International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Volume XXXVIII, Part 8, Kyoto Japan 2010
SUSPECTED PLUME IMPINGEMENT INFLUENCE ON BOARD CALIBRATION
SYSTEM OF TERRA/ASTER/VNIR INVESTIGATED THROUGH TREND ANALYSIS ON
BOARD CALIBRATION DATA
K.Arai a* , N. Ohgi b and H. Inada c
a
b
Dept. of Information Science, Saga University, 1 Honjo 840-8502 Japan, arai@is.saga-u.ac.jp
Japan Resources Observation System and Space Utilization Organization, 2-24-2 Nichibei Bldg, Hacchobori, Chuoku, Tokyo, 104-0032 Japan, nohgi@jaros.or.jp
c
NEC Corporation, 1-10 Nisshin-cho, Fuchu-shi, Tokyo 183-0036 Japan, h-inada@bx.jp.nec.com
Commission VIII, ICWG IV/VIII
KEY WORDS: Onboard calibration, Sensitivity degradation, Fuel consumption, Contamination model, ASTER/VNIR
ABSTRACT:
Trend analysis of Terra/ASTER/VNIR calibration data is made for finding possible causes for degradation of radiometric calibrat ion
coefficients. Two sets of photometers are equipped at just after the onboard calibration lamp and at just in front of optics en trance of
the mission instrument, VNIR. Unfortunately, the later was malfunctioned 300 days after the launch so that degradation of
calibration optics which is situated in between calibration lamp and VNIR optics entrance is not monitored after that. The trends of
calibration lamp response of VNIR within 300 days after the launch is very resemble to that of degradation of the later calibra tion
lamp so that it might be possible to say that one of the possible causes of degradation VNIR response would be common. That might
be a contamination at the optics entrance of VNIR which is later photo monitor is equipped due to plume impingement. From the
spectral dependency, particle size of plume impingement is estimated. Also, it is confirmed that extrapolated trend is very similar to
the onborad calibration data trend.
product [Thome, Arai et al., 2008]. Any electro-optical sensor
is expected to degrade once in orbit, and therefore requires a
mechanism to monitor the data’s radiometric quality over time.
Many sensors, including ASTER, employ onboard calibration
devices to evaluate temporal changes in the sensor responses.
Onboard calibrators in general, provide excellent temporal
sampling of the sensor’s radiometric behaviour over time. In
addition, the repeatability and precision of the onboard systems
allow use of these data in characterizing the sensor’s response
trends. Typical approaches for onboard calibration include
lamp-based, diffuser-based, and detector-based methods.
ASTER VNIR: Visible and Near Infrared Radiometer and
SWIR: Short Wave Infrared Radiometer use lamp-based
onboard calibrators. The specific design of the ASTER OBC is
described in the following section. Then the sensor’s response
trends and suspected influence due to plume impingement of
contamination of optics entrance of ASTER instrument is
followed by with some evidences. Finally, discussions and
concluding remarks are described.
1.INTRODUCTION
Almost all the solar reflection channels of mission instruments
onboard Earth observation satellite carry their own calibration
system to maintain consistency of the radiometric fidelity of the
instrument. Thus users may convert from the Digital Number,
DN to radiance taking the onboard calibration system derived
calibration coefficient into account. There are some reports on
the calibration issues which include the Marine Observation
Satellite-1 [Arai, 1988], Landsat-7 Enhanced Thematic Mapper
Plus [Barker, et al., 1999], SeaWiFS [Barnes, et al., 1999],
SPOT-1 and 2 [Gelleman, et al., 1993], Hyperion [Folkman, et
al., 1997], and POLDER [Hagolle, et al., 1999]. Onboard
calibrators cannot provide results of a higher accuracy than the
preflight laboratory calibration. This means that the accuracy of
the in-flight (absolute) calibration is inferior to the preflight
results. This is because the preflight calibration source is used
to calibrate the onboard calibrators. In addition, the uncertainty
of the onboard calibrator typically increases with time. Hence,
it makes good sense to include additional calibration
approaches that are independent of the preflight calibration.
Besides the normal and expected degradation of the onboard
calibrators, they also run the risk of failing or operating
improperly. Therefore, vicarious approaches are employed to
provide further checks on the sensor’s radiometric behavior.
