Journal of Earth Science, Vol. 25, No. 2, p. 397–406, April 2014
Printed in China
DOI: 10.1007/s12583-014-0423-9
ISSN 1674-487X
The Reconnaissance of Mineral Resources through ASTER
Data-Based Image Processing, Interpreting and Ground
Inspection in the Jiafushaersu Area, West Junggar, China
Lei Liu1, 2, Jun Zhou1, 2, Fang Yin1, Min Feng*3, Bing Zhang4
1. Key Laboratory of Western Mineral Resources and Geological Engineering of Ministry of Education, School of Earth Sciences and
Resources, Chang’an University, Xi’an 710054, China
2. Lanzhou AuriferouStone Mining Services Co. Ltd., Lanzhou 730030, China
3. Global Land Cover Facility, Department of Geographical Sciences, University of Maryland, College Park 20740, USA
4. Geological Brigade 7 of Xinjiang Bureau of Geology and Mineral Resources, Wusu 833000, China
ABSTRACT: Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data
covering the Jiafushaersu area in Xinjiang were used for mapping lithology and hydrothermal
alteration. The study area situates at a potential mineralization zone in relation to small hypabyssal
granodiorite or quartz monzonite intrusions along the margin of granitoid batholiths of Darbut foot
wall. The false colour composition of bands 521 and the first three principal component analyses (PCA1,
PCA2, PCA3) in RGB identify the lithological units and discriminate the small intrusions very well
from the adjacent granitoid batholiths. PCA and spectral angle mapper (SAM) algorithm were
employed to discriminate alteration minerals. The results indicate that the hydroxyl-bearing or ferric
and less commonly carbonate types show good correlation with the quartz monzonite porphyry and
aplite. Field verification led to finding of the Jiafushaersu molybdenum mineralization. The lithological
and geochemical features imply that the molybdenum mineralization is close to the porphyry type. This
study further verified that the foot wall of the Darbut suture could have served as a more important
metallogenic district for the porphyry copper and molybdenum deposits. It is concluded that the
ASTER data-based methods can be used as a powerful tool for small intrusion-type mineral resources
targeting.
KEY WORDS: ASTER, Darbut, false colour combination, principal component analysis, SAM.
1
INTRODUCTION
The Advanced Spaceborne Thermal Emission and
Reflection Radiometer (ASTER), launched on board NASA’s
TERRA spacecraft in December 1999, have provided a finer
spectral resolution. ASTER consists of three separate
subsystems with a total of 14 spectral bands across the
visible—near infrared (VNIR), short wave infrared (SWIR) and
thermal infrared (TIR) with three, six and five bands in each
part of the spectrum respectively (Tangestani et al., 2008;
Rowan et al., 2006, 2005; Rowan and Mars, 2003). With the
spectral resolution of ASTER, identification of specific
alteration assemblages becomes feasible (Abrams, 2000).
Therefore, ASTER multispectral data have been extensively
used in mineralogical and lithological studies (Amer et al.,
2012, 2010; Pour and Hashim, 2011; Tangestani et al., 2011;
Mars and Rowan, 2010, 2006; Di Tommaso and Rubinstein,
2007; Zhang et al., 2007; Rowan et al., 2005; Crosta et al.,
*Corresponding author: [email protected]
© China University of Geosciences and Springer-Verlag Berlin
Heidelberg 2014
Manuscript received July 29, 2013.
Manuscript accepted Feburary 12, 2014.
2003; Rowan and Mars, 2003), largely enhancing the alteration
mineral mapping effect or compensating for the limited spectral
resolution of Landsat TM and ETM+ data in the shortwave
infrared region.
West Junggar is bounded on the southeast by the Darbut
suture from the Junggar block or basin (Fig. 1). This
northwestern most orogenic belt of China is of a big potential
in mineral resources, identified by many ore deposits (mostly
gold) like Hatu (Yu, 1998) and Saertuohai (Gan et al., 1996) in
the hanging wall (northwestern side) of Darbut. However,
Baogutu (Cheng and Zhang, 2006) and Tuketuke (Zhang et al.,
2009) copper deposits (gold and molybdenum act as
by-products in Baogutu and the pertinent mineralization also
exists in Tuketuke), porphyry type, were owed to the recent
success of mineral exploration in the foot wall (southeastern
side), which has strongly challenged the well-known
subduction-related or orogenic mineralization model (Groves et
al., 1998; Chen, 1996) that limited the prospecting zone for
hydrothermal gold and porphyry copper-gold deposits to the
hanging wall of a subduction zone. Importantly, the onset of the
mineral exploration in Tuketuke was related to the alteration
mineral mapping of ETM+ data and pertinent ground
inspection (Zhang et al., 2009), which led to the discovery of
tens of mineralization points. The Jiafushaersu molybdenum
Liu, L., Zhou, J., Yin, F., et al., 2014. The Reconnaissance of Mineral Resources through ASTER Data-Based Image Processing,
Interpreting and Ground Inspection in the Jiafushaersu Area, West Junggar, China. Journal of Earth Science, 25(2): 397–406,
doi:10.1007/s12583-014-0423-9
398
Lei Liu, Jun Zhou, Fang Yin, Min Feng and Bing Zhang
mineralized points are 35 km (straight) east of Tuketuke (Fig.
