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Detecting lithology with Advanced Spaceborne Thermal Emission and
Reflection Radiometer (ASTER) multispectral thermal infrared
radiance-at-sensor data
Yoshiki Ninomiya a,*, Bihong Fu b, Thomas J. Cudahy c
a Geological Survey of Japan, AIST, Tsukuba 305-8567, Japanb Lanzhou Institute of Geology, Chinese Academy of Sciences, Lanzhou 730000, China
c CSIRO Exploration and Mining, PO Box 1130, Bentley, WA 6101, Australia
Received 1 October 2004; received in revised form 7 June 2005; accepted 20 June 2005
Abstract
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard NASAs Terra satellite measures multispectral
thermal infrared (TIR) emission from the Earths surface to space. Based on analysis of TIR spectral properties of typical rocks on the Earth,
several mineralogic indices including the Quartz Index (QI), Carbonate Index (CI) and Mafic Index (MI) for detecting mineralogic or
chemical composition of quartzose, carbonate and silicate rocks with ASTER-TIR data are proposed. These indices are applied to the
ASTER-TIR data scenes for selected study areas in China and Australia. The results show that ASTER-TIR can discriminate quartz and
carbonate rocks as well as maficultramafic rocks, even with atmospherically uncorrected radiance-at-sensor data. Lithologic interpretations
agree well with published geologic data and field observations. The mineralogic indices applied to ASTER-TIR provide one unified approach
for lithologic mapping in arid and semi-arid regions of the Earth.
D 2005 Elsevier Inc. All rights reserved.
Keywords: Quartz; Carbonate; Silicate; Mafic; Felsic; Ophiolite; Mineralogic indices; Emissivity spectra; ASTER; Thermal infrared; Geology; Lithologic
mapping
1. Introduction
In a pioneering study of spectroscopy, Lyon (1965)
demonstrated that silica and silicate minerals, the major
components of the Earths crust, show strong fundamental
spectral bands corresponding to the SiO bond length in the
thermal infrared (TIR) atmospheric window (8 12 Am),although they do not cause prominent spectral features in
the visible to shortwave infrared region of the spectrum
(0.42.5 Am). Various workers (e.g., Hunt & Salisbury,
1974; Salisbury et al., 1988) have shown that TIR
emissivity spectra of igneous rocks are correlated with the
bulk (chemical) SiO2 content.
Remote-sensing for lithologic mapping using TIR
spectral signatures was first demonstrated using the
airborne Thermal Infrared Multispectral Scanner called
TIMS (Kahle & Goetz, 1983; Kahle et al., 1980; Kahle &
Rowan, 1980). Similar airborne systems (e.g., Fu & Chou,
1998) confirmed the usefulness of TIR multispectral
remote sensing. These TIR systems were able to measurethe changes in wavelength of the broad emissivity low
related to the Si O bonds. Systems with higher spectral
resolution, such as MIRACO2LAS (Cudahy and others,
1999) and SEBASS (e.g., Cudahy et al., 2000), are able to
map more detailed TIR spectral signatures related to the
abundances and chemistries of specific silicate, sulphate
and carbonate minerals.
The Advanced Spaceborne Thermal Emission and
Reflection Radiometer (ASTER) sensor was developed
based on the success of TIMS, and was launched onboard
0034-4257/$ - see front matterD 2005 Elsevier Inc. All rights reserved.
doi:10.1016/j.rse.2005.06.009
* Corresponding author.
E-mail address: [email protected] (Y. Ninomiya).
Remote Sensing of Environment 99 (2005) 127 139
www.elsevier.com/locate/rse
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Terra in December 1999. Terra was the first of NASAs
Earth Observation System (EOS) series of satellites. It
obtains multispectral image of the Earth (Yamaguchi et
al., 1998) not only in the visible to near-infrared (VNIR;
three bands between 0.5 and 0.9 Am, 15-m resolution,
stereoscopic capability for the NIR band) and in the
shortwave infrared (SWIR; six bands between 1.6 and 2.5Am, 30-m resolution), but also in the TIR (five bands
between 8 and 12 Am, 90-m resolution, NEDT
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any spectral features in VNIR to SWIR. In contrast, they
have prominent spectral features in TIR region due to
fundamental asymmetric Si O Si stretching vibrations.
