[Geophysical Research Letters]
Supporting Information for
[In-situ optical measurements of Chang’E-3 landing site in Mare Imbrium: 1. Mineral
abundances inferred from spectral reflectance]
[Hao Zhang1*, Yazhou Yang1, Ye Yuan1, Weidong Jin1, Paul G. Lucey2, Meng-Hua Zhu3, Vadim
G. Kaydash4, Yuriy G. Shkuratov4, Kaichang Di5, Wenhui Wan5, Bin Xu5, Long Xiao1, Ziwei
Wang1, and Bin Xue6]
[1Planetary Science Institute, School of Earth Sciences, China University of Geosciences, Wuhan, China
2
Hawaii Institute of Geophysics and Planetology, University of Hawaii, Honolulu, USA
3
Space Science Institute, Macau University of Science and Technology, Taipa, Macau
4
Astronomical Institute of Kharkov V.N. Karazin National University, Kharkov, Ukraine;
5
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy
of Sciences, Beijing, China
6 Xi'an
Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China.
(*) Corresponding author: Hao Zhang, School of Earth Sciences, China University of Geosciences, 388 Lumo Road,
Hongshan District, Wuhan, China, 430074, um_zhanghao@yahoo.com
]
Contents of this file
Text S1 to S2
Figures S1 to S5
Tables S1 to S4
Introduction
This supplementary material includes the calibration of the VNIS spectra (Text S1), the
fitting metrics of the LUT and measurement spectra (Text S2), 5 figures and 4 tables.
Text S1. The calibration of the VNIS spectra:
In planetary remote sensing there are two ways to obtain the absolute reflectance
rs(i,e,α) of an airless planetary surface, where i, e, and α are, respectively, the angles of
incident zenith, viewing zenith, and phase. First, rs(i,e,α) can be obtained by dividing the
1
registered radiance from an area of the surface Is(i,e,α) to that from a calibrated nearLambertian etalon Ic(i,e,α) with known reflectance rc(i,e,α) within the spectral range of
interest,
Is
rc .
Ic
(S1)
Is
,
cosi  J( )S( )d
(S2)
rs 
In the second approach, rs is obtained as
rs 
where J() is the solar irradiance reaching the surface [Gueymard, 2004] and S() is the

normalized spectral response of the sensor, respectively. The preflight-measured CE3
VISNIR sensor spectral response S() is approximated by Gaussian functions centered at
each band’s center wavelength with varying full width at half maximum (FWHM).
In this work the reflectance defined above corresponds to the reflectance factor
[Hapke, 2012] or reflection coefficient [Shkuratov et al., 2011] defined elsewhere. Many
workers also use the radiance factor I/F to represent reflectance and the relationship
between I/F and the reflectance defined here is
I /F  rs cosi .
(S3)
Three out of the four VNIS measurements have the complete CMOS and SWIR
calibration files (Node E, 
Node N203 and Node N205) and one (Node S3) has its
calibration files missing completely (either no calibration was performed at all or the data
was lost during transmission). For Node S3, the calibrated radiance values are offset in
the CMOS-SWIR overlapping region. Although Node N203 has the complete CMOS and
SWIR calibration files, the calibrated reflectance values (Eq. (S1)) in the overlapping
CMOS-SWIR spectral region (900 to 945 nm) are offset. These are shown in Fig. S2.
2
Following suggestions by the payload team, the CMOS radiance values of the S3 and
N203 spectra were scaled to their corresponding SWIR values at the overlapping region
as the SWIR sensor was found to be more stable during preflight tests. For Node E and
Node N205, the 2 spectra with better quality, both the calibrated radiance values and
reflectance (obtained using Eq. (S1) or (S2)) are continuous at the overlapping CMOSSWIR region and the reflectance values obtained using the two approaches agree with
each other within 5%, as shown in Fig. S3. To be consistent, the reflectance values
presented in this work were all obtained using the 2nd approach (eq. (S2)). The
uncertainties in scaling the CMOS data to SWIR for Node S3 and Node N203 may not be
critically important in this work as the spectral analysis described in the main text uses
the continuum-removed spectra.
With the assumption that the directional part of lunar surface reflectance rs can be
separated into the Lommel-Seeliger (LS) function and a phase function f(,) that is
independent of the incident-viewing geometry as [Yokota et al., 2011]
rs (i,e, , ) 
0
cosi