1), lying at the margin of similar granitoid batholiths, and its
finding was also attributed to the reconnaissance of Tuketuke
surroundings by ASTER data-based remote sensing studies and
the following ground inspection (Zhang et al., 2009).
Conspicuously, the achievements of this study may
contribute to the better understanding of orogeny-related
mineralization, outline a potential mineralization zone (ca. 40
km span from Tuketuke to Jiafushaersu) in relation to small
hypabyssal granodiorite or quartz monzonite intrusions along
the margin of granitoid batholiths, reveal the alteration and
mineralization characteristics of the relevant intrusions and
show the synthetic studies or ore prospecting under the
guidance of ASTER data-based image processing and
interpreting in Jiafushaersu, a sparsely vegetated arid region.
2 GEOLOGIC AND TECTONIC SETTINGS
2.1 Tectonic Framework
The Darbut suture separates the Kazakhstan plate from the
Junggar Basin (Coleman, 1989), which was interpreted as a
trapped oceanic basin of Late Paleozoic age (Carroll et al.,
1990). The suture, SW-NE-orientated and dipping toward NW
(Gan et al., 1996), is marked by an ophiolite zone (mostly
dismembered serpentinized harzburgite and dunite tectonites)
continually extending about 100 km (Feng et al., 1989),
suggesting a B-type subduction (the oceanic crust
northwestwards underplating the continent) along the
Kazakhstan margin. The major evolution age was confined to
the Early–Middle Devonian by the radiolaria from the relevant
cherts (Xiao et al., 1992) and the gabbros radiometric dating
(395±12 Ma, Sm-Nd isochrone; Zhang and Huang, 1992).
Both of the hanging wall and foot wall of Darbut are
dominated by the shallow-marine tuffaceous siltstone, tuff and
intermediate-basic lava (toward the upper) of Carboniferous
age, manifesting a gradual closure of the basin at that time. But
the orogeny is mainly identified by the large-scale imbricate
thrusting of Upper Carboniferous rocks (the Tailegula
Formation) in the hanging wall (Feng et al., 1989) and the
extensive granite intrusion of Late Carboniferous age (Fig. 1).
The continental molasses of Early Permian age clearly marks
the final closure of the suture (Carroll et al., 1990).
2.2
Regional Mineralization in the Suture Hanging Wall
The known mineral deposits in the region are basically
clustered in the hanging wall of the suture (Fig. 1). Accordingly,
Chen (1996) proposed a metallogenic model with zonation, i.e.,
the zone in the proximity of the suture was defined as a
favorable mineralization site for the hydrothermal type ore
deposits, next to it for the granite-related tungsten-tin deposits
along the batholith-dominated area, and further away from the
suture for the porphyry type ore deposits.
This model is analogous to the veining proposal of Groves
et al. (1998) for certain gold deposits, in which the so-called
orogenic type was presumed to have formed in the vicinity of
the subduction zone (accreted terranes adjacent to continental
magmatic arcs), whereas epithermal veins and gold-rich
porphyry and skarn deposits in the distal island or continental
arcs toward the continent.
Figure 1. (a) Generalized geological map of the western
Junggar, NW China, showing the distribution of the
intrusions, ophiolite belts and main faults; (b) geological
map of the study area (modified after Cheng and Zhang,
2006; Xiao et al., 1992; GBXBGMR, 1966). Mineralization
types: Hatu, magmatic hydrothermal Au quartz vein; Qiqiu,
Au quartz vein or altered rock related to volcanic edifice;
Saertuohai, ultrabasic rock-related Au; Baogutu, Tuketuke
and Baobei, porphyry Cu-Au; Kuogeshaye, Au quartz vein
related to intermediate-basic dikes.
2.3
Recent Achievements in the Suture Foot Wall
In essence, some granitoid batholiths and stocks also
emplaced in the Carboniferous shallow-marine sediments of
Darbut foot wall (Fig. 1). The discovery of the Baogutu
copper-gold deposit has casted doubts on the above modeling.