Quartz, the most common mineral on the Earth, shows
absorption features (i.e., emissivity minima) in ASTER
bands 10 and 12, resulting in higher emissivity in band 11
than in bands 10 and 12, as shown in Fig. 1b. The series of
alkali feldspars (K-feldspars), which often coexist with
quartz in felsic igneous rocks, have a strong emissivity peak
in band 11, resulting in lower emissivity in band 11 than in
bands 10 and 12, contrary to the property of quartz
described above. For silica and silicate minerals and rocks,
the broad spectral emissivity low corresponding to SiObond length shifts to longer wavelength as the chemical
SiO2 content (weight percent) decreases. After this property,
the ratio of the emissivity at band 12 to band 13 for silicate
rocks (typically igneous rocks) increases as the SiO2 content
decreases (i.e., as the rock type changes from felsic to
mafic), as shown in Fig. 1c, d, e and f. In addition, some
sulfate minerals including gypsum have a very strong
absorption at band 11 spectral region (i.e., near 8.7 Am)
due to stretching fundamentals, as a result, it exhibits lower
emissivity in band 11 than in bands 10 and 12, likely the
property of K-feldspars described above (Ninomiya & Fu,
2003). According to published spectral properties, some
oxides (Salisbury et al., 1992) and halite (Crowly & Hook,
1996) show similar spectral shape to ultramafic rocks (i.e.,
emissivities are high in ASTER bands 10 to 12; low in
ASTER bands 13 and 14).
2.3. Definition of indices (Ninomiya & Fu, 2002)
From the spectral emissivity property of a carbonate rock
composed of calcite and dolomite, the two major carbonate
minerals on the Earth, shown in Fig. 1a and described in
Section 2.1, the Carbonate Index (CI) for ASTER-TIR data
is defined as
CI D13
D14; 6
where Di is any kind of ASTER data related to ASTER
band i. In this paper, we use radiance-at-sensor data
without atmospheric corrections for D. CI is expected to be
high for calcite and dolomite. No peculiar response isexpected for other carbonate minerals.
From the spectral emissivity property of quartz shown in
Fig. 1b and described in Section 2.1, the Quartz Index (QI)
is defined as
QI D11 D11
D10 D12: 7
QI is expected to be high for quartz and low for K-feldspar
and gypsum.
As described in Section 2.1, the broad spectral emissivity
low shifts to longer wavelengths as the chemical SiO2
content in silicate rock decreases, as shown in Fig. 1c to f.This introduced the definition of the Mafic Index (MI) as
MI D12
D13: 8
MI is correlated to the SiO2 content in silicate rocks,
typically igneous rocks, but it is also sensitive to carbonates.
To eliminate this unexpected property of MI, a series of
Mafic Index separated for carbonates, MIn, is redefined as
MIn D12
D13ICIn
D12ID14n
D13n1: 9
The original MI is the case for which n =0. Comparingimages of different versions of MIn series shows good
separation of carbonates and silicates in MI3 (Ninomiya,
2002). Therefore, in the present paper, we use MI3 for MI.
MI is expected to correlate negatively with the SiO2 content
in silicate rocks. That is, it is expected to be high for
ultramafic rocks, and systematically lower as the rock type
changes to felsic and finally quartzose rock. MI is expected
to be high for halite and some iron oxides with the spectral
property described in Section 2.1. For theoretical blackbody
and natural graybody materials, typically vegetation,
MI0.89, which is similar to index values for intermediate
rocks with chemical SiO2 content65% (Ninomiya, 2002).
Fig. 1. Emissivity spectra of (a) carbonate rock, (b) quartzose rock, (c)
granite, (d) diorite, (e) gabbro, (f) peridotite, with the convolved data to
ASTER bandpasses. Each tick in Y-axis registers 1.0/0.75 in emissivity
except for (b): 1.0/0.5.
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This MI value is expected to be a robust boundary between
mafic and felsic rocks, with minimum influence of other
factors on spectral contrast, for example, atmospheric
downwelling irradiance and topographic effects, because
blackbodies have low spectral contrast.
2.4. Stability analysis and improvement
The Carbonate Index (CI), Quartz Index (QI) and Mafic
Index (MI) were calculated from ASTER Level-1B data.
