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Mapping mineralogical alteration using principal-component analysis and
matched filter processing in the Takab area, north-west Iran, from ASTER
data
Article in International Journal of Remote Sensing · May 2008
DOI: 10.1080/01431160701418989
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Mapping mineralogical alteration using
principal‐component analysis and
matched filter processing in the Takab
area, north‐west Iran, from ASTER data
a
a
b
F. Moore , F. Rastmanesh , H. Asadi & S. Modabberi
c
a
Department of the Earth Sciences , College of Sciences , Shiraz
University , Shiraz 71454, Iran
b
Mining Department , Esfahan University of Technology , Esfahan,
83111, Iran
c
Department of Environment of Islamic Republic of Iran , Pardisan
park , Tehran, 15875 , Iran
Published online: 29 Apr 2008.
To cite this article: F. Moore , F. Rastmanesh , H. Asadi & S. Modabberi (2008) Mapping
mineralogical alteration using principal‐component analysis and matched filter processing in the
Takab area, north‐west Iran, from ASTER data, International Journal of Remote Sensing, 29:10,
2851-2867, DOI: 10.1080/01431160701418989
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International Journal of Remote Sensing
Vol. 29, No. 10, 20 May 2008, 2851–2867
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Mapping mineralogical alteration using principal-component analysis
and matched filter processing in the Takab area, north-west Iran, from
ASTER data
F. MOORE*{, F. RASTMANESH{, H. ASADI{ and S. MODABBERI§
{Department of the Earth Sciences, College of Sciences, Shiraz University,
Shiraz 71454, Iran
{Mining Department, Esfahan University of Technology, Esfahan, 83111, Iran
§Department of Environment of Islamic Republic of Iran, Pardisan park, Tehran, 15875,
Iran
(Received 27 November 2006; in final form 12 April 2007 )
The Takab area, located in north-west Iran, is an important gold mineralized
region with a long history of gold mining. The gold is associated with toxic
metals/metalloids. In this study, Advanced Space Borne Thermal Emission and
Reflection Radiometer data are evaluated for mapping gold and base-metal
mineralization through alteration mapping. Two different methods are used for
argillic and silicic alteration mapping: selective principal-component analysis and
matched filter processing (MF). Running a selective principal-component
analysis using the main spectral characteristics of key alteration minerals
enhanced the altered areas in PC2. MF using spectral library and laboratory
spectra of the study area samples gave similar results. However, MF, using the
image reference spectra from principal component (PC) images, produced the
best results and indicated the advantage of using image spectra rather than
library spectra in spectral mapping techniques. It seems that argillic alteration is
more effective than silicic alteration for exploration purposes. It is suggested that
alteration mapping can also be used to delineate areas contaminated by
potentially toxic metals.
1.
Introduction
The Advanced Space Borne Thermal Emission and Reflection Radiometer
(ASTER), which is aboard the Earth observing system (EOS) TERRA platform,
records solar radiation in 14 spectral bands (Rowan and Mars 2003, Rowan et al.
2005). It measures reflected radiation in three bands between 0.52 and 0.86 mm
(VNIR); in six bands from 1.6 to 2.43 mm (SWIR), and emitted radiation in five
bands in the 8.125–11.65 mm wavelength region (TIR). The resolution of VNIR,
SWIR, and TIR is 15 m, 30 m, and 90 m respectively (Fujisada 1995).
With the spectral resolution provided by ASTER, identification of specific
alteration assemblages becomes feasible (Abrams 2000). The VNIR, SWIR, and
TIR wavelength regions provide complementary data for lithologic mapping and
exploration through alteration mapping. Already, ASTER data have been
*Corresponding author. Email: moore@geology.susc.ac.ir
International Journal of Remote Sensing
ISSN 0143-1161 print/ISSN 1366-5901 online # 2008 Taylor & Francis
http://www.tandf.co.uk/journals
DOI: 10.1080/01431160701418989
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2852
F. Moore et al.
extensively used for these purposes (e.g. Crosta et al. 2003, Rowan and Mars 2003,
Rowan et al. 2003, 2005, 2006, Ninomiya et al. 2005).