2.CALIBERATION SYSTEM ONBOARD
TERRA/ASTER/VNIR
2.1Onboard calibration
As for the onboard calibration, given the understanding that the
orbiting sensor’s response will change over time, for instance,
the ASTER: Airborne Sensor for Thermal Emission and
Reflection calibration tem developed a methodology, based on
OBC: Onboard Calibration results, to update pre-flight RCCs:
Radiometric Calibration Coefficients that are input to generate
the Level-1B (radiometrically and geometrically corrected DN)
ASTER VNIR and SWIR channels use lamp-based onboard
calibrators for monitoring temporal changes in the sensor
responses.
Space restrictions aboard the Terra platform
disallow a solar-based calibration, and therefore, onboard
calibration is lamp-based. The VNIR and SWIR have two
onboard calibration lamps, lamp-A and lamp-B. Both are used
1057
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Volume XXXVIII, Part 8, Kyoto Japan 2010
periodically, and as a backup system. The VNIR calibration
lamp output is monitored by a silicon photo monitor, and is
guided to the calibration optics. The calibration optics output is
itself monitored by a similar photo monitor that illuminates a
portion of the VNIR aperture’s observation optics. Meanwhile,
the SWIR calibration assembly does not have a second silicon
photo monitor. In the pre-flight phase, the onboard calibrators
were well characterized with integration spheres calibrated with
fixed freezing point blackbodies of Zn (419.5K), Pb (327.5K)
and Sn (231.9K). This was accomplished by comparing the
VNIR and SWIR output derived from the integration sphere’s
illumination of the two sensors. The same comparison was
made by the calibration lamp’s (A and B) illumination of the
two sensors.
Next, the pre-flight gain and offset data (no
illumination) were determined. In addition, MTF: Modulation
Transfer Function was measured with slit light from a
collimator while stray light effect was measured with the
integration sphere illumination, which is blocked at the full
aperture of the VNIR and SWIR observation optics entrance.
The pre-flight calibration data also includes (1) the spectral
response, (2) out-of-band response, and (3) signal-to-noise ratio
measured with a double grating monochromator.
The VNIR has two onboard calibration halogen lamps (A and
B) as is shown in Fig.1.
and aft of the calibration optics to monitor the output of the
lamps as well as any possible degradation in the calibration
optics. Lamp output and photo monitor data are collected
every 33 days (primarily it was 16 days of the Terra orbital
revisit cycle plus one day = 17 days), and RCC are calculated
from the VNIR output taking into account the photo-monitor
output. The RCC values are normalized by the pre-flight data to
determine their final estimate. This procedure is the same for
the SWIR RCC calculation except that the SWIR OBC does not
include a photo monitor system at the lamp. Thus, only data
from a photo monitor that is aft of the calibration optics are
taken into account. The sources of VNIR and SWIR radiometric
calibration uncertainties are shown in Table 1.
Table 1 Uncertainty in the absolute responsivity for normal gain
mode of VNIR and SWIR at post launch phase
Uncertainty depends on the band (RSS of each band is 2.8, 3.9,
3.4, 5.2, 4.4, 3.9 for bands 4 to 9, respectively)
SWIR
Source of uncertainty
VNIR
Uncertainty
Uncertainty
(%)
(%)
1.5
0.7
Photomonitors sensitivity
change due to temperature
change
Degradation of photo1.0
2.0
monitors
Photo-monitor
output
0.4
0.5
measurements
Lamp radiance change due
2.0
0.5-0.6
to gravity shift
Radiometer
output
0.4
1.4-4.5
measurements
Lamp radiance change due
N/A
1.0-1.2
to temperature change
Others
(non-uniform
2.0
0.2
contamination)
Root Sum Square (RSS)
3.4
2.8-5.2
The uncertainty in the band-to-band response ratio is 2.3% with
the root sum square among 2.0% of the in-orbit lamp’s spectral
radiance changes. It registers 0.4% of the radiometer output
measurements, and 1.0% of the others. Uncertainty in the
detector-to-detector response ratio is 0.8% with the root sum
square among 0.6% of the integration sphere, 0.4% of the
radiometer output measurements, and 0.4% of the others. The
most significant uncertainty is contamination and lamp radiance
changes due to a gravity shift followed by photo-monitor
sensitivity variations due to temperature changes and
degradation.
