Ninomiya Cudahy[1]

7/28/2019 Ninomiya Cudahy[1]

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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.

Y. Ninomiya et al. / Remote Sensing of Environment 99 (2005) 127139 129


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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


Fig. 4. The Mafic Index (MI) calculated on simulated radiance-at-sensor

data by atmospheric water-vapor content (kg/m2) assigned in MODTRAN


Y. Ninomiya et al. / Remote Sensing of Environment 99 (2005) 127139130


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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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