It was developed along the contact zone, with 300–400 m thick
drill-penetrated ores (Cu 0.1%–0.5%; Au 0.1–0.2 g/t as
by-product), between tuffaceous siltstones and a small
granodiorite porphyry body (0.84 km2) (Cheng and Zhang,
2006).
This success is followed by the Tuketuke copper deposit
(Zhang et al., 2009), which, though under drilling and tunneling,
The Reconnaissance of Mineral Resources through ASTER Data-Based Image Processing
similarly correlate with the small granodiorite porphyry
intrusions (mostly several thousand square meters) at granitoid
batholith margins. It was the small intrusions with distinct
lithology and their apparent wall-rock alteration in Tuketuke
that made us reconnoiter the surrounding area through ASTER
data-based imagery features and relevant ground inspection,
resulting in the finding of the Jafushaersu molybdenum
mineralization, although the alteration in Tuketuke does not
match the ideal zoning of a porphyry copper deposit (e.g., Hall
et al., 1974) and is typified by extensive propylitization,
relatively stronger chloritization toward the ores, intensely
chloritized and silicified ores, overall ferric stains and slight
sericitization, and notable potash-feldspar enrichment in the
depth.
1 2
3
399
ASTER Bands
4
56 7 8 9
Reflectance (offset for clarity)
Kaolinite
Muscovite
Calcite
Chlorite
Limonite
0.5
3 METHODOLOGY
3.1 Preprocessing of ASTER Data
A cloud-free L1B-ASTER scene of the Jiafushaersu area,
acquired on 31 May 2001 was reprojected to UTM 45N,
Krasovsky. The 15 m VNIR data were re-sampled to 30m to fit
with SWIR data which could preserve the spectral
characteristics of the SWIR data (Galvão et al., 2005). ASTER
SWIR crosstalk effects were corrected using the crosstalk
software provided by ERSDAC (ERSDAC, 2003). The internal
average relative reflectance (IARR) method (Ben-Dor and
Kruse, 1994) was applied in this study to convert radiance data
to reflectance images.
1 2
(a)
2.5
2.0
1.5
Wavelength (µm)
ASTER Bands 4
56 7 8 9
1.0
3
Reflectance (offset for clarity)
Kaolinite
Muscovite
Calcite
Chlorite
Limonite
3.2
Reflectance Spectra Analysis
According to the geologic setting and mineralization
characteristics, the alteration in the study area might be
composed of hydroxyl-bearing (kaolinization, chloritization,
sericitization), ferric stains (mainly limonitization) and
carbonates (calcitization). Figure 2 shows the laboratory
reflectance spectra of relevant minerals and the corresponding
resampled ASTER spectra. The hydroxyl-bearing or carbonate
minerals exhibit distinct absorption features centered near 2.20
μm (band 6) or 2.32 μm (band 8), with relatively stronger
reflectance around bands 4 and 7 (Hunt, 1977). For the
ferric-iron minerals, a distinct absorption feature locates around
band 1 and band 3 (Hunt, 1977). These spectral absorption
features provide the basis for identifying lithology and mapping
alteration minerals.
Therefore, a series of procedures were adopted in the
image processing and unknown mineral resources targeting.
First of all, false colour composition (FCC) and principal
component analysis (PCA) were used in enhancing the
lithological differences. Secondly, PCA and spectral angle
mapper (SAM) algorithm were employed to discriminate
alteration minerals.
3.3
False Colour Composition
Lithology discrimination using remote sensing data is
mainly based on certain factors, such as chemical and mineral
composition, colour or tone, grain-size or roughness,
weathering characteristics, soil and vegetation (Xiong et al.,
2011; Kenea, 1997). Different bands could be selected
according to reflectance spectroscopy data of the rocks to
(b)
0.5
1.0
2.0
1.5
Wavelength (µm)
2.5
Figure 2. Five pairs of laboratory reflectance spectra of
some common minerals which are important in the study
area. (a) USGS Spectral Library pattern; (b) spectra
re-sampling to ASTER bandpass (modified after USGS
Spectral Library).
compose false colour composite images to determine the
lithology (Xiong et al., 2011; Di Tommaso and Rubinstein,
2007; Moghtaderi et al., 2007; Kenea, 1997). Therefore, FCC
was used on VNIR and SWIR bands to separate the main
lithological groups especially the small intrusions exposed in
the study area.
3.4
Principal Component Analysis
Principal components analysis (PCA) is an image
enhancement technique for displaying the maximum spectral
contrast from multispectral bands, while the resultant
components are often more interpretable than the original
images (Tangestani et al., 2008; Singh and Harrison, 1985).