The largest uncertainty is the radiometer output measurement
followed by the photo monitor degradation, and lamp radiance
dynamics due to temperature changes. Due to filter and detector
sensitivity changes in the short wave infrared region, the
uncertainty of the radiometer’s output measurements are not so
good, and vary by band. SWIR’s absence of an aft photo
monitor disallows monitoring the lamp output degradation, and
hence, uncertainty in that regard is greater than that of VNIR.
For the same reason, the uncertainty of the lamp radiance
dynamics due to temperature changes is added to the VNIR
uncertainty source. The influence due to non-uniform
contamination of SWIR is smaller than that of VNIR because
the SWIR wavelength coverage is longer than that of VNIR
(Similar particle size for the same contamination material is
assumed).
Fig.1 Onboard calibration system of the ASTER/VNIR
The light from these lamps is led to the VNIR optics via a set of
calibration optics. Filters and photo-monitors are located fore
1058
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Volume XXXVIII, Part 8, Kyoto Japan 2010
are similar, there are small biases, 1% for Band 1, -4% for Band
2 and -2% for Band 3, respectively as is indicated in Fig.3.
From these proto-flight model test data, and analyses derived
with the previous mission instrument data, VNIR OBC is
reliable at the 2% (1 sigma value) level while SWIR is at a 4%
level. Thus the following RCC determination method is adopted
The ASTER radiometric calibration coefficients are generated
via the OBC data. The first three months of ASTER operation
corresponded to the sensor activation and evaluation (A&E)
phase during which the OBC results alone were used to
determine the RCC. The OBC data have since been further
evaluated by a panel of radiometric scientists relative to the VC
results. The panel determined a set of trend equations used
until a subsequent calibration panel review. The panel also
determined the weightings used in the merging of the OBC and
VC results. The best estimates of the ASTER RCC are
publicized quarterly through newsletters, an Internet server, and
other means. The user may then modify results obtained using
the Level-1B product according to how large the difference is
between the OBC results and the OBC-merged-with-VC results.
The first panel meeting was held late during the A&E period to
determine the weights for OBC and VC as well as version 1.0
radiometric calibration coefficients.
ASTER’s current approach to determine the RCC for level-1
processing is as follows:
(1). Check for consistency between the halogen lamp system A
and B. (System A and B are turned on every 17 days),
(2). Check for inter-channel dependency to find out if all bands
within a telescope display similar tendencies
(3). Calculate RCC if both (1) and (2) are satisfied
(4). Calculate calibration coefficients based on cross-calibration
results if (1) and (2) are not satisfied
(5). Calculate calibration coefficients based on other vicarious
calibration data sets if (1) and (2) are not satisfied, and no
cross-calibration coefficients exist
Basically, RCC for level-1 processing is determined with the
current RCC, if the deviation of the current RCC is within a
range of the uncertainty, 2% for VNIR and 4% for SWIR in
comparison to the previous RCC. If the RCC trend shows
inconsistent behaviour, then cross calibration and vicarious
calibration are taken into account [Arai, 1994].
Fig.2 OBC RCC trends for Band 1(Blue), Band 2(Green) and
Band 3(Red)
Fig.3 OBC and vicarious RCC trends
Therefore, VNIR sensitivity degradation is confirmed with the
different two sources. VNIR sensitivity degradation can be
expressed with exponential function so that one of the possible
causes of the degradation is contamination. The other causes are
degradation of optical transparency of the calibration optics,
sensitivity degradation of photo-monitor, degradation of
photmonitor filter, etc.
2.2Onboard calibration trend
Fig.2 shows the RCC trends for VNIR. The RCC were
changed relatively rapidly in the early stage of the launch, and
is changed gradually for the time being. These are
approximated with an exponential function with a bias and a
negative coefficient. If the trend is approximated with the
function of RCC = B exp (-At) + C, then A, B, and C equal the
following values:
VNIR
2.3 Photo-monitor output trend
As is shown in Fig.1, VNIR has two photo-monitors, one (PD2)
is set at lamp output and the other one (PD1) is set at the optics
entrance, just in front of the collecting mirror.