The geothermal basin of Takab area, in the north-western part of Iran, is
characterized by having a wide variety of mineral deposits. The most important
mineral commodity is gold. Zarshuran in this area is one of the largest gold deposits
in Iran. Most deposits in the Takab area and their alteration halos contain
potentially toxic metals/metalloids such as arsenic, antimony, and selenium, and
pose serious environmental problems (Modabberi 2004, Modabberi and Moore
2004). Hence, alteration mapping, in addition to its use as an exploration tool, can
also serve to delineate areas prone to contamination of toxic metals.
The main purpose of this study is application of ASTER data in determining the
distribution pattern of these metals/metalloids sources, through alteration mapping.
A 7706912 pixel subscene of ASTER 168/99/7 covers the study area. The data were
acquired on July 2000.
2.
Study area
Takab area is a sparsely vegetated semi arid, mountainous region, located north of the
Takab town, NW Iran (figure 1). It is an important gold-producing region and hosts
several famous gold deposits, including Zarshuran and Aghdarreh. Gold mineralization is widespread, and occurrences of gold-bearing, arsenic, antimony, and basemetal deposits in Takab area are also common (Asadi 2000, Asadi et al. 2000).
The Takab depositional sequence is characterized by stratigraphic hiatus and
unconformities. According to Samimi (1992), the mining area is in a region of
Precambrian metamorphic basement with late Precambrian carbonates and shales
overlain by Cambro-Ordovician formations. Tertiary rocks transgress over these
older rocks.
Figure 1 presents the geological map of Takab area. The oldest rock units are a
series of greenish-grey metamorphic mica schist and quartzite of lower Precambrian
age. These rocks underlie metamorphosed ultramafic rocks, including complexes of
serpentinite and serpentine schist, metagabbro, and metamorphosed basaltic rocks
of middle Precambrian. A thick bedded greyish crystalline dolomitic limestone and
dolomite comprise the upper Precambrian sequence. Cambrian deposits consist of
dolomite, shale, and sandstone.
Olio-Miocene stratigraphic units are composed of thick-bedded to massive
limestone, gypsiferous marl, and sandstone, with associated basaltic and andesitic
volcanic rocks. The youngest rock units are loose clay-cemented polygenetic
conglomerate and travertine. A number of felsic intrusive rocks, mainly granite and
quartz porphyry, microgranite, and aplite, are exposed north and west of the study
area.
Zarshuran, the most important gold deposit of Takab area, is located 42 km north
of the Takab town (figure 1). It has an ancient history of arsenic and gold mining
(Samimi 1992). The Zarshuran area is characterized mainly by rocks of Precambrian
age. Epithermal gold mineralization occurs in the Zarshuran black shale and
limestone of Precambrian age. More than 30 sulfide minerals and sullphosalts have
now been identified at Zarshuran (Karimi 1993, Mehrabi et al. 1999, Asadi et al.
2000). Pyrite, the most abundant sulfide, is associated with both ore and gangue
minerals. The main stage of gold and arsenic mineralization is accompanied by
massive silicic and argillic alteration (Asadi 2000). The intensity of silicification
varies from weak to total replacement of the host by jasperoid. Massive
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Mapping mineralogical alteration using principal-component analysis
Figure 1.
Geological map of the Takab area.
cryptocrystalline quartz and hydrothermal quartz with idiomorphic hexagonal
crystals are the main components of siliceous alteration.
Argillic alteration is intimately associated with the gold mineralization. The
moderately to intensely argillized rocks consist of varying proportions of finegrained clays (sericite, illite, and kaolinite), quartz, gypsum, sulfides (pyrite,
orpiment, and realgar), and As–Sb sulfosalts.
Aghdarreh, the second largest gold deposit in the Takab area occurs in an OligoMiocene limestone. Like Zarshuran, the most important alteration types are
silicification and argillization, and silicification ranges from weak to complete
2854
F. Moore et al.
replacement of the wall-rock by jasperoid. Important alteration minerals include
quartz, illite, and kaolinite.
Generally speaking, silicification and argillic alteration are widespread throughout the Takab region.
3.
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3.1
Methods
Preprocessing of ASTER data
A cloud-free L1A-ASTER scene of the Takab area, acquired on 14 July 2000 was
orthorectified and reprojected to UTM 39N, WGS-84 by Geosense in the
Netherlands, using a SRTM Digital Elevation Model and orthorectified Landsat
ETM + imagery of the area as reference materials.