Scene-dependent qualitative analyses were made of the gray-
scale images of each index and the false-color composite
image of the three indices. Ninomiya and Fu (2002) pointed
out the potential usefulness of these indices for discriminat-
ing rock types. A theoretical analysis of the stability of the
indices with respect to surface temperature and atmospheric
parameters indicates that QI and MI are insensitive to
temperature, provided atmospheric conditions are good, but
that CI is heavily affected by temperature differences even ingood atmospheric conditions. We have confirmed these
properties of the indices by analysis of multi-temporal
images of known study areas (Ninomiya, 2002). Normal-
ization of the brightness temperature for band 13 to a fixed
temperature reduces the heavy dependency of CI to surface
temperature. The normalized radiance at sensor at band i is
defined as
nLisen Lisen
expk13
kiIln
c1
k135
L13sen 1
!( ) 1
expc2
ki
nT=ea13 1
;
10
where Lseni is radiance at sensor in band i, ki is the center
wavelength (Am) of band i, ea13 is the assumed emissivity in
band 13, nT is the fixed temperature (K) to be normalized,
and c1 and c2 are the radiation constants given in Eq. (5).
Here in this study, ea13 is adopted as 1.0, and nTis adopted as
300. Case studies with the indices applied to the normalized
radiance-at-sensor data suggested successful improvement
on the ability of CI in mapping carbonate rocks (Ninomiya,
2003; Ninomiya, 2004; Ninomiya & Fu, 2003). The
normalization processing is not important for QI and MI;
however, here the normalized radiance at sensor is used for
all the indices for the uniformity of the data processing.
Hereafter, the indices applied for the normalized radiance
calculated with Eq. (10) are expressed as CI, QI and MI,
respectively.For analyzing the sensitivity of the indices to the
atmospheric parameters, simulated ASTER-TIR radiance-
at-sensor data were generated for a 300-K blackbody and
typical rock samples shown in Fig. 1. Spectral atmospheric
transmissivity, path radiance and downwelling irradiance
were derived using an atmospheric radiative transfer
model, MODTRAN, a moderate-resolution version of
LOWTRAN 7 (Kneizys et al., 1988), applied to the
mid-latitude summer model atmosphere. The measured
emissivity spectra in Fig. 1 and the calculated spectra of
atmospheric parameters are convolved into responsivity
function of each band in ASTER-TIR (Fujisada, 1995) togenerate ei, si, LAji and EA,
i in Eq. (5). The spectral
contrast of emissivity for the surface rocks in remote
sensing is usually degraded by various factors, for
example, weathering, topography and mixing with gray-
body materials like vegetation. The degraded emissivity,
ed, can be estimated as
ed e 1 Ia 1; 11
where the degradation ratio, a, is between 0 and 1. Here,
degradation is not considered in generating simulated
ASTER-TIR radiance-at-sensor data, so a=1. (Downwel-
Fig. 2. The Carbonate Index (CI) calculated on simulated radiance-at-sensor
data vs. atmospheric water-vapor content (kg/m2) assigned in MODTRAN
at the elevation of 1000 m asl.
Fig. 3. The Quartz Index (QI) calculated on simulated radiance-at-sensor
data vs. atmospheric water-vapor content (kg/m2) assigned in MODTRAN
at the elevation of 1000 m asl.
Fig. 4. The Mafic Index (MI) calculated on simulated radiance-at-sensor
data by atmospheric water-vapor content (kg/m2) assigned in MODTRAN
at the elevation of 1000 m asl.
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ling atmospheric irradiance also degrades the spectral
contrast of emissivity as shown in Eq. (5), but this term
is treated separately.)
As an example, the effect of water vapor content (kg/m2)
assigned in MODTRAN at the elevation of 1000 m above
sea level (asl) on CI calculated from the simulated radiance-
at-sensor data is shown in Fig. 2. By comparing the resultsshown in Fig. 2 with the result derived by changing the
elevation of scene, it became clear that the main atmos-
pheric factor affecting the indices is water vapor content.
Fig. 2 indicates that CI is >1.04 for the carbonates only if
the atmospheric water vapor content is less than 15 kg/m2.
