During the 3.5-year operation of GOSAT (Greenhouse gases Observing SATellite), NIES GOSAT DHF (GOSAT Data
Handling Facility of National Institute for Environmental Studies) has been producing some standard products from the
data of TANSO-CAI (TANSO: Thermal And Near-infrared Sensor for carbon Observation; CAI: Cloud and Aerosol Imager) and TANSO-FTS (Fourier Transform Spectrometer). The standard data products of CAI Level 1B/1B+, FTS
Level 2 SWIR (column amount of CO2 and CH4), FTS Level 2 TIR (profiles of CO2 and CH4 concentration), CAI Level
2 (cloud flag), FTS Level 3 (global map of XCO2, XCH4), and CAI Level 3 (global radiance and global reflectance) have
been provided to general users. In addition, CAI Level 3 NDVI (Normalized Difference Vegetation Indices) and FTS Level 4A (flux of CO2) are released to GOSAT RA (Research Announcement) researchers and Model Group RA users,
respectively. Since the FTS Level 2 SWIR data have been accumulated more than three years, global distribution and the timely
changes of greenhouse gases are observed. In 2012, the version up of FTS Level 1B and FTS Level 2 SWIR has been carried out and the data quality of the new version has been significantly improved.
During the 2.5 year operation of GOSAT (Greenhouse gases Observing SATellite), NIES GOSAT DHF (GOSAT Data
Handling Facility of National Institute for Environmental Studies) has been producing CAI Level 1B and 1B+, FTS
Level 2 SWIR (column amount of CO2 and CH4), CAI Level 2 (cloud flag ), FTS Level 3 products (global map of XCO2,
XCH4,) and CAI Level 3 (global radiance and global reflectance), receiving FTS Level 1A/1B, and CAI Level 1A data
from JAXA (FTS: Fourier Transform Spectrometer; CAI: Cloud and Aerosol Imager, JAXA: Japan Aerospace
eXploration Agency). In addition, FTS Level 2 TIR are released to RA users. FTS Level 3 TIR, and Level 4A and 4B
products (emission/absorption and 3D global distribution of CO2) will be released in the near future..
Since the FTS Level 2 SWIR data have been accumulated more than 2.5 years, global trends can be observed, while the
validation results show negative bias of 2 to 3 % for CO2 and negative bias of 1 to 2 % for CH4. A comparison with the
results by different algorithms is also conducted.
All the mentioned data products are distributed through a website, the GOSAT User Interface Gateway (GUIG), and
users of the products include the researchers responded to the three Research Announcements (RA) and general users
(GU). Number of the RA users exceeds 100 and that for GU exceeds 1100.
KEYWORDS: 3D image processing, Visualization, 3D metrology, Biomedical optics, Information visualization, Standards development, 3D visualizations, Cameras, Electrocardiography, Computer graphics
The present study investigates whether VIMS, which can be induced in 2D images, is affected by stereoscopic
presentation. To do this, we conducted an experiment to measure the effects psychologically and physiologically.
Visual stimulus was computer graphics that simulates traveling along streets with additional pitch and roll motion for 10
minutes. The stimulus were presented as either stereoscopic, "3D", images or "2D" images. Before/after and during
each trial, psychological and physiological measurements for biomedical effects were conducted. As results,
psychological measurements indicate effects of stereoscopic presentations on VIMS. First, subjective score of comfort
level measured every one minute significantly decreased to uncomfortable level in the 3D than in the 2D condition.
Second, subscore of "Nausea" of Simulator Sickness Questionnaire significantly higher in the 3D than in the 2D
condition, while the other subscores and the total score also showed the similar tendency. Moreover, physiological
measurements also indicate effects of 3D presentations on VIMS. The LF/HF ratio, which is the index of sympathetic
nerve activity, clearly increased more in the 3D than in the 2D condition. We conclude that stereoscopic presentation
enhances biomedical effects of VIMS. We speculate that stereoscopic images can be efficient reference of spatial
orientation.
KEYWORDS: Fourier transforms, Carbon dioxide, Data processing, Short wave infrared radiation, Clouds, Aerosols, Data archive systems, Calibration, Data modeling, Gases
After the 1.5 year operation of GOSAT (Greenhouse gases Observing SATellite), NIES GOSAT