f (, )  0  LS  f (, ) ,
4 cosi  cose
4
(S4)
where 0 is the single scattering albedo, the VNIS spectra can be photometrically
 RELAB configuration as,
corrected to the
rs (30,0,30, )  rs (i,e, ,  )
LS(30,0,30) f (30, )
.
LS(i,e,  )
f (, )
(S5)
In principal, Eq. (S5) should be applied to every band of the VNIS spectra to derive the
 configuration spectra. Since for CE3 data the phase function is only
“true” RELAB
available at 3 overlapping wavelengths approximately centered at 470, 540 and 640 nm
(Jin et al., 2015), we used f(30)/f() at 640 nm in Eq. (S5) to perform the correction for
3
the whole VNIS spectra. It should be noted that because of the possible presence of phase
reddening effect, the f(30)/f() value could be larger at shorter wavelengths and smaller
at longer wavelengths and hence the above simple scheme could somehow distort the
spectra. However, as shown below, our mineral abundance retrievals used the continuumremoved spectra between 750 and 1550 nm and thus the effects of possible spectral
distortion should be reduced. Also this simple scheme is the best we can do with the
available data.
Text S2. The fitting metrics of the mineral spectral LUT and measurement
To find the best match between the LUT and measurement, we used 4 selection
criterions: minimum absolute difference (ABS, eq. (S6)), normalized absolute difference
(NABS, eq. (S7)), centered pattern root mean square (CPRMS, eq. (S8)) [Taylor, 2001]
and the spectral angle mapper (SAM, eq. (S9)) given by
N
ABS   f n  rn ,
(S6)
n 1
N
f n rn
 ,
f
r

NABS  

1
CPRMS 
[( f  f )  (rn  r )]2 ,
N n 1 n
n 1
(S7)
N
(S8)
N

SAM 
f
r
n n
i1
N
,
N
(S9)
 f r
2
n
i1
2
n
i1
where fn, rn, f and r are the nth measurement data, nth model prediction, average of

measurement and average of model prediction of N discrete data points, respectively.


