of hydrothermal alteration.
Maherabad prospect area is a Cu-Au porphyry system. Maherabad prospect
is dominated by subvlcanic intrusive rocks such as monzonite and diorite
porphyry stocks that intruded into upper Eocene-Oligocene volcanic rocks
(andesite, tuff and dacite) (Fig. 1). Quartz- Sericite-Pyrite
(QSP), argillic and propylitic alteration are most common in the area.
Alteration minerals include quartz, sericite, carbonate, chlorite, epidote
and clay minerals. Intense quartz stockwork associated with pyrite and
minor chalcopyrite as well as oxidized zone minerals such as malachaite,
iron oxides, clay minerals and copper wad is associated with mineralization
in this region. Cu (300 ppm to up to 1 wt %) and Au (200 to up to 500
ppb) anomalies are coincident with the alteration zones.
Sheikhabad prospect consists of argillic, alunitization, sericitic and
silicified zones which are best developed within upper Eocene-Oligocene
andesite, tuff, ignimbrite and dacite that are partly intruded by diorite
porphyry dikes (Fig. 1). Dissiminated minor pyrite and
secondary iron oxides are present in this region. Au and Cu anomalies
are coincident. This area can be a high-sulfidation epithermal gold system,
which formed above a Cu-Au porphyry deposit.
Khopik prospect area is a Cu-Au porphyry deposit. The geology of the
Khopik prospect area is partly characterized by hornblend-monzonite porphyry
associated with potassic alteration (secondary biotite+ magnetite+quartz±chlorite±K-feldspar±calcite),
which is in faulted contact with volcanic rocks such as andesite and dacite.
Most of this area is dominantly volcanic rocks (Fig. 1).
Other hydrothermal alteration includes sericitic, argillic, tourmalization
and propylitic zones that have been telescoped with potassic alteration
by faulting activity. Stockwork, open space filling and dissiminated mineralization
are recognized. Pyrite and magnetite as well as minor chalcopyrite are
common in this area. Oxidized zone consists of malachaite and iron oxides.
Geochemical data show that Cu (300 ppm to up to 1.5%) and Au (150 to up
to 2000 ppb) concentration are coincident.
Hanich prospect area is similar to low-sulfidation epithermal systems.
The rocks are dominantly altered andesite and dacite (Fig.
1). Argillization, sericitization and silicification are common hydrothermal
alteration in this area. Mineralization is not seen at surface.
MATERIALS AND METHODS
In this study, we have analyzed ETM+ data for the identification
of hydrothermal alteration. Processing procedures were done by ENVI 4.0
software. The investigated area is within an approximately 374 km2
subset of the ETM+ scene (WRS- Path =159, Raw = 038, Acquisition
data 2002/08/06). Bands1, 2, 3, 4, 5, 7 and 8 have been used for this
study. The images have been corrected by using control points from topographic
sheets. Both subscenes are jointed together to form a single image. Different
image processing techniques such as false color composite images, ratio
images, color composite ratio image, Principal Component Image Analysis
(PCA), Intensity-Hue-Saturation (IHS) transformation, filtering, supervised
classification and unsupervised classification are normally used for delineating
the favorable areas for further exploration.
Simplified regional geological map of study area modified
after the Sar-e-chah-e-shur map (Vassigh and Soheili, 1975), Mokhtaran
map (Movahhed-avval and Emami, 1978) and Khosf map (Eftekharnezhad
et al., 1989). The location of four known prospect areas is
In this study, three different
processing techniques have been used for detection of porphyry Cu-Au and
epithermal Au deposits in eastern Iran. These are as follow: (1) false
color composite, (2) color composite ratio images and (3) Principal Component
The airborne geophysics data we have used in this research involved magnetometry
and radiometry done over the South Khorasan province in 2005 by Geological
Survey of Iran (GSI). The aim of this survey was exploration for mineral
deposits in eastern Iran. The flight line spacing was chosen at 200 m.
The elevation of flight and elevation of sensor were 65 and 30 m, respectively.