The corresponding relationships for QI and MI are shown in
Figs. 3 and 4, respectively.
Figs. 24 suggest each index responds sensitively for the
targeted rock types. This indicates the possibility of
mapping the target rock types using fixed threshold values
independent of the specific scene, provided that the
atmospheric conditions are good enough.Fig. 5 shows for ASTER Level-1B images a scatter
diagram of the histogram peak of CI vs. precipitable water
vapor content drawn from NCEP Reanalysis data provided
by the NOAA-C IRE S Climat e Diagno sti cs Center,
Boulder, Colorado, USA, from their Web site at http://
www.cdc.noaa.gov/. The closed dots in Fig. 5 are for
highly vegetated ASTER images, which are expected to
represent CI of graybody vegetation. The open dots are for
sparsely vegetated ASTER images, which may be affected
by the distribution of rocks in the image. Fig. 5 suggests
the applicable threshold for mapping carbonate with CI
would be 1.04 to 1.045 when the atmospheric water vapor
content is low enough (as a guideline,
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Fig. 6. (a) A compiled geological map overlaid on an ASTER VNIR false-color composite image of the Mt. Yushishan study area. Abbreviated names of map
units: Z, Precambrian rocks; CO, Cambrian to Ordovician rocks; OS, Ordovician to Silurian rocks; P, Permian rocks. (b) Color-composite image of the
indices: QI=red, CI=green and MI=blue. Index values linearly scaled to display 99% of the histogram between 0 and 255 DN. The alphabetic labels identify
the targets of discussion in the main text. (c) Detected pixels with the indices as: red, quartzite (QI> 1.05); dark red, siliceous rock (QI> 1.03); yellow, carbonate
rock (CI> 1.045); dark yellow, possible carbonate rock (CI > 1.035); purple, ultramafic rock (MI> 0.92). Display is of MI image with a fixed gray-scale range of
0.8 to 0.9.
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those for mafic rocks. However, further investigation is
needed to determine whether the suspected mafic debris
exists or not. One possible source of confusion and
ambiguity is the presence of minerals showing similar
values of MI, for example halite or some iron oxides.
With respect to the older sequences, a part of Sinian
system mapped as Precambrian and shown as A in Fig. 6ahas high QI values (reddish) and we expect it to be quartzite,
but most of the rest of the Sinian system (B and the area
around Mt. Yushishan itself) has high CI values (greenish)
and we expect it to be limestone or dolomite. Except for the
Sinian system, other areas appear bluish, suggesting that the
local lithologies are dominated by silicates. In the Paleozoic
region, some parts (C), represented as magenta, are high
both in QI and MI, but low in CI. Others areas (D F)
are represented as bluish, typical for silicate rocks. Also, the
Paleozoic region includes a greenish part (G) that we
expect to be carbonate rocks.
The rock types detected on the basis of the individualindex values confirm the lithologies predicted from the
colors in Fig. 6b. That is, the regions expected from the false
colors to be quartzose or carbonate rocks are demonstrated
to have high enough QI (>1.05) or CI (>1.045) to qualify.
Each pixel thus classified is red or yellow, respectively, in
Fig. 6c. A secondary threshold on CI (>1.035 for this
image), dark yellow in Fig. 6c, complements the detection
of carbonate rocks, and a threshold on QI (>1.03 in this
case), dark red in Fig. 6c, is effective for detecting siliceous
rocks with relatively high quartz and low feldspar content.
The regions of Paleozoic silicate rocks are classified by MI
value as follows: the region D with average MI0.90 is
expected to be intermediate to mafic; the region E with
average MI0.87 is expected to be felsic; and the region
F composed of sub-regions with average MI of 0.87
0.90, is expected to be mixed felsic and mafic.
Most of the region of intrusions is displayed as bluish,
suggesting silicate composition. The analyses on the colors
combined with the relative tone in MI gray-scale image
shown in Fig. 6c, clearly indicate the different rock types.
Both units H and I are mapped as felsic intrusions (Fig.
6a); however, H appears darker in the MI image (Fig. 6c),
indicating a higher chemical SiO2 content than unit I.