ASTER L1A data are converted to radiance at sensor data using standard ENVI
software. In order to perform spectral analysis and compare multispectral image
spectra with reference reflectance spectra, the radiance data had to be converted to
reflectance data (Lau 2004). The radiance data are affected by atmospheric effects,
such as water vapour and distribution of aerosols, and therefore require
atmospheric correction to minimize these influences and hence generate meaningful
pixel spectra that can be correlated with field spectra. In this study, the SWIR bands
of the study area were atmospherically corrected using a modified (proprietary by
GEOSENSE) Internal Average Relative Reflectance (IARR) (Kruse et al. 1985). In
this technique, the average scene spectrum is calculated and is used as the reference
spectrum, which is then divided into the spectrum at each pixel of the image. The
ASTER Thermal emmitance data, analysed in the study area, were produced from
the level 1B data using IARR algorithm (Moghtaderi et al. 2007). The level 1B data
had been produced previously from level 1A data using a bilinear resampling
procedure.
3.2
Image processing
Different image-processing techniques can be applied on ASTER data. These
techniques range from multispectral methods such as PCA and band ratioing (e.g.
Crosta et al. 2003, Rowan et al. 2005) to mineral-mapping methods such as matched
filtering (e.g. Rowan et al. 2006).
In this study, two different methods, namely principal-component analysis (PCA)
and matched filter (MF) processing, are compared and combined for alteration
mapping. In both methods, the spectral characteristics of alteration key minerals of
the study area were used.
In order to determine the main spectral features of the alteration minerals in the
study area, some samples were collected from alteration zones in the vicinity of
Zarshuran and Aghdarreh operations. Reflectance spectra of the samples were
measured in the laboratory using the TerraSpecH spectroradiometer at the Geosense
Company, Netherlands (table 1).
3.2.1 Principal-component analysis. TM data have already been extensively used
for alteration mapping (e.g. Kaufmann 1988, Loughlin 1991, Ruiz-Armenta and
Prol-Ledesma 1998, Tangestani and Moore 2001, 2002, Carranza and Hale 2002).
However, the TM visible and near-infrared (VNIR) and short-wave infrared
(SWIR) bands can only discriminate areas rich in iron oxides/hydroxides and
clay minerals, respectively. With the spectral resolution provided by ASTER,
Mapping mineralogical alteration using principal-component analysis
2855
Table 1. Characteristics of used spectroradiometer (TerraSpecH).
Spectral range
Spectral resolution
Scanning time
Detectors
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Input
350–2500 nm
3 nm @ 700 nm
6 nm @ 1400 nm
7 nm @ 2150 nm
100 ms
One 512 element
Si photodiode array 350–1000 nm
Two separate, TE cooled, graded index InGaAs photodiodes
1000–2500 nm
Detachable SMA 905 style 1.5-m fibre-optic cable
identification of specific alteration assemblages becomes feasible, since it has six
spectral bands in the SWIR (bands 4–9), a region where many clay minerals show
diagnostic spectral features, compared with only two TM bands (TM 5 and TM 7)
(Abrams 2000).
PCA is a widely used technique for alteration mapping in metallogenic provinces.
PCA can be applied to multivariate datasets, such as multispectral remote sensing
images with the purpose of extracting specific spectral responses as in the case of
hydrothermal alteration minerals (Crosta et al. 2003). If the number of input
channels is reduced to avoid a particular spectral contrast, the chances of defining a
unique principal component (PC) for a specific mineral class will be increased
(Loughlin 1991). Chavez and Kwarteng (1989) introduced a specific kind of PCA in
which only two bands are used as input to PCA. They labelled this kind of PCA
selective PCA. Selective PCA can be used to enhance and map the spectral
differences or contrast between different spectral regions. When only two bands are
used as input to PCA, the spectral contrast is mapped into the second component.
The result of selective PCA processing is easier for visual interpretation.
In this study, those bands that contain the most representative common spectral
features of the alteration minerals in Takab area were chosen as input bands to
PCA. As the main alteration zones in the study area are argillic and silicic, the
SWIR and TIR regions of the ASTER data were respectively used for argillic and
silicic mapping.