The obtained results from ETM+ images processing and their
integration with airborne geophysics data have been confirmed by on the
ground field geology such as geological, alteration and mineralization
mapping, geochemical explorations and magnetic susceptibility measurements
in the district.
RESULTS AND DISCUSSION
ETM+ data analysis: Reflectance spectra of some common
clay minerals, alunite and iron oxides are shown in Fig.
2 and 3. TM band 7 (2.1- 2.4 μm) absorption
features detect mainly clay and sheet silicates, which contain Al-OH-
and Mg-OH- bearing minerals and hydroxides in the alteration zone, due
to molecular vibrational processes becoming very prominent (Fig.
2). These minerals have higher reflectance values within TM band 5
(1.55-1.75 μm) (Fig. 2).
Iron oxides, which contain Fe-OH bearing minerals in the gossan zone,
have higher absorption within ETM+ band 1 (0.45-0.52 μm)
and higher reflectance within TM band 3 (0.63-0.69 μm) (Fig.
3). These bands provide a useful tool for detection of alteration
minerals assemblage in different image processing techniques described
False color composite image: Several false color composite images
were produced for enhancing the identification of hydrothermal alteration
in the study area. Figure 4 is a false color composite
image of TM bands 7-5-4 shown in red, green and blue respectively. Sericitic
and argillic alteration zones in Maherabad, Sheikhabad, Khopik and Hanich
prospect areas can be distinguished by a white-green color. The prophylitic
zones were recognized by brown color. In Khopik area, this is in brown-orange
color due to intense chloritization and epidotization. Another small area
of alteration is detected in southeastern region, north of Bid village,
within andesite and tuff. This can to be a new prospect area for further
exploration. Vegetation has a higher reflectance in TM band 4 (0.75-0.90 μm).
||Reflectance spectra of some common clay minerals (after
||Spectral reflectance curves for jarosite, hematite and
goetite (after Sabins, 1997)
Vegetation locations were shown by blue
color in the study area. The color composite RGB: 754 did not show very
good results for lithologic discrimination. The Kuh-e-Shah dacite and
volcanic rocks south of it were recognized by dark green and violate color
respectively. Microgranodiorite unit in the Southeastern part of district
were characterized by white color, whereas tuff unit in northwestern part
of the area has a similar color. Volcanic rocks in the northern part of
the study area were detected by violate color that are similar to these
rocks in south and southeastern area (Fig. 4).
Color composite ratio images: Ratio techniques are a highly effective
means of minimizing brightness variations owing to the topographic slope
and changes in albedo. In this technique, bands with high reflectance
are divided by bands with high absorption.
|| Red-Green-Blue color composite of bands 7, 5 and 4
Therefore a ratio of band 5/
band 7 would yield very high values for altered zones comprising dominantly
hydroxyl- bearing minerals. This characteristic of phyllosilicates has
been used in numerous mineral exploration investigations. With the same
technique, iron oxide minerals can be detected by the band 3/band 1 ratio
Color composite ratio images are produced by combining three ratio images
in red, green and blue. An advantage of the color composite ratio images
is that it combines the distribution patterns of both iron minerals and
hydrothermal clays. A disadvantage is that the color patterns are not
as distinct as in the individual density- sliced images (Sabins, 1999).
More than 20 color composite ratio images have been produced for target
location. Two of these are presented here. In the RGB: 5/7, 5/4, 3/1 (Fig. 5), the area in white, bright blue- green, pink and yellow shows a
response of band 5 and 7 (Al-OH- bearing minerals) and band 3 and 1 (Fe-OH-
bearing minerals). The four prospect areas can be detected by this technique.
The small altered region to the east of Khopik prospect area can also
be distinguished by white- pink pixels too. Propylitic alteration can
be recognized by yellow- green color in this area. Vegetation is detected
by red color (Fig. 5). Discrimination of different rock
unites is similar to previous technique shown Fig. 4.
In bright red is Kuh-e-Shah dacite, in violate to green- violate is unaltered
volcanic rocks, in blue- white is microgranodiorite unit and in blue is
tuff unit of northwestern study area (Fig. 5).