PCA has been applied widely to multispectral remote sensing
images with the purposes of enhancing the spectral differences
and extracting specific spectral responses (Amer et al., 2012,
2010; Liu et al., 2011; Moore et al., 2008; Tangestani et al.,
2008; Crosta et al., 2003). Standard PCA has been applied to
outline the lithological differences and map alteration minerals.
Lei Liu, Jun Zhou, Fang Yin, Min Feng and Bing Zhang
3.5
1 2
Spectral Angle Mapper
The spectral angle mapper (SAM) algorithm treats spectra
as multidimensional vectors and calculates angles of similarity
between them, operated by comparing image spectra with
reference spectra (either library or from endmember derivation),
with smaller SAM angles indicating greater similarity (Amer et
al., 2012; Galvão et al., 2005; Kruse et al., 1993). This method
is independent of illumination conditions (i.e., topographic
shading) and widely used for spectral matching (Bishop et al.,
2011).
In this work, image-derived endmembers were used as
reference spectra which were collected based on the standard
methodology developed by Kruse et al. (2003). Firstly,
minimum noise fraction transformation (MNF) (Green et al.,
1988), pixel-purity index (PPI) and n-Dimensional Visualizer
techniques (Kruse et al., 2003; Green et al., 1988) were applied
consecutively to the ASTER data to locate the purest pixels.
Secondly, the regions with highest DN values in the PCA
images were adopted to filter and identify endmember spectra.
Eventually, four image end-members were selected (Class 1 to
Class 4 in Fig. 3). Although the image endmembers do not
match the laboratory reflectance spectra ideally due to the
influences such as the presence of variable mineral-mineral
mixtures, mineral-vegetation mixtures and grainsize variations
(Mars and Rowan, 2006; Rowan et al., 2005; Rowan and Mars,
2003), they still retain the key absorption features centered near
bands 1, 3, 6 and 8 (Fig. 3). The Class 1 displays absorption
features in bands 6 and 8 which are caused by muscovite,
chlorite, carbonate minerals and slight kaolinite (Fig. 3). The
absorption in band 6 indicates that the Class 2 is composed of
muscovite and slight kaolinite. The special spectra shape of
Class 3 is mainly dictated by kaolinite and ferric-iron oxides.
Furthermore, the Class 4 is characterized by the absorption in
bands 1 and 3, which is caused by absorption in ferric-iron
oxides.
4 RESULTS AND DISCUSSION
4.1 Lithological Map
The best compositions were achieved using the ASTER
composite of bands 521 (RGB) that provide good
discrimination of lithologies especially the small intrusion
comprises certain different phases (Fig. 4a). The lithological
difference in the intrusive rocks of the study area is clearly
outlined in different colour. Potash-feldspar granites have
carroty colour, hornblende or biotite granites have orange with
greyish colour. The quartz monzonite and tonalite have
charcoal grey colour roughly predominate in the southwestern
part of the batholith. Some small intrusions are identified by
light grey and carroty colour which occur in the south part of
the study area.
The nine principal components resulting from analysis of
9-band ASTER images were used to outline the lithological
differences. The image eigenvectors and eigenvalues obtained
from PCA, using covariance matrix on all nine bands of
ASTER of the Jiafushaersu area are indicated in Table 1. The
first three principal components (PCA1, PCA2, PCA3) are used
in lithological mapping because they contain 99.33% of the
spectral information. The results show that lithological units
Reflectance (offset for clarity)
400
0.5
3
ASTER Bands
5 67 8 9
4
Class 4
Class 3
Class 2
Class 1
1.0
1.5
Wavelength (µm)
2.0
Figure 3. Four representative endmember spectra extracted
from ASTER image. Class 1, muscovite, chlorite, carbonate
minerals and slight kaolinite; Class 2, muscovite and slight
kaolinite; Class 3, kaolinite and ferric-iron oxides; Class 4,
ferric-iron oxides.
especially the small intrusions in the Jiafushaersu area were
discriminated on the false colour composite imagery (PCA1,
PCA2, PCA3) in R, G, B (Fig. 4b). The small intrusions are
identified by white, pink and red colour. The small intrusions in
white colour are interpreted as potash-feldspar granites. Field
inspection indicates that the small intrusions in pink and red
colour are aplite (pink) and small quartz monzonite porphyry
bodies (red).
Geological interpretation of the area studied has been
principally based on the processed images referred to a
geological map of this area produced by GBXBGMR (1966) at
a scale of 1 : 200 000. A lithological map of Jiafushaersu area
has been generated from the ASTER band composition and
PCA images (Fig. 5). Field validation was carried out to map
the small intrusions and contacts supporting the results
obtained from ASTER-based method.