In argillic alteration mapping, the subset (selective) bands were selected according
to the position of characteristic spectral features of key argillic minerals in the SWIR
portion of the spectrum. The main argillic alteration minerals in Takab area are
kaolinite, sericite, and Illite. Figure 2 shows reflectance spectra of these minerals
resampled to ASTER bandpasses 1–9 and produced from available USGS spectral
library.
All minerals show a distinct absorption feature around 2.2 mm (band 6). They also
display distinct reflectance around bands 4 and 7, with the reflectance in band 4
being stronger. Figure 3 shows the laboratory spectra of samples of argillic zone in
the study area. The spectra illustrate similar spectral signatures to that of USGS
spectral library. Bands 4 and 6 were chosen as input to selective PCA. Table 2 shows
the eigenvector statistics for these bands. According to eigenvector loadings and
their signs, in PC2 clay minerals of argillic alteration (kaolinite, illite, and sericite)
are enhanced with bright pixels. Figure 4 shows the distribution of argillic alteration
in the Takab area.
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2856
F. Moore et al.
Figure 2. Laboratory reflectance spectra of important clay minerals (kaolinite, muscovite
(sericite), illite) in the Takab area. The spectra were resampled to the ASTER bandpasses 1–9.
All minerals show a distinct absorption feature around 2.2 mm (band 6 of ASTER). USGS
spectral library.
In silicic alteration mapping, silicate minerals exhibit fundamental molecular
vibrational absorption features in the 8–14-mm atmospheric window, which is the
basis of lithologic mapping using multispectral thermal-infrared images (Salisbury et
al. 1988). The main silicic alteration key mineral of the study area is quartz. Spectra
of quartz display minima in ASTER bands 11 and 12 (Rowan and Mars 2003).
According to Rowan (1998), quartz-rich rocks have distinctly asymmetrical
Figure 3. Laboratory spectra of the argillic zone minerals in the study area. The spectra
were resampled to the ASTER bandpasses 1–9. All minerals show a distinct absorption
feature around 2200 nm (band 6 of ASTER).
Mapping mineralogical alteration using principal-component analysis
2857
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Table 2. Eigenvector statistics for ASTER bands 4 and 6 of the Takab
area.
Input bands
PC1
PC2
Band 4
Band 6
0.78
0.62
0.62
20.78
channels 10–14 image spectra with low slopes in the channels 10–12 region and steep
slopes in the channels 12–14. The reason for this asymmetry is the dominance of
quartz (figure 5). So, it is expected that quartz-rich rocks will be enhanced in dark
red in the colour composite 14–12–10 (RGB). Figure 6 confirms this expectation.
Figure 7 shows the emittance spectra of the dark red region in figure 6.
The reason for producing emittance spectra is the lack of emittance data of silicic
alteration minerals of Takab area in TIR region. Also, the TIR spectral libraries
available for rocks and soils are much more limited than VNIR-SWIR mineral
spectral libraries, and nearly all the emissivity spectra represent fresh, unweathered
samples (Rowan et al. 2005).
As expected, silicic alteration minerals (mainly quartz), exhibit a distinct
minimum at band 12 and a maximum at band 14. These bands were used as inputs
of selective PCA. The eigenvector statistics for these bands are presented in table 3.
According to eigenvector loadings and their signs, silicified rocks are enhanced in
PC2 with dark pixels (figure 8).
3.2.2 Al-OH clays ratio image. The reflectance of key argillic alteration minerals,
kaolinite, illite, and sericite (Al-OH clays) in band 4 and their distinct absorption
Figure 4. PC2 image of selective PCA on bands 4 and 6 of ASTER. Clay minerals of argillic
alteration are enhanced as bright pixels.