4
These methods are among the most frequently used fitting metrics in matching model
predictions and discrete measurement data points. For example, some of the methods
(ABS) concentrate more on absorption depth and some (NABS) concentrate more on
spectral shape. It was found that the CPRMS are SAM methods would give nearly
identical results and thus only one of them (SAM) is used to balance the weight. The
optimum matching results are shown in Fig. S4 and are summarized in Table S3. Based
on these 3 typical matching results the average and standard deviations are used as the
final matching results.
References for Supplementary Materials
Gueymard, C. A. (2004). The sun’s total and spectral irradiance for solar energy
applications
and
solar
radiation
models. Solar
energy, 76,
423-453.
doi:10.1016/j.solener.2003.08.039.
Yokota, Y., Matsunaga, T., Ohtake, M., Haruyama, J., Nakamura, R., Yamamoto, S., ...
& Mizutani, H. (2011). Lunar photometric properties at wavelengths 0.5–1.6 μm
acquired by SELENE Spectral Profiler and their dependency on local albedo and
latitudinal zones. Icarus, 215, 639-660.
Taylor, K. E. (2001). Summarizing multiple aspects of model performance in a single
diagram. Journal of Geophysical Research, 106, 7183-7192. DOI:10.1029/2000
JD900719.
5
Figure S1. The lunar surface with an area of roughly 13 by 13 cm imaged by the CMOS
camera at 635 nm (Node E). Among the 256 by 256 pixels in the whole imagery, those
surrounded by the circled area correspond to the one single pixel measured by the SWIR
detector. The contour plot of the phase angles of this image is also shown.
Figure S2. Reflectance spectra of 4 measurements obtained by using the solar irradiance
calibration method (Eq. (S2)).
6
Figure S3. Reflectance values obtained by using different calibration methods for Node
E and Node N205. A. Reflectance values. B. Relative differences in percentage. The
relative percentage is defined as (eq.(S1)-eq.(S2))/eq.(S1).
7
Figure S4. Comparisons of the best matched LUT spectra and CE3 data. Blue dots:
continuum—removed CE3 measurement, red line: minimum absolute difference (Eq.
(S3)), orange line: minimum normalized absolute difference (Eq. (S4)), green line:
spectral angle mapper (SAM). A, B, C and D are Node E, Node S3, Node N203 and
Node N205, respectively.
8
Figure S5. Comparisons of continuum-removed M3 spectra (blue dots) with the best
matched LUT spectra (line) by using the minimum absolute difference method (eq. (S4))
for 3 representative sites, C1 (upper), L (middle) and H (lower), as indicated in Fig. S4.
9
Table S1.
Data
Locations
Measurement Time
(Moon Coordinate)
(UTC)
Node E
(-19.508837, 44.119063)
Node S3
(-19.508858, 44.118693)
Node N203
(-19.509439, 44.118516)
Node N205
(-19.509961, 44.118639)
START_TIME = 2013-12-23T02:10:10.279Z
STOP_TIME = 2013-12-23T02:50:36.279Z
START_TIME = 2013-12-24T01:35:42.925Z
STOP_TIME = 2013-12-24T01:52:38.196Z
START_TIME = 2014-01-12T14:49:40.402Z
STOP_TIME = 2014-01-12T15:30:09.225Z
START_TIME = 2014-01-14T16:31:12.206Z
STOP_TIME = 2014-01-14T17:11:38.251Z
Table S1. Locations and measurement times of the 4 VNIS spectra. 2 APXS
measurements were also made at Node S3 and Node N205 and the results are
summarized in Table S3.
10
Data
Method
OLV
OPX
CPX
PLG
Node E
ABS
NABS
SAM
0.296
0.244
0.236
0.258
0.033
0.138
0.154
0.160
0.150
0.011
0.162
0.078
0.160
0.133
0.048
0.231
0.219
0.228
0.226
0.006
0.142
0.052
0.050
0.081
0.053
0.063
0.071
0.074
0.069
0.006
0.075
0.078
0.074
0.075
0.002
0.150
0.142
0.148
0.146
0.004
0.296
0.308
0.298
0.300
0.006
0.513
0.569
0.590
0.557
0.040
0.597
0.708
0.590
0.631
0.066
0.393
0.373
0.388
0.384
0.010
0.218
0.348
0.368
0.311
0.081
0.238
0.156
0.128
0.174
0.057
0.118
0.088
0.128
0.111
0.021
0.178
0.218
0.188
0.194
0.021
Average
Node S3
ABS
NABS
SAM
Average
Node N203
ABS
NABS
SAM
Average
Node N205
ABS
NABS
SAM
Average
i(°)
e(°)
α(°)
59.9
48.2
107.9
67.5
47.4
69.7
47.1
54.1
44.4
85.6
86.0
95.3
Table S2. Retrieved mineral weight percentage by comparing CE3 data and the mineral
look-up table data. ABS: by searching the minimum of absolute difference between LUT
and data; NABS: absolute difference of standard-deviation-normalized LUT and data;
SAM: spectral angle mapper. i: solar zenith angle; e: viewing zenith angle; α: phase
angle.
11
Data
Method
OLV
OPX
CPX
PLG
ABS
NABS
SAM
0.192
0
0.128
0.68
0.282
0
0.188
0.53
H
0.21
0
0.14
0.65
0.228
0
0.152
0.62
Average
0.045
0
0.03
0.075
ABS
0.038
0
0.342
0.62
NABS
0.033
0
0.297
0.67
L
SAM
0
0
0.22
0.78
0.024
0
0.286
0.69
Average
0.019
0
0.061
0.08
ABS
0.04
0
0.36
0.6
NABS
0.033
0
0.297
0.67
C
SAM
0.04
0
0.36
0.6
0.038
0
0.339
0.623
Average
0.004
0
0.032
0.035
Table S3. Retrieved mineral molar abundances by comparing M3 data and the mineral
look-up table data. ABS: by searching the minimum of absolute difference between LUT
and data; NABS: absolute difference of standard-deviation-normalized LUT and data;
SAM: spectral angle mapper. H, L, and C correspond to the 3 units indicated in Fig. 4.
12
Figure
Number
Fig. 1
Fig. 2
Fig. 4
Fig. S1
Data ID
CE3_BMYK_LCAM2955_SCI_N_20131214131003_20131214131003_0001_A.2A.
SP_2C_02_05208_N443_E3405 line33
M3G20090416T101921_V01_RFL.IMG
CE3_BMYK_VNISCD_SCI_N_20131223021010_20131223021010_0005_A.2B
CE3_BMYK_VNISSD_SCI_N_20131223021320_20131223021320_0005_A.2B
CE3_BMYK_VNISCD_SCI_N_20131224013542_20131224013542_0006_A.2B
CE3_BMYK_VNISSD_SCI_N_20131224013852_20131224013852_0006_A.2B
CE3_BMYK_VNISCD_SCI_N_20140112144940_20140112144940_0007_A.2B
CE3_BMYK_VNISSD_SCI_N_20140112145252_20140112145252_0007_A.2B
CE3_BMYK_VNISCD_SCI_N_20140114163112_20140114163112_0008_A.2B
CE3_BMYK_VNISSD_SCI_N_20140114163422_20140114163422_0008_A.2B
M3G20090416T101921_V01_RFL.IMG
CE3_BMYK_VNISCD_SCI_N_20131223021010_20131223021010_0005_A.2B
Table S4. The IDs for the data used in this work
13