Many veins in unit H with relatively high MI values (i.e.,
low SiO2 content) are recognized as linear features in the MIgray scale image, which is consistent with the field
observation. For the analysis based on the value of MI, the
gray scale of MI (Fig. 6c) was set between 0.8 (black) and 0.9
(white), and the pixels with MI>0.92 (colored purple) are
considered to be ultramafic rocks. MI values for both units
H and I are < 0.9, indicating felsic to intermediate
composition. The average MI value for unit H is 0.85,
and the value for unit I is 0.875, which suggests that the
chemical SiO2 content in I is the lower. Unit K, mapped
as ultramafic intrusions, is well-detected with MI > 0.92, and
unit J, mapped as mafic intrusions, is also well-detected
with MI>0.90. Unit J is displayed as white in Fig. 2c. MI
values indicate that part of the mapped felsic intrusions (L)
is, as appears, to have mafic to ultramafic composition,
although it is not indicated as such in the published geologic
map.
3.2. Mt. Fitton study area
The Mt. Fitton study area is in the eastern central part of
South Australia. It lies between 29-45V and 30-00V S, and
between 139-10Vand 139-30VE. The elevation there ranges
from 50 to 750 m asl. The climate is arid, and vegetation is
sparse. We analyzed an ASTER Level-3A image acquired
over the study area on April 24, 2000, using the three mineral
indices as for the Yushishan area discussed above. Fig. 7a
shows the geology compiled from a published geological
map (GSSA, 1965) overlaid on a VNIR false-color image of
the ASTER scene. Precipitable water at the time of the
ASTER data acquisition was6 kg/m2 as estimated from the
archived NCEP Reanalysis data. The Precambrian AdelaideSystem is developed well in the study area, with only minor
exposures of Jurassic and Cretaceous sequences. Fig. 7b, c
and d present the index images, CI (index values: 1.02
1.045), QI (1.01.06) and MI (0.80.9). Some rocks in the
study area have been hydrothermally altered. To locate
alteration minerals exhibiting Al OH spectral absorption
bands, two additional indices, OHIa and OHIb, were
generated (Ninomiya, 2003). OHIa is defined for ASTER
SWIR data as D4*D7 /D6 /D6, where Di is radiance-at-
sensor data for ASTER band i. OHIais used to detect minerals
having an absorption feature at 2.2 Am, typically montmor-
illonite and micas. OHIb is defined for ASTER SWIR data as
D4*D7 /D5 /D5. It is used to detect minerals having an
absorption feature at 2.17 Am, typically pyrophillite. Minerals
with absorption features both at 2.17 and 2.2 Am, typically
kaolinite and alunite, are detectable in both indices. The
results suggest that only altered minerals having absorption
feature at 2.2 Am occur in the Mt. Fitton study area. Together
with the geologic map, this suggests that the detected
alteration minerals are mostly micas. Pixels of alteration
minerals (OHIa>4.0) are displayed as cyan in Fig. 7f.
Alteration occurs in a variety of Precambrian sequences
and intrusions.
The region A is expected from its high CI values to be
carbonate (Fig. 7b). A is displayed as cyan in Fig. 7e.Usually, pure carbonate shows high CI and low QI and MI,
but in this case it shows relatively high MI (Fig. 7d). This
implies that carbonate and mafic minerals or rocks occur
together in the region, consistent with the published
geological map and field observations of talc and tremolite
there. Other thin or small units are expected from their CI
values to be carbonates. The regions labeled B are an
example; the southern region B is at Wildman Bluff ( Fig.
7a). Marginally high CI values for pixels in lines repre-
sented by C indicate the existence of carbonate-rich
layers unresolved in the 90-m ASTER-TIR pixels. Carbo-
nate content in the layers may be low. High CI values in
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D indicate the presence of some carbonate; however,
consideration of all the index values for D indicates
silicate composition.
Several small regions (E in Fig. 7c) with QI values
>1.05 display as reddish in Fig. 7e, indicating that they are
quartz-rich and feldspar-poor stone or sand. Some of the
regions seem to be in Cenozoic deposits; however, the
locations of the regions in general coincide with Mesozoic
formations. Regions labeled F have marginally high QI
values, but the composition cannot be specified without
consideration of the other index values discussed below.