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2858
F. Moore et al.
Figure 5. Spectra representing quartz-rich rocks. All rocks show a distinct absorption
feature around band 12 of ASTER (modified from Rowan 1998).
feature in band 6 are used as the criteria for argillic alteration mapping. Although
this is good for the Al-OH clays, it is still large and positive for many other minerals
such as carbonates. In order to evaluate the accuracy of the resultant argillic
alteration map, a relative band-depth (RBD) image (Crowley et al. 1989, Rowan
and Mars 2003, Rowan et al. 2005) was produced to display the extent of Al-OH
clays in the study area. This ratio was calculated as follows (Band 4 + Band 7)/(Band
6) (Rowan et al. 2005). In the resultant image, argillically altered rocks are enhanced
with bright pixels (figure 9). The RBD image and PC2 of PCA analysis are in good
agreement.
3.2.3 Matched filter processing. The matched filtering technique (Harsanyi and
Chang 1994) maximizes the response of the known endmember and suppresses the
response of the composite unknown background, thus matching the known
signature. It provides a rapid means of detecting specific materials based on a
match to library or image endmember spectra and does not require knowledge of all
endmembers within an image scene.
In this study, the reference spectra were selected from the USGS spectral library
and, in the case of the TIR region, from JHU and also the hand spectroradiometer
results of the samples measured in laboratory. Also, the spectra representing the
enhanced altered areas in those PCs that were selected as representing the
distribution of altered rocks were used as reference spectra in mineral mapping.
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Mapping mineralogical alteration using principal-component analysis
2859
Figure 6. Colour composite made with bands 14–12–10 from ASTER data. Silicified rocks
are enhanced as dark red.
In this regard, the reference spectra were selected from true anomalous areas. For
those altered rocks that are enhanced as dark pixels in PC images, the image must be
negated, and the reference spectra must be selected from high DN values of known
altered areas.
In argillic alteration mapping, matched filter processing, using the USGS spectral
library of kaolinite, illite, and sericite (key minerals of the argillic alteration) in the
Takab area, enhanced the alteration halos mostly around the Zarshuran mine
(figure 10). Running the MF technique, using reference spectra derived from PC
image, produces results similar to those of the Al-OH clays ratio image, with the
altered areas being more clear and widespread in the former (figure 11).
In silicic alteration mapping, as mentioned, massive cryptocrystalline quartz and
hydrothermal quartz with idiomorphic hexagonal crystals are the main components
Figure 7.
Spectra of siliceous rocks occurring in the Takab area.
2860
F. Moore et al.
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Table 3. Eigenvector statistics for ASTER bands 12 and 14 of the Takab
area.
Input bands
PC1
PC2
Band 12
Band 14
0.80
0.60
0.60
20.80
of siliceous alteration. The spectral library spectrum of this mineral was used as a
reference in MF technique. For this purpose, TIR bands were used. Also, the
reference spectra derived from PC image were used in image processing. The use of
spectral library spectra gave unusual results, and the silicified rocks were not
enhanced. The use of image spectra for MF produced better results (figures 12 and
13).
4.
Results and conclusions
Selective PCA, using ASTER data and laboratory measured spectral characteristics
of the samples in Takab area, provided a simple way for alteration mapping.
Comparison of the obtained results with available geological maps and ground data
checking showed that selective PCA is a reasonable and reliable way for preparing
alteration maps. Running PCA with SWIR bands also gives the same result at PC2
and differentiates between Zarshuran carbonate host and the adjacent ultramafic
rocks (figure 14). Running PCA with TIR bands as inputs gives similar results to
PC2 for selective PCA. The reason for this is probably the emittance of silicified
rocks in this part of electromagnetic spectrum.
Matched filter processing also provides a rapid method for argillic alteration
mapping based on main spectral reflectance and spectral emittance characteristics.
USGS spectral library, hand specctroradiometer results of the study area samples,
Figure 8. PC2 image of running selective PCA on bands 14 and 12 of ASTER. Silified rocks
are enhanced with bright pixels.
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Mapping mineralogical alteration using principal-component analysis
2861
Figure 9. ASTER relative-band depth (RBD) image for Al-OH clays, in which clays are
enhanced as bright pixels.
and image spectra were used as a reference for argillic alteration mapping.
Comparison of figures 10 and 11 shows that matched filter processing using image
spectra yields a considerably more clear alteration map. Running this technique
using the USGS spectral library and laboratory measured spectra of the study area
samples gives similar results but different from matched filter processing using
image spectra. This is because the laboratory measurements of samples typically
Figure 10. Matched filter processing result for argillic alteration mapping using kaolinite,
illite, and sericit as endmembers (USGS spectral library).