Two SW-NE orientated granitoid intrusions, probably
united below the surface or in depth, are developed in the foot
wall of Darbut and extend eastwards about 40 km from
Tuketuke to Jiafushaersu (Fig. 1). Ground inspection shows
that the intrusion comprises certain different phases: the major
part is formed by the potash-feldspar granite (carroty on
RGB521) and the hornblende or biotite granite (orange with
greyish tone), the quartz monzonite and tonalite (grey) roughly
predominate in the middle part of the batholith, and some small
quartz monzonite porphyry bodies (light grey) occur around the
batholith margin (Figs. 1, 4). Aplite is also present in the
proximity of the batholith.
4.2
Principal Component Analysis
PCA was applied to all nine bands of ASTER imagery to
highlight alteration minerals. The covariance eigenvalues and
eigenvector matrix of the PCA using all nine bands is given in
Table 1. The methodology used here mainly followed the
studies of Pour and Hashim (2011).
The first principal component (PCA1) is composed of a
positive weighting from all nine bands. Overall scene
The Reconnaissance of Mineral Resources through ASTER Data-Based Image Processing
brightness, or albedo, is responsible for the strong correlation
between the nine bands (Pour and Hashim, 2011). Eigenvector
loadings for PCA2 indicate the difference of the VNIR bands
with SWIR bands. PCA3 is a comprehensive reflection of all
nine bands. This transformation also indicates a moderate
eigenvector loadings for ASTER bands 3 and 2 with opposite
sign (+0.487 and -0.036), which probably indicate the
enhancement of the vegetation. The eigenvector loadings show
that PCA4, PCA5 and PCA6 contain the alteration information
according to the position of characteristic absorption features of
alteration minerals. PCA7, PCA8 and PCA9 are noisy and
uninformative.
The simple methodology for iron oxides mapping by PCA
on ASTER data is meant to examine the eigenvector loadings
for bands 1, 2 and 4 in PCA4, PCA5 and PCA6 in order to find
the component with a moderate or strong loading with opposite
signs from both bands (Pour and Hashim, 2011). Iron oxides
can be mapped as bright pixels in PCA4 because of the positive
contribution from band 4 (0.560), while negative contributions
from band 1 (-0.454) and band 2 (-0.105) (Table. 1).
Eigenvector loadings of bands 4, 5, 6 and 7 in PCA5 are
-0.429, 0.479, 0.511 and -0.219, respectively (Table 1).
Considering the magnitude and sign of the eigenvector loadings
in PCA5, PCA5 highlights the Al-OH bearing minerals as dark
pixels. Therefore, PCA5 image was inversed in order to show
altered areas in bright pixels.
Eigenvector loadings in PCA6 indicate similar results with
moderate or strong eigenvector loadings in bands 8 (-0.229)
and 9 (0.651) (Fe, Mg-OH bearing minerals, carbonates),
respectively (Table 1). Therefore, PCA6 can be indicator of
propylitic alteration zones with bright pixels.
Figure 6 shows RGB colour composite of PCA4 (iron
oxides), inversed PCA5 (Al-OH bearing minerals), and PCA6
(Fe, Mg-OH bearing minerals and carbonates) image of the
study area. Alteration minerals are depicted as white to yellow
colour (iron oxides), green to yellow colour (sericite/muscovite
and kaolinite), and blue to white colour (chlorite and carbonate),
which are easily recognizable from surrounding rocks (Fig. 6).
Spectral Angle Mapper Alteration Zones
The four image-derived endmembers shown in Fig. 3 for
the identified alteration minerals were used as reference spectra
to perform SAM supervised classifications of visible and
shortwave infrared 9-band ASTER image. The threshold value
of 0.05 radians was used to represent the smaller angle that
matches the pixels spectra to the reference spectra. The results
of SAM processing based on the ASTER image-derived
endmembers (classes 1 to 4 in Fig. 3) are shown in Fig. 7.
The SAM results indicate that the dominance of kaolinite
and ferric-iron oxides (blue colour) in the aplite and in some
locations in the small quartz monzonite porphyry bodies (Fig.
7). The small quartz monzonite porphyry intrusions in are
highly altered with muscovite, chlorite, carbonate minerals and
slight kaolinite (red colour). The southernmost quartz
monzonite porphyry intrusion has strong alteration of
sericitization and kaolinization (green colour). The ferric-iron
401
oxides mainly occur in the southeast part of the study area
(cyan colour).
4.4
Ground Inspection and Studies
The lithological difference in the intrusive rocks of
Jiafushaersu (Figs. 4, 5) is clearly outlined by certain false
colour composites (using VNIR and SWIR) and PCA imagery.