Band-1: A = 0.00190, B = 0.360, C = 0.735
Band-2: A = 0.00168, B = 0.282, C = 0.807
Band-3: A = 0.00150, B = 0.216, C = 0.860
During 2500 days after the launch, VNIR OBC RCC were
degraded about 10% for Band-3, 16% for Band-2 and 23 % for
Band-1, respectively while SWIR OBC RCC were degraded
approximately 2.0 to 3.5% depending on bands. These trends
are very similar to the vicarious calibration derived RCC, and
also look similar to the OBC RCC trend of the Optical Sensor
onboard the JERS-1 satellite, a legacy precursor to the ASTER
instrument.
Each of the VNIR bands is shown, as are the onboard calibrator
results for these bands in a fashion similar to that shown in
Fig.2. On the other hand, Fig.3 shows vicarious calibration
trend. Although both onboard and vicarious calibration trends
Fig.4 Photomonitor output for both calibration system A and B
of PD1 and PD2.
1059
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Volume XXXVIII, Part 8, Kyoto Japan 2010
with the assumption that the size distribution is followed by the
power law as well as the accumulated number of particles is
normalized by one. Fig.8 shows the estimated size distribution.
The size distribution estimation has not been validated yet.
Although PD1 output shows scale-off (under flow) at around
370 days after launch as is shown in Fig.4, the degradation of
the degradation ratio shows almost same trend as OBC and
vicarious RCC trends.
Also PD2 output shows stable lamp illumination so that one of
possible causes for the sensitivity degradation is contamination
at the optics entrance because the calibration optics is
composed with browning lenses (less degradation of
transparency due to radiation from solar flare).
From the PD1 output data, approximated exponential function
is estimated with least square method. The degradation rate is
confirmed to be almost same as OBC and vicarious RCC trends
as is shown in Fig.5.
㪄㪋㪅㪊
㪄㪋㪅㪊㪉
㪄㪋㪅㪊㪋
㪄㪋㪅㪊㪍
㪄㫃㫅㩿㪩㪚㪚㪀
㪄㪋㪅㪊㪏
㪄㪋㪅㪋
㪄㪋㪅㪋㪉
㪄㪋㪅㪋㪋
㪄㪋㪅㪋㪍
㪄㪋㪅㪋㪏
㫐㩷㪔㩷㪄㪇㪅㪋㪉㪐㪎㫏㩷㪄㩷㪈㪅㪍㪈㪌㪏
㪄㪋㪅㪌
㪌㪅㪇㪇
㪄㪋㪅㪌㪉
㪍㪅㪊㪇
㪋㪅㪇㪇
㪈㪘
㪉㪘
㪈㪙
㪉㪙
㪘㫇㫇㫉㫆㫏㪅㪜㫏㫇㪅
㪊㪅㪇㪇
㪉㪅㪇㪇
㪍㪅㪊㪌
㪍㪅㪋㪇
㪍㪅㪋㪌
㪍㪅㪌㪇
㪍㪅㪌㪌
㫃㫅㩿㪮㪸㫍㪼㫃㪼㫅㪾㫋㪿㪀
㪍㪅㪍㪇
㪍㪅㪍㪌
㪍㪅㪎㪇
㪍㪅㪎㪌
Fig.7 Spectral characteristics of RCC and its linearly
approximated function.
㪈㪅㪇㪇
㫐㩷㪔㩷㪍㪼㪄㪇㪅㪇㪇㪎㪈㫏
㪇
㪌㪇
㪈㪇㪇
㪈㪌㪇
㪉㪇㪇
㪉㪌㪇
㪛㪸㫐㫊㩷㪸㪽㫋㪼㫉㩷㫃㪸㫌㫅㪺㪿
㪈㪅㪜㪂㪇㪎
㪊㪇㪇
㪊㪌㪇
㪋㪇㪇
㪈㪅㪜㪂㪇㪍
㪫㪿㪼㩷㫅㫌㫄㪹㪼㫉㩷㫆㪽㩷㫇㪸㫉㫋㫀㪺㫃㪼㫊
㪇㪅㪇㪇
Fig.5 Approximated exponential function of PD1 output
together with the other photomonitor output trends.
OBC RCC trends with reference to the calibration systems
(Lamp A and B as well as photo-monitor PD1 and 2) are shown
in Fig.6. The first three lines are for Band 3, 2 and 1,
respectively, of RCC ranges from 105 (just after the launch) to
76 at around 3600 days after launch while the last four lines are
for photo-monitor output. As is mentioned before, photomonitor PD1 for both lamp A and B were in scale off at 370
days after launch so that PD1 (lamp A and B) trend were
extrapolated by the exponential function with coefficients
determined from the PD1 output data of the first 370 days. As is
shown in Fig.6, the coefficients of exponential function of RCC
trend is almost same as that of extrapolated function of PD1.