The brightness of the MI image in regions G and H is
Fig. 7. (a) A compiled geological map overlaid on an ASTER VNIR false-color composite image of the Mt. Fitton study area. Abbreviations for map units: Pw,
upper Proterozoic Wilpena group in Adelaide system; Pu, lower Proterozoic Unberatana group in Adelaide system. (b) Gray-scale image of CI, linearly
stretched to display values from 1.02 to 1.045. Alphabetic labels identify the targets of discussion in the text. (c) Gray-scale image of QI, linearly stretched to
display values of 1.0 to 1.06. Alphabetic labels identify the targets of discussion in the text. (d) Gray-scale image of MI, linearly stretched to display values of
0.8 to 0.9. Alphabetic labels indicate the targets of discussion in the text. (e) Color-composite image of the indices: QI = red, CI= green, and MI= blue. Index
values have been linearly scaled to display 99% of the histogram for each color. (f) Pixels detected with the indices: red, quartzite (QI>1.05); dark red, siliceous
rock (QI> 1.04); yellow, carbonate rock (CI> 1.045); dark yellow, possible carbonate rock (CI > 1.04); cyan, Al OH bearing altered rock (OHIa>4.0); pink,
quartz-rich AlOH bearing altered rock (QI>1.04 and OHIa>4.0). Display is of MI image with a fixed gray-scale range of 0.8 to 0.9.
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similar, which suggests that the chemical SiO2 contents ofthe surface rocks exposed there are also similar. From the
MI values (0.850.86), it appears that the rocks are felsic
silicates. On the other hand, the QI values differ: for G,
QI1.005 to 1.015, whereas for H QI1.02 to 1.03.
This indicates that the rock types are different, even if the
chemical SiO2 content is the same. We interpret G to
contain felsic rocks rich in K-feldspar, such as granite,
whereas H may contain acidic rocks poor in K-feldspar.
This interpretation agrees well with the geologic map.
There are several small regions like J with very high
values of MI. Values of 0.89 to 0.90 indicate intermediate to
mafic silicate rock composition. The presence of tremolite in
some of the regions in J has been confirmed at the field andis consistent with the remote-sensing assessment. Also,
several thin layers represented by K are expected to be
relatively mafic. The region I has relatively high MI
values, indicating relatively low SiO2 contents compared to
massive units such as G and H. It is not certain if the
high-frequency textural features in the CI and MI images at
region I are topographic artifacts, or if they reflect the
complicated distribution of carbonate and silicate minerals
there.
The joint analysis of the different mineral indices applied
to Fig. 7e revealed areas having MI values of 0.80.9 that
subdivided the region F, with relatively high QI values,
Fig. 7 (continued).
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into two sub-regions. The eastern part in the lower
Proterozoic sequence (Pu1) seems to be siliceous, and the
western part consist of upper Proterozoic sequences (Pu3,
Pu4, Pw1 and Pw2) seems to be silicate rocks with lower
SiO2 content.
The latest formation of Proterozoic (Pw3) in the south-
western part of the study area, around Quartzose Peak (Fig.3a), is indicated to be quartzose or siliceous rocks, with red
pixels (QI > 1.05) or dark red pixels (QI>1.04). A part of the
region near Dingo Hill (Fig. 3a) appears to be mica-rich,
from high values of OHIa and QI. These pixels are pink in
Fig. 3e. Most of the other regions in Pw3 seem to be silicate
rocks with relatively high SiO2 content. Comparing the
images of the indices in and around the detected altered
regions shows that some areas appear from QI values to be
quartz-rich, but the remote-sensing indices alone are not
sufficient to determine whether the quartz is from source
rock or generated by hydrothermal silicification processes.
3.3. Xigaze study area
The study area is located on the Xigaze segment of
Yarlung Zangbo ophiolite belt, southern Tibet, China, from
29-00Vto 29-20VN and from 88-45Vto 89-30VE. The elevation
of this area ranges from 3700 to 5000 m asl. Xigaze has a
warm, semi-arid monsoon highland climate and vegetations
are sparsely distributed along the river valleys. Short grasses
sparsely cover the mountain regions. Two ASTER images of
the Xigaze area were analyzed. The image of the western part
of the study area was acquired on December 13, 2001; the
image of the eastern part was acquired on November 1, 2000.