Some alteration minerals (Fig. 6) are also highlighted by the
PCA-based discrimination, which belong to primarily
hydroxyl-bearing (chlorite, sericite and kaolinite) or ferric
(limonite) and less commonly carbonate types (minor calcites
growing on the greisenized quartz veinlet walls and dispersed
on the surface by weathering). The SAM mapping results
basically correspond to the PCA ones (Figs. 6, 7). The
alteration zones discriminated by the image processing
techniques were verified through ground inspection.
The in situ field work led to the discovery of the
mineralized quartz monzonite porphyry in Jiafushaersu (points
1, 2 and 3 in Fig. 7), 0.72 km2. Three other similar bodies,
scattered to the northeast, only show slight mineralization and
4.3
Figure 4. (a) ASTER colour composition (5, 2 and 1) and (b)
(PCA1, PCA2 and PCA3) in RGB showing the intrusive
rocks in different colour.
402
Lei Liu, Jun Zhou, Fang Yin, Min Feng and Bing Zhang
Table 1
Eigenvector matrix of principal components analysis on VNIR+SWIR
bands of ASTER data for Jiafushaersu area
Input
bands
Band
1
Band
2
Band
3
Band
4
Band
5
Band
6
Band
7
Band
8
Band
9
Eigen values
(%)
PC1
0.269
0.337
0.322
0.352
0.317
0.335
0.357
0.377
0.322
94.681
PC2
-0.560
-0.506
-0.373
0.112
0.245
0.261
0.213
0.227
0.232
4.206
PC3
-0.292
-0.036
0.487
-0.465
-0.367
-0.104
-0.029
0.268
0.492
0.444
PC4
-0.454
-0.105
0.587
0.560
-0.010
-0.063
-0.126
-0.220
-0.238
0.301
PC5
0.060
-0.154
0.293
-0.429
0.479
0.511
-0.219
-0.406
0.002
0.133
PC6
0.200
-0.100
-0.157
0.369
-0.079
0.000
-0.554
-0.229
0.651
0.099
PC7
0.526
-0.759
0.238
0.073
-0.157
-0.062
0.208
0.085
-0.075
0.060
PC8
-0.027
0.003
0.035
-0.057
0.358
-0.573
0.464
-0.467
0.323
0.042
PC9
-0.034
0.092
-0.082
0.067
-0.562
0.459
0.444
-0.494
0.103
0.035
22%–38% (27.75%), potash-feldspar 19%–31% (27.50%) and
biotite 9%–12% (11.0%), though the thin section failed to cut
hornblendes, falling into the granite district of the International
Union of Geological Sciences (IUGS) classification
(http://www.iugs.org/), but being closer to the granodiorite. It is
thus named quartz monzonite porphyry (molybdenum
mineralized) considering the presence of quartz phenocrysts
and on account of its notable difference from the granodiorite
porphyry (copper mineralized) in Tuketuke, which contains
24% quartz, 47% plagioclase, 16% potash-feldspar and 13%
biotite plus hornblende on the basis of sixteen thin section
statistics. On the other hand, the granodiorite porphyry in
Baogutu, which was related to the mineralization, was
re-defined as the diorite porphyry by a recent petrographic
study (Shen et al., 2009). In any event, the parent porphyry for
the molybdenum mineralization petrologically resembles that in
Climax in being silica- and alkali-rich with abundant quartz,
potash feldspar and albite (Hendry et al., 1988).
The surface observation or the shallow denudation at the
apex exhibited that the molybdenite with minor chalcopyrite
was clustered in the greisenized quartz veinlet (mostly 1–2 cm
Figure 5. Detailed lithological map of the Jiafushaersu area
based on interpretation of the FCC and PCA images.
are 0.075, 0.050 and 0.145 km2 (in the order toward the
northeast) in area. Sparsely-distributed hornblendes
(needle-shaped) and biotites imply a feature slightly toward the
intermediate, but considerable quartz phenocrysts connote
somewhat closer to the acid despite a relative scarcity of
potash-feldspar phenocrysts (Figs. 8a, 8b), grossly resembling
the specimen from Jinduicheng (Zhu et al., 2010), a giant size
molybdenum porphyry deposit at the south margin of the North
China Block. The petrological composition, based on four thin
sections, of the mineralized porphyry in Jiafushaersu consists
mainly of quartz 30%–37% (avg. 33.75%), plagioclase
Figure 6. RGB colour composite of PCA4, PCA5 (inversed),
and PCA6 images, showing hydrothermal alteration halos
corresponding with the identified small intrusions.