Thus it might be concluded that one of the possible causes of
the RCC degradation would be contamination at the optics
entrance of VNIR due to plume impingement.
㪈㪌㪇㪇
㪩㪚㪚㩷㪸㫅㪻㩷㫇㪿㫆㫋㫆㫄㫆㫅㫀㫋㫆㫉㩷㫆㫌㫋㫇㫌㫋㩿㪭㪀
㪇㪅㪈㪇㪇
㪈㪅㪇㪇㪇
㪈㪇㪅㪇㪇㪇
Another evidence of the causes of RCC degradation is the
relation between fuel consumption and RCC degradation. Fig.9
shows the fuel consumption of Terra satellite which carries
ASTER/VNIR. Fig.9 also shows approximated function of the
fuel consumption together with approximated function of RCC
degradation. As is well known that the fuel consumption in just
after launch is relatively large, there is bias between the two
approximated functions of fuel consumption and RCC
degradation. Both functions, however, show almost same trend.
㪊㪌㪇
㪄㪉㪇
㪈㪇㪇㪇
㪈㪅㪜㪂㪇㪇
2.4Fuel consumption and RCC trend
㪇
㪌㪇㪇
㪈㪅㪜㪂㪇㪈
Fig.8 Estimated size distribution of plume impingement that is
one of causes of the RCC degradation
㫇㪻㪈㪸㩿㪜㫏㫋㪼㫉㫇㫆㫃㪸㫋㫀㫆㫅㪀
㫇㪻㪉㪸
㫇㪻㪈㪹㩿㪜㫏㫋㪼㫉㫇㫆㫃㪸㫋㫀㫆㫅㪀
㫇㪻㪉㪹
㪹㪸㫅㪻㪈
㪹㪸㫅㪻㪉
㪹㪸㫅㪻㪊㪥
㪇
㪈㪅㪜㪂㪇㪉
㫉㪸㪻㫀㫌㫊㩿㫄㫀㪺㫉㫆㫄㪼㫋㪼㫉㪀
㪏㪇
㪉㪇
㪈㪅㪜㪂㪇㪊
㪈㪅㪜㪄㪇㪉
㪇㪅㪇㪈㪇
㪈㪇㪇
㪋㪇
㪈㪅㪜㪂㪇㪋
㪈㪅㪜㪄㪇㪈
㪈㪉㪇
㪍㪇
㪈㪅㪜㪂㪇㪌
㪉㪇㪇㪇
㪉㪌㪇㪇
㪊㪇㪇㪇
㪊㪌㪇㪇
㪋㪇㪇㪇
㪛㪸㫐㫊㩷㪸㪽㫋㪼㫉㩷㫃㪸㫌㫅㪺㪿
Fig.6 OBC RCC trend together with photo-monitor output trend.
From the wavelength dependency of OBC RCC trend, it is
possible to estimate size distribution if it is assumed that plume
impingement is one of possible causes of the RCC degradation.
Fig.7 shows wavelength dependency of the RCC degradations.