Fig. 8a shows the compiled geological map (Wang et al.,
1984) overlaid on the mosaicked ASTER VNIR false-color
images. Precipitable water at the time of the ASTER data
acquisition is estimated from archived NCEP Reanalysis data
to have been nearly 0 kg/m2 for the western scene, and 3 kg/
m2 for the eastern scene. The Xigaze ophiolite represents a
peculiar oceanic lithosphere, comprising from north (top) to
south (bottom) marine sediments in stratigraphic contact over
pillow lavas or lava flows, to fresh harzburgites and
lherzolites (Nicolas et al., 1981). It is bounded by Upper
Cretaceous flysch (K2) in the north and by Upper Triassic
flysch (T3) or Upper Jurassic Lower Cretaceous abyssal
sediments and basic lava (J3 K1) in the south. The J3K1sequence along the boundary with ultramafic unit partly
consists of radiolarian cherts.
The labels on the mosaicked color-composite image of
the indices (Fig. 8b) together with the MI image scaled 0.85
(black) to 0.95 (white) (Fig. 8c) show locations of features
in the discussion below. QI values >1.05 characterize pixels
showing the outcrop in T3. These appear red and are labeled
A in Fig. 8c. The high QI values indicate almost pure
quartz rock. The QI values around the outcrop itself are
lower, which from the index values nevertheless appears to
be silicate. The region K2 (B) shows many bright and
dark small flecks in the CI image, and small color patches inthe color-composite image (Fig. 8b). Further investigation is
necessary to understand the complicated lithologic informa-
tion represented here. Alternatively, the pattern may result
from some kind of topographic artifact. Comparing the MI
image to the VNIR image indicates that most of the outcrops
in the northern part in K2 have relatively high values of MI,
indicating high mafic contents. Probably the source of these
sedimentary rocks is the nearby maficultramafic rocks.
Regions in the ophiolitic belt (C) shown as white in
Fig. 8c have MI values > 0.97 and correlate well to the
mapped ultramafic rocks (Fig. 8a). Some of the ultramafic
regions (D) in the geological map have lower values ofMI. In part of one of the westernmost regions D (Fig. 8a),
possible carbonate rocks appear yellow (CI > 1.045) in Fig.
8c. This occurrence is not explained in the published
geological map. Region E, which has MI values lower
than for ultramafic rocks but high enough (MI>0.9) for us
to expect mafic rock compositions, agrees well with the
distribution of mafic rocks in the geological map. A part of
region E has relatively high CI values (>1.04) indicated
as dark yellow in Fig. 8c. We interpret this to indicate
carbonate content. This possibly reflects the carbonate
concentrations in pores in the basalt rocks occurring in
E that we observed in the field. There are several
ultramafic or mafic layers detected in the MI index image.
Some, labeled F, are not described in the published
geological map. The regions of radiolarian cherts in J3K1have been identified as units with QI>1.035, the pixels of
which appear dark red or red in Fig. 8c. These are labeled
G. The extent of the units may be grasped intuitively with
the color-composite image of the indices (Fig. 8b).
4. Discussion
The case studies reported here are at different elevations
and present a set of examples that demonstrate the stabilityof the mineral indices to temperature and atmospheric
changes. The stability of the indices, especially CI, to
temperature is accomplished by normalizing the radiance-at-
sensor data to a fixed temperature as described in Section
2.4. Analyses of the behavior of the indices with respect to
Fig. 8. (a) A compiled geological map overlaid on an ASTER VNIR false-color composite image of the Xigaze study area. Abbreviation of map units: T 3,
Upper Triassic rocks; J3 K1, Upper Jurassic to Lower Cretaceous rocks; K1, Lower Cretaceous rocks; K2, Upper Cretaceous rocks; E, Lower Tertiary rocks.
(b) Color-composite image of the indices: QI= red, CI= green, and MI= blue, linearly scaled to cover 99% of the histogram for each color. The alphabetic labels
indicate the targets of discussion in the text. (c) Pixels detected with the indices: red, quartzite (QI>1.05); dark red, siliceous rock (QI>1.035); yellow,
carbonate rock (CI> 1.045); dark yellow, possible carbonate rock (CI> 1.04). Display is of MI image with a fixed gray-scale range of 0.85 to 0.95.
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