The Reconnaissance of Mineral Resources through ASTER Data-Based Image Processing
wide) that was formed mainly by coarse transparent quartzes
and had some large flake of white micas and fine calcites on the
wall (Fig. 8c). Only certain chalcopyrite was seen to be
disseminated in the porphyry during the inspection. Fluorite,
topaz, magnetite and huebnerite were not found at this stage,
although those were common in the molybdenum stockwork of
Climax (Stein and Hannah, 1985). Additionally, the veinlet in
Jiafushaersu strictly occurs in four sets of fractures rather than
forms the stockwork (Fig. 8d). Their attitudes are recognized as
(1) dipping SE130° with a 25° angle; (2) trending NW325°,
nearly vertical; (3) dipping SE140° with a 63° angle; and (4)
trending NE35°, nearly vertical. The wall is straight and flat,
indicating a very stable extension toward the depth, although
the third set (dipping SE140°, angle 63°) is not so steady.
403
Among them the first set (dipping SE130°, angle 25°) is the
major molybdenum-bearing structure with a space between 30
and 50 cm. Nevertheless, the structural relation between those
fractures and the large-scale sinistral strike-slipping fault (Fig.
7b) is uncertain.
Only in the southwestern corner of the mineralized
porphyry were trenches and open pits available during the
studies. An investigation through the limited excavation
revealed that the immediate host rock of veinlets was typified
by the intensive silicification plus chloritization and
calcitization (dense, hard and dark greyish), whereas
sericitization, kaolinization and limonite or ferric stains were
ubiquitous in the porphyry. Thin sections further detailed that
chloritization mainly took place in both biotite and basic
Figure 7. (a) Result of SAM mapping method overlain on bands 521 (RGB) and (b) enlargement of the exploration target in
(a). Classes 1 to 4 refer to Fig. 3.
plagioclase, calcitization was primarily developed along the
veinlet wall, kaolinization was mostly related to potash feldspar
while sericitization to plagioclase. Certain kaolins were
doubtless originated from the surface weathering, especially
those with ferric stains. But the distinguishable features based
on various image processes (Figs. 6 and 7) suggest that the
mineralized porphyry is notably different from its neighboring
rocks in the lithology and wall-rock alteration as a whole. In the
mineral exploration sense, the differential weathering, even if
present, just reflects an essential disparity and can be also used
for locating a target. At this stage, it is difficult for us to
generalize macroscopically the zoning pattern of the wall-rock
alteration due to the limited exploration.
4.5
Discussion
The known porphyry or porphyry-like coppermolybdenum-gold mineralization points or deposits in West
Junggar have been mostly located at the foot wall of the suture
or at the subducted side to date, notably challenging the
previous well-known metallogenic model (Groves et al., 1998;
Chen, 1996), which postulated these types of mineral deposits
to have been originated from a far-off zone at the hanging wall
or toward the continent. It led us not only to think over the
metallogenic theory, but also to revalue how to target the
mineral resources of this kind. Furthermore, the mineral
exploration in both Tuketuke (Zhang et al., 2009) and
Jiafushaersu (this study) commenced with a remote
sensing-orientated study. The mineralization characteristics
combined with the image processing and interpreting are
substantiated as follows.
The small intrusions with distinct lithology are clearly
outlined by false colour composites of bands 521 in R, G, B)
and PCA images (PCA1, PCA2, PCA3) in R, G, B (Fig. 4).
Among the newly documented small intrusions, the quartz
monzonite porphyry appears in red colour on the PCA image
(Fig. 4b) due to the high reflectance in VNIR. Potash-feldspar
granite bodies have been separated from the dominantly
hornblende or biotite granite due to their white colour on the
PCA image which is attributed to the major spectral feature of
potash feldspar. The hornblende or biotite granite as well has
been separately mapped based on the processed images (Fig. 4b)
in pink colour, with rough texture. Additionally, the aplite is
present in the proximity of the batholiths in yellow with red
tone.
Both PCA and SAM methods received satisfactory
alteration mineral mapping results. The PCA results indicate
404
the dominance of iron oxides, sericite and kaolinite, and
chlorite and calcite in the quartz monzonite porphyry, aplite
and in some locations in the potash-feldspar granite. The SAM
results outline the alteration mineral assemblages basically
correspond to the PCA ones, but more explicitly.
Some of the mapped alteration zones in PCA and SAM
agree very well with the GPS locations of ground inspection in
the Jiafushaersu area (Points 1 to 11 in Fig. 7). The results
Lei Liu, Jun Zhou, Fang Yin, Min Feng and Bing Zhang
reveal new alteration zones in the four small quartz monzonite
porphyry intrusions within the hornblende or biotite granite.