From this spectral dependency, size distribution is estimated
㪝㫌㪼㫃㩷㪺㫆㫅㫊㫌㫄㫇㫋㫀㫆㫅㩷㪸㫅㪻㩷㪸㫇㫇㫉㫆㫏㪅㩷㪽㫌㫅㪺㫋㫀㫆㫅㩷㫎㫀㫋㪿
㪼㫏㫇㫆㫅㪼㫋㫀㪸㫃㩷㪽㫌㫅㪺㫋㫀㫆㫅
㪧㪿㫆㫋㫆㫄㫆㫅㫀㫋㫆㫉㩷㫆㫌㫋㫇㫆㫌㫋㩿㪭㪀
㪍㪅㪇㪇
㪊㪊㪇
㪊㪈㪇
㪝㫌㪼㫃㩷㪺㫆㫄㫊㫌㫄㫇㫋㫀㫆㫅
㪊㪋㪇㪜㫏㫇㩿㪄㪇㪅㪇㪇㪇㪉㫏㪀
㪜㫏㫇㫆㫅㪼㫋㫀㪸㫃㩷㪘㫇㫇㫉㫆㫏㪅
㪉㪐㪇
㪉㪎㪇
㪉㪌㪇
㪉㪊㪇
㪉㪈㪇
㪄㪇㪅㪇㪇㪇㪉㫏
㫐㩷㪔㩷㪊㪇㪉㪅㪋㪋㪼
㪉
㪩 㩷㪔㩷㪇㪅㪐㪍㪊㪊
㪈㪐㪇
㪈㪎㪇
㪈㪌㪇
㪇
㪌㪇㪇
㪈㪇㪇㪇
㪈㪌㪇㪇
㪉㪇㪇㪇
㪉㪌㪇㪇
㪊㪇㪇㪇
㪊㪌㪇㪇
㪋㪇㪇㪇
㪛㪸㫐㫊㩷㪸㪽㫋㪼㫉㩷㫃㪸㫌㫅㪺㪿㪃㩷㫏
Fig.9 The relation between fuel consumption and RCC
degradation.
1060
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Volume XXXVIII, Part 8, Kyoto Japan 2010
Fig.10 also shows the OBC RCC trends, with the reference to
the two calibration systems, Lamp A and B as well as PD2, for
Band 1, 2 and 3. Fig.10 also shows the fuel consumption and its
approximated function with exponential function. It may say
that theses show almost same trend.
㪩㪚㪚㪃㩷㪸㫇㫇㫉㫆㫏㫀㫄㪸㫋㪼㪻㩷㪽㫌㫅㪺㫋㫀㫆㫅㩷㪸㫅㪻㩷㪽㫌㪼㫃
㪺㫆㫅㫊㫌㫄㫇㫋㫀㫆㫅
㪈
㪇㪅㪎㪂㪇㪅㪊㪜㫏㫇㩿㪄㪇㪅㪇㪇㪈㫏㪀
㪘㪹㪈㪉㪌㪇㪇
㪘㪹㪈㪉㪌㪇㪈
㪘㪹㪉㪉㪌㪇㪇
㪘㪹㪉㪉㪌㪇㪈
㪘㪹㪊㪉㪌㪇㪇
㪘㪹㪊㪉㪌㪇㪈
㪙㪹㪈㪉㪌㪇㪇
㪙㪹㪈㪉㪌㪇㪈
㪙㪹㪉㪉㪌㪇㪇
㪙㪹㪉㪉㪌㪇㪈
㪙㪹㪊㪉㪌㪇㪇
㪙㪹㪊㪉㪌㪇㪈
㪝㫌㪼㫃
㪇㪅㪐㪌
㪇㪅㪐
㪇㪅㪏㪌
㪇㪅㪏
㪇㪅㪎㪌
㪇㪅㪎
㪇
㪈㪇㪇㪇
㪉㪇㪇㪇
㪊㪇㪇㪇
㪛㪸㫐㫊㩷㪸㪽㫋㪼㫉㩷㫃㪸㫌㫅㪺㪿㪃㩷㫏
Fig.12 Detector temperature for Bands 1,2,3.
As is shown in Fig.11 and 12, dark signal (Output signal when
no input from the VNIR optics entrance (Night time
observation)) and detector temperature is very stable so that it
may say that detector sensitivity is stable enough. Consequently,
optics transparency would be a most suspected cause of the
RCC (sensitivity) degradation due to plume impingement by
hydrogen from the thrusters of Terra satellite because the RCC
trend shows very resemble trend of fuel consumption.
㪋㪇㪇㪇
Fig.10 Relations between OBC RCC trend and fuel
consumption as well as the approximated function of fuel
consumption.
㪙㪸㫅㪻㩷㪈㩷㪛㪸㫉㫂㩷㩿㫇㫀㫏㪔㪉㪌㪇㪇㪃㪉㪌㪇㪈㪀
3.CONCLUDING REMARKS AND DISCUSSIONS
㪍㪅㪇㪇
It may concluded the followings,
(1)
Similar trend is observed between OBC/RCC and
photomonitor1 output when the photomonitor1 output
trend is extrapolated for 3600 days, original trend is
terminated with a 360 days though
(2)
Assumption of which RCC degradation is caused by
contamination of optics entrance of VNIR due to
plume impingement from gas jet for attitude control
seems to be correct
(3)
Using wavelength dependency of RCC degradation,
size distribution is estimated with the relation between
ln(wavelength) and ln(RCC degradation) based on
power low distribution function. It has to be validated
though.