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2862
F. Moore et al.
Figure 11. Matched filter processing result for argillic alteration mapping using PCA image
spectra.
have a high alteration mineral content, whereas the image spectra represent 30-m
pixels within which the alteration mineral content may be less concentrated (Rowan
et al. 2006).
The same is true for silicic alteration where using image spectra yielded better
results. Matched filter processing using the JHU spectral library yielded unusual
results in that the least matching occurs around the deposits and quartz-rich rocks.
Figure 12. Matched filter processing result for silicic alteration mapping using quartz as an
endmember (JHU spectral library).
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Mapping mineralogical alteration using principal-component analysis
2863
Figure 13. Matched filter processing result for silicic alteration mapping using PCA image
spectra.
In examining these spectra, it was found that the quartz absorption feature in the
vicinity of band 12 of ASTER data is missing in this spectral library (figure 15).
The representative spectra of the silicified rocks of the Takab area clearly show
this absorption feature (figure 7). The result clearly indicates the advantage of using
image spectra instead of library spectra as a reference in matched filtering and
probably other spectral mapping techniques such as the spectral angle mapper.
Figure 14. PC2 image of running PCA using SWIR bands of ASTER data. Argillicalley
altered rocks are enhanced with bright pixels.
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2864
F. Moore et al.
Figure 15. JHU spectral library of quartz. The spectra were resampled to the ASTER
bandpasses 10–14.
Comparison of figures 8 and 13, and 4 and 11 shows that MF processing using PC
image spectra displays more widespread altered areas than SPCA or MF using
laboratory spectra. This is also confirmed by ground-data checking and considering
the proposed anomalous areas by the geological survey of Iran (figure 16).
Silicic and argillic alterations display different distribution patterns. The silica
anomaly is usually only of interest when it coincides with other spectral anomalies.
Figure 16. Colour composite made with argillic, argillic + silicic, and silicic alteration as
RGB, respectively. The alteration zones are quite bright.
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Mapping mineralogical alteration using principal-component analysis
2865
Silica anomalies related to alteration are often quite subtle compared with many
false anomalies. In the study area, high silica values are not confined to
hydrothermal alteration. Silica mapping also maps silica in siliceous rocks and
other surface materials such as quartz-rich sands (figure 1).
Argillic alteration is more widespread than silicic alteration. In order to find
hydrothermally altered regions that show both silicic and argillic alterations, a
colour composite image was created by combining the argillic alteration image,
silicic + argillic alteration images, and silicic alteration image as red, green, and blue,
respectively. The images used are the results of matched filter processing with image
spectra (figure 16).
In the resultant image, alteration zones are quite bright, and white pixels are
potentially the most prospective in that they are both argillized and silicified. The
image also shows that apart from known deposits, several new anomalies also exist in
the study area. With one exception, all these anomalies are located west and north-west
of Zarshuran. According to Karimi (1993), a few kilometres to the west of Zarshuran
there are several old workings showing ancient mining activity. The majority of the
deposits are hosted by carbonates (Asadi 2000). Exploration by the Geological Survey
of Iran (1997) in the Takab area also reveals several promising exploration targets in
this region. Approximate locations of these anomalies are shown in figure 16. The
created colour composite image, thus, successfully mapped these new anomalies as well
as the known deposits. It seems that in the study area, argillic alteration is apparently
more important than silicic alteration for exploration purposes.
Analysis of ASTER data in this study showed that although selective PCA is a
robust technique and that matched filter processing provides a rapid mean for
alteration mapping, neither of these two techniques can by itself produce a
satisfactory alteration mapping. However, combining the two methods produces a
better result. Furthermore, as potentially toxic metals are mostly hosted by
alteration minerals, the proposed method may also be used to delineate
contaminated areas. The coincidence of alteration haloes in this study with
contaminated areas in Takab area supports this conclusion. This new implication of
alteration mapping deserves further investigation.
Acknowledgements
The authors would like to thank the Ministry of Science Research and Technology
of Iran, for grant number 113545, which provided the financial resources for this
research. The authors would also like to thank Dr Marc Goossense, for his help in
the spectral analysis.
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