The ground inspection led to the discovery of the mineralized
quartz monzonite porphyry. Results indicate that the workflow
of the image processing, interpretation and ground inspection is
a powerful mineral targeting method for the reconnaissance
stages of mineral exploration in a regional scale.
Figure 8. (a) Thin sections of quartz phenocrysts and plagioclase in quartz monzonite porphyry; (b) quartz phenocrysts and
potash-feldspar in quartz monzonite porphyry; (c) polished section of molybdenite in the greisenized quartz veinlet; (d) four
sets of fractures control veinlets and mineralization in Jiafushaersu.
The analogousness of the mineralization in Tuketuke and
Jiafushaersu to the porphyry type mineral deposit can be also
corroborated by relevant geochemical facts, although the size
of them is limited at this stage, especially for Jiafushaersu,
because the exploration is ongoing. As we know, a genetic
correlation between adakites and porphyry copper-gold
deposits has been elucidated by many studies (e.g., Oyarzun et
al., 2001), and the general criteria for adakites are: SiO2＞56%,
Al2O3＞15%, Sr＞400 ppm and Y＜16 ppm. The assays of the
copper-mineralized granodirite porphyry in Tuketuke (two
samples) yielded a similar result: (1) SiO2 67.37%, Al2O3
15.14%, Sr 270 ppm and (2) SiO2 66.73%, Al2O3 14.97%, Sr
300 ppm and the relative depletion of strontium was interpreted
as being not so fresh for the samples (Zhang et al., 2009).
Moreover, the molybdenum-mineralized porphyry in
Jiafushaersu spatially correlates with a tungsten anomaly (2.5
ppm) on the basis of the geochemical survey result at a scale of
1 : 200 000, implying an intimate relation between
molybdenum and tungsten as it is in Climax (Hall et al., 1974)
notwithstanding tungsten minerals have not been found yet in
Jiafushaersu.
5
CONCLUSION
Eventually, combined with the achievements in previous
studies of the regional mineralization in West Junggar, the
recognition of both remote sensing and geology in Jiafushaersu
by this study can result in drawing the following conclusions.
First, the successful exploration of the Baogutu porphyry
copper-gold deposit (Shen et al., 2009; Song et al., 2007;
Cheng and Zhang, 2006) intensified the targeting of similar
mineral deposits in the same tectonic setting. The new addition
or the recent progress of ore prospecting in Tuketuke (Zhang et
al., 2009) and Jiafushaersu (this study), together with the many
newly-found similar mineralization points, further verified that
the foot wall of the Darbut suture could have served as a more
important metallogenic district for the porphyry copper and
molybdenum deposits. This may contribute to forming a better
metallogenic theory later.
Second, the Jiafushaersu molybdenum-mineralization site
is about 35 km (straight line) east of the Tuketuke porphyry
copper-gold deposit and this is a granitoid batholith-dominated
zone (Fig. 1). The batholith is formed by certain intrusive
phases and identified by many small granodiorite or quartz
monzonite-porphyry stocks around its margin. This implies that
The Reconnaissance of Mineral Resources through ASTER Data-Based Image Processing
the relevant zone is of a big potential in the porphyry type
copper-gold resources due to its size.
Third, the different intrusive phases are clear in
multispectral or PCA false colour composite. The ASTER
bands 521 (RGB) is one of the best composites that provide
good discrimination of the small intrusions (Fig. 4). The quartz
monzonite porphyry is rounded, in light grey colour and occurs
around the batholith margin. These similar small intrusions,
despite often omitted by the geological map at a scale of
1 : 200 000, are clearly outlined by ASTER images and very
useful for prospecting.
Fourth, PCA and SAM algorithm were employed to
discriminate alteration minerals. For the PCA results, the
hydroxyl-bearing (chlorite, sericite and kaolinite) or ferric
(limonite) and less commonly carbonate types (minor calcite)
show good correlation with the quartz monzonite porphyry and
aplite in the south (Fig. 6). The SAM mapping results basically
correspond to the PCA ones (Fig. 7).
Fifth, the workflow of ASTER images processing,
interpretation and ground inspection, together with synthetic
analysis with geologic data, is an efficient and powerful
mineral targeting method, which can be applied in the sparsely
vegetated arid region in northwestern China.
Last, the features of lithology, alteration minerals and
tungsten-rich
geochemical
signature
of
the
molybdenum-mineralized intrusion in Jiafushaersu imply that
the molybdenum mineralization is close to the porphyry type.
ACKNOWLEDGMENTS
The study was supported by the Special Fund for Basic
Scientific Research of Central Colleges of China (Nos.
CHD2011SY013, 2013G1271103), Chang’an University,
China and the Central University Foundation of China (Nos.
CHD2011ZY005, CHD2011JC168).
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