Consequently, optics transparency would be a most suspected
cause of the RCC (sensitivity) degradation due to plume
impingement by hydrogen from the thrusters of Terra satellite
because the RCC trend shows very resemble trend of fuel
consumption.
㪌㪅㪇㪇
㪉㪌㪇㪇㪄㪣㫆㫎
㪉㪌㪇㪈㪄㪣㫆㫎
㪉㪌㪇㪇㪄㪥㫆㫉㫄㪸㫃
㪉㪌㪇㪈㪄㪥㫆㫉㫄㪸㫃
㪉㪌㪇㪇㪄㪟㫀㪾㪿
㪉㪌㪇㪈㪄㪟㫀㪾㪿
㪛㪥
㪋㪅㪇㪇
㪊㪅㪇㪇
㪉㪅㪇㪇
㪈㪅㪇㪇
㪇㪅㪇㪇
㪈㪐㪐㪐㪆㪈㪉㪆㪍
㪉㪇㪇㪈㪆㪋㪆㪈㪐
㪉㪇㪇㪉㪆㪐㪆㪈
㪉㪇㪇㪋㪆㪈㪆㪈㪋 㪉㪇㪇㪌㪆㪌㪆㪉㪏 㪉㪇㪇㪍㪆㪈㪇㪆㪈㪇 㪉㪇㪇㪏㪆㪉㪆㪉㪉
㪉㪇㪇㪐㪆㪎㪆㪍
㪉㪇㪈㪇㪆㪈㪈㪆㪈㪏 㪉㪇㪈㪉㪆㪋㪆㪈
㪙㪸㫅㪻㩷㪉㩷㪛㪸㫉㫂㩷㩿㫇㫀㫏㪔㪉㪌㪇㪇㪃㪉㪌㪇㪈㪀
㪌㪅㪇㪇
㪋㪅㪇㪇
㪉㪌㪇㪇㪄㪣㫆㫎
㪉㪌㪇㪈㪄㪣㫆㫎
㪉㪌㪇㪇㪄㪥㫆㫉㫄㪸㫃
㪉㪌㪇㪈㪄㪥㫆㫉㫄㪸㫃
㪉㪌㪇㪇㪄㪟㫀㪾㪿
㪉㪌㪇㪈㪄㪟㫀㪾㪿
㪛㪥
㪊㪅㪇㪇
㪉㪅㪇㪇
4.ACKNOWLEDGEMENTS
㪈㪅㪇㪇
㪇㪅㪇㪇
㪈㪐㪐㪐㪆㪈㪉㪆㪍
㪉㪇㪇㪈㪆㪋㪆㪈㪐
㪉㪇㪇㪉㪆㪐㪆㪈
㪉㪇㪇㪋㪆㪈㪆㪈㪋 㪉㪇㪇㪌㪆㪌㪆㪉㪏 㪉㪇㪇㪍㪆㪈㪇㪆㪈㪇 㪉㪇㪇㪏㪆㪉㪆㪉㪉
㪉㪇㪇㪐㪆㪎㪆㪍
The authors would like to express special thanks to Dr. Fujisada
(SILC), Dr. Ono (AIST), Dr. Sakuma (AIST), Dr. Tsuchida
(AIST), Dr. Iwasaki (University of Tokyo), Dr. Slater (formally
worked for University of Arizona), Dr. Biggar (University of
Arizona), Dr. Thome (NASA/GSFC) and Dr. Keiffer (formally
worked for USGS) for all their help and valuable discussions.