The band ratio RGB: 5/7, 2/7, 7/4 shows hydrothermal alteration in pink,
blue, dark blue and yellow colors. Five altered areas have been shown
in Fig. 6. Vegetation is in orange. Kuh-e-Shah dacite
and volcanic rocks are in yellow- orange and yellow- green color, respectively.
The tuff unit and propylithic zone do not differ in color and both are
in dark blue (Fig. 6).
Principal Component Analysis (PCA): The Principal Component Analysis
(PCA) is widely used for alteration mapping in metallogenic provinces
(Kaufman, 1988; Crosta and Moore, 1989; Bennet et al., 1993; Rutz-
Armenta and Prol-Ledesma, 1998; Abrams et al., 1983; Tangestani
and Moore, 2002; Ranjbar et al., 2004; Jing and Panahi, 2006).
This technique is a multivariate statistical technique that selects uncorrelated
linear combinations (eigenvector loadings) of variables in such a way
that each successively extracted linear combination, or Principal Component
(PC), has a smaller variance (Singh and Harrison, 1985).
|| Red-green-blue color composite ratio image of 5/7,
|| Red-green-blue color composite ratio image of 5/7,
|| General statistics for 6 bands
|| Correlation matrix for 6 bands
|| Principal components for 6 bands
Three PCA techniques have been used for satellite images processing:
(1) standard PCA on six bands of Landsat, (2) Crosta technique on four
or six bands and 3) selective PCA on two or three bands.
In this study, the general statistics and principal component eigenvectors
and eigenvalues for six, four and three bands have been calculated in
different ways. More than 20 different alteration maps of this area have
been produced by these PCA techniques and their color compositions. The
best processed images have been selected and are described below.
The statistics and principal component transformation (eigenvectors and
eigenvalues) are described in Table 2A-C, using six
ETM+ bands as input bands (bands 1, 2, 3, 4, 5 and 7). It is
observed the PC1 does not contain spectral features relevant in this analysis
as it is a combination of all bands. This component contains 95.9% of
the variance of the 6 bands (Table 2C). The PC1 gives
information mainly on albedo and topography. Vegetation should be enhanced
in PC5 as this PC has higher with negative sign (-0.60) loading of band
4. The PC6 has higher loadings of band 5 (-0.85). This PC should detect
the hydroxyl minerals in dark pixels because of negative contributions
of band 5 and positive contributions of band 7 (0.37). The PC5 has a higher
positive loading of band 3 (0.71). This PC should represent iron oxides
in bright pixels because of positive contributions of band 3 and band
1 (Table 2C). Although the principal component eigenvectors
and eigenvalues indicate important of PC5 and PC6 for alteration detection,
these PC images have not clearly shown the location of four prospect areas.
The PC4 image clearly detects the location of alteration zones in dark
pixels. In order to show the areas with hydroxyl minerals in bright pixels
an inverse of this PC is obtained by using Eq. 1.
PC4 = –0.59 (band 1)+0.57
(band 2)–0.11 (band 3)–0.32 (band 4)+0.06 (band5)+0.43
Color composition PC images are also useful technique for hydrothermal
alteration mapping (Conradsen and Harpoth, 1984; Ranjbar et al.,
2004; Roustaei et al., 2006). This technique is produced by combining
three PC images in red, green and blue. Color composition of PC3, PC2
and PC4 (using 7 bands as input bands) in red-green-blue is shown in Fig.
7. Sericitic and argillic alteration have been characterized by green
color. Propylitic zone is in yellow- orange to pink. As with the previous
techniques, a fifth altered area is detected by green color. Vegetation
can be detected by dark green color (Fig. 7).
Discrimination of different rock units is shown: in green-brown color
is Kuh-e-Shah dacite, in dark red to violate are volcanic rocks, in dark
blue is micrograndiorite and in bright blue is the tuff unit. Plutonic
rocks near the villages in Maherabad area are the same color as volcanic
rocks (Fig. 7).
Crosta technique is also used for features oriented principal components
selection. Through the analysis of the eigenvector values it allows identification
of the principal components that contain spectra information about specific
minerals, as well as the contribution of each of the original bands to
the components in relation with spectral response of the materials of
interest. This technique can be applied on four and six selected bands
on TM data (Crosta and Moore, 1989; Rutz-Armenta and Prol- Ledesma, 1998).
Crosta technique is commonly used on Bands 1, 3, 4 and 5 for enhancing
iron oxides and bands 1, 4, 5 and 7 for detection hydroxyl minerals. Although
the Crosta method is very useful for the alteration mapping; nevertheless,
there are areas which are altered but are not enhanced by this technique
(Ranjbar and Honarmand, 2004). Crosta technique has been used for alteration
mapping in study area but this technique proved not to be useful.
|| Red-green-blue color composite image of PC3, PC2, PC4
(using 7 bands as input bands)
|| General statistics for 3 bands
|| Correlation matrix for 3 bands
|| Principal components for 3 bands
The selected principal component analysis on three bands has also been applied
in study area. The statistics and PC eigenvectors and eigenvalues have been
calculated in Table 3A-C and 4A-C, using
bands 1, 4 and 5 and bands 1, 5 and 7 as input bands, respectively.
Table 3C shows that vegetation should be enhanced
in PC3 because of higher loadings of band 4 (-0.68).
|| General Statistics for 3 bands
|| Correlation matrix for 3 bands
|| Principal components for 3 bands
PC2 has higher loadings
of band 5 (0.51). This PC should detect hydroxyl minerals with bright
pixel due to positive contributions of band 5.
Table 4C shows that hydroxyl minerals should be enhanced
in PC3 because of higher loadings of band 5 (-0.85). Hydroxyl minerals
can be detected in dark pixels due to the negative contribution of band
5 and positive contribution of band 7 (0.15).
|| RGB color composite image of PC1 (157), PC2 (157),
In order to show hydroxyl minerals in bright pixels an inverse of this PC is obtained by using Eq. 2. PC2 can recognize hydroxyl minerals in bright pixel too (Table 4C).
PC3 = –0.49 (band 1)+0.85
(band 5)–0.15 (band 7)
Color composition PC images have been combined by PC1 (157), PC2 (157)
and PC3 (145) in red, green and blue, respectively (Fig.
8). The areas in green, yellow and white colors are sericitic and
argyllic alterations. Propylitic zones can be detected by darker green
and brown color. In addition to the four known prospect areas, a fifth
altered region was also recognized by this technique. Vegetation is enhanced
in blue color. Discrimination of Kuh-e-Shah dacite and volcanic rocks
is not very good and both are in dark blue- violate color. Microgranodiorite
unit (southeast of area) is in pink. Tuff unit is in white too (Fig.
Airborne geophysics data analysis: Airborne geophysics data (radiometry
and magnetometry) is another useful tool for porphyry copper and epithermal
gold systems exploration.
Behn et al. (2001) argued that high- resolution aeromagnetic data
from northern Chile shows that of porphyry copper deposits coincide with
magnetite anomalies, which most likely reflect loci of mafic intrusions
in mid to deep crustal level.
Ranjbar et al. (2001) and Ranjbar and Honarmand (2004) have worked
on a airborne geophysics data and concluded that the porphyry copper deposits
in the Kerman region are associated with a distinct magnetic lows relative
to the host rocks. Their potassium is high and resistivity is low.
Airborne magnetometry studies in Infiernillo porphyry deposit, Argentina,
have shown a positive anomaly approximately coincident with the potassic
zone, surrounded by a relatively low magnetic intensity halo suggesting
magnetic destruction, features typical of the phyllic zone (Tommaso and
Dickson et al. (1996) have shown, in Kerman province that elevated
potassium in the sericite zone is often observed around the mineralization
areas. Also acid sulfate conditions resulting from weathering of near
surface sulfides can result in Th mobilization from host rocks and Th
can precipitate with iron in gossan.
|| RTP map of study area (GSI, 2005)
Similar results have been obtained
over the Darrehzar prospect area, near the Sarcheshmeh porphyry deposit.
The higher K and Th counts over the altered zone are due to the presence
of abundant sericite, clay and K-feldspar minerals (Ranjbar et al.,
Figure 9 shows Reduced to Pole Magnetic (RTP) map of
the study area that has been produced by the Geological Survey of Iran
(2005). Field intensity and shape of anomaly were changed by magnetic
dipoles and their location relative to the Earth magnetic field and strike
of flight lines. Therefore using the RTP filter these effects are omitted
and the magnetic anomaly is returned to its true situation. The maximum
and minimum fields in the RTP map are 47890.924 and 46686.153 nt, respectively
The magnetic anomaly is related to the erosion level of porphyry and
epithermal deposits, the type of alteration and mineral assemblage observed
in surface and the intensity of alteration and amount of magnetite destruction.
Increase of erosion-level is indicated by outcrops of magnetite-type granitoid
rocks hosting mineralization and the presence of potassic alteration associated
with magnetite (particularly in Cu-Au porphyry deposit). Types of alteration
and minerals assemblage influence magnetic intensity, as potassic and
propylitic zones occasionally have high magnetite content and sericitic
and argillic zones don`t have magnetite due to its destruction.
In the study area, the high magnetic anomaly is related to magnetite-series
intrusive rocks that commonly host alteration and mineralization at both
the surface and at depth (Fig. 9). Magnetic susceptibility
measurements of volcanic-plutonic rocks (80x10-5 to >5000x10-5
SI) confirmed this idea. In this manner magnetite veins are occasionally
present in propylitic and potassic zones. The area with a relatively low
magnetic intensity suggested magnetic destruction in other types of alteration
zone (Fig. 9).
Figure 10 shows a ternary radiometry map of the area.
Three radioelement concentrations are shown: potassium as red, uranium
as blue and thorium as green. On the map, blue areas are relatively high
in uranium, red areas are relatively high in potassium and green areas
are relatively high in thorium. The intensity of each color is proportional
to the concentration. White areas have very low radioelement concentration
normally due to overburden covering the bedrock (Fig. 10).
|| Ternary map of study area (GSI, 2005)
The high potassium and uranium counts over the prospect areas reflect
the presence of sericite, K- feldspar and clay minerals. The high thorium
count can be implied to be in gossan zone in which Th has been precipitated
along with iron (Fig. 10).
The Lut block has a great potential for different types of mineralization,
particularly porphyry copper and epithermal gold deposits, as result of
its suitable subduction zone tectonic setting resulting in the presence
of calcalkaline subvolcanic rocks. Maherabad, Sheikhabad, Khopik and Hanich
prospect areas are the best documents for this claim. Eastern Iran can
potentially become the second important porphyry copper belt in Iran after
ETM+ images processing is a valuable technique for delineating
favorable areas for further exploration. This technique works very well
in eastern Iran due to low precipitation causing very minor soil development
and the small amount vegetation and therefore good rock exposure. Getting
access to the most of the region due to lack of roads cause exploration
to be expensive and time consuming. ETM+ data analysis for
detection and reconnaissance mapping of iron oxides and hydroxyl minerals
zones in areas with low vegetation cover can to be an excellent low-cost
alternative method of exploration. Integration of both satellite images
processing and airborne geophysics data can obtain better results.
In this study, different image processing methods consists of false color
composite images, color composite ratio images and different techniques
of principal component analysis and their color compositions have been
used. All of these techniques clearly show the four known prospect areas
in the study area, but color composition selective images may be the most
reliable method for enhancing the areas with hydrothermal alteration.
In addition to the four known porphyry-epithermal prospect areas, a fifth
previously unknown small altered area has also been detected in southeastern
Airborne magnetometry data shows high concentrations of magnetic over
the most of the study area reflected of magnetic-series granitoid rocks
related to mineralization or propylitic/potassic zone with magnetite veins.
Low magnetic areas reflect magnetic destruction in other types of alteration
zone. The high K and U counts have resulted from the presence of sericite,
clay minerals and K-feldspar. The high thorium count occurs in gossan
zones in which Th has been precipitated with iron.