㪉㪇㪈㪇㪆㪈㪈㪆㪈㪏 㪉㪇㪈㪉㪆㪋㪆㪈
㪙㪸㫅㪻㩷㪊㪥㩷㪛㪸㫉㫂㩷㩿㫇㫀㫏㪔㪉㪌㪇㪇㪃㪉㪌㪇㪈㪀
㪈㪏㪅㪇㪇
㪈㪎㪅㪇㪇
㪈㪍㪅㪇㪇
㪈㪌㪅㪇㪇
㪈㪋㪅㪇㪇
㪉㪌㪇㪇㪄㪣㫆㫎
㪉㪌㪇㪈㪄㪣㫆㫎
㪉㪌㪇㪇㪄㪥㫆㫉㫄㪸㫃
㪉㪌㪇㪈㪄㪥㫆㫉㫄㪸㫃
㪉㪌㪇㪇㪄㪟㫀㪾㪿
㪉㪌㪇㪈㪄㪟㫀㪾㪿
㪈㪊㪅㪇㪇
㪈㪉㪅㪇㪇
㪈㪈㪅㪇㪇
㪛㪥
㪈㪇㪅㪇㪇
References
㪐㪅㪇㪇
㪏㪅㪇㪇
Arai K., Preliminary assessment of radiometric accuracy for
MOS-1 sensors, International Journal of Remote Sensing, 9,
1, 5-12, 1988.
Arai, K., In-flight test site cross calibration between mission
instruments onboard same platform, Advances in Space
Research, 19, 9, 1317-1328, 1997.
Barker, J.L., S.K. Dolan, et al., Landsat-7 mission and early
results, SPIE, 3870, 299-311, 1999.
㪎㪅㪇㪇
㪍㪅㪇㪇
㪌㪅㪇㪇
㪋㪅㪇㪇
㪊㪅㪇㪇
㪉㪅㪇㪇
㪈㪅㪇㪇
㪇㪅㪇㪇
㪈㪐㪐㪐㪆㪈㪉㪆㪍 㪉㪇㪇㪈㪆㪋㪆㪈㪐
㪉㪇㪇㪉㪆㪐㪆㪈
㪉㪇㪇㪋㪆㪈㪆㪈㪋 㪉㪇㪇㪌㪆㪌㪆㪉㪏 㪉㪇㪇㪍㪆㪈㪇㪆㪈㪇 㪉㪇㪇㪏㪆㪉㪆㪉㪉
㪉㪇㪇㪐㪆㪎㪆㪍 㪉㪇㪈㪇㪆㪈㪈㪆㪈㪏 㪉㪇㪈㪉㪆㪋㪆㪈
Fig.11 Dark signals for Bands 1(Top),2(Middle),3(Bottom)
1061
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Volume XXXVIII, Part 8, Kyoto Japan 2010
Barnes, R.A., E.E.Eplee, et al., Changes in the radiometric
sensitivity of SeaWiFS determined from lunar and solar
based measurements, Applied Optics, 38, 4649-4664, 1999.
Gellman, D.I., S.F. Biggar, et al., Review of SPOT-1 and 2
calibrations at White Sands from launch to the present, Proc.
SPIE, Conf.No.1938, 118-125, 1993.
Hagolle, O., P.Galoub, et al., Results of POLDER in-flight
calibration, IEEE Trans. On Geoscience and Remote
Sensing, 37, 1550-1566, 1999.
Herman B.M. and S. R. Browning, A numerical solution to the
equation of radiative transfer, J. Atmos. Sci., 22:559566, 1965.
Moran M.S., R. D. Jackson, G. F. Hart, P. N. Slater, R. J.
Bartell, S. F. Biggar, D. I. Gellman, and R. P. Santer,
"Obtaining surface reflectance factors from
atmospheric and view angle corrected SPOT-1 HRV
data," Rem. Sens. Env., vol. 32, pp. 203-214, 1990.
Moran M.S., M. S., R. D. Jackson, P. N. Slater, and P. M.
Teillet, "Evaluation of simplified procedures for
retrieval of land surface reflectance factors from
satellite sensor output," Remote Sens. Environ., vol.
41, pp. 169-184, 1992.
Ono.A., F.Sakuma, K.Arai, et al., Pre-flight and Inflight
Calibration for ASTER, Journal of Atmospheric and Ocean
Technology, Vol.13, No.2, pp.321-335, Apr.,1996.
Slater P., K.Thome, A.Ono, F.Sakuma, K.Arai, et al.,
Radiometric Calibration of ASTER, Journal of Remote
Sensing Society of Japan, Vol.15, No.2, pp.16-23, June
1995.
Thome, K., K. Arai, S.Tsuchida, S.Biggar, ASTER preflight
and in-flight calibration and validation of level 2 products,
IEEE Trans. on Geoscience and Remote Sensing, 36, 4,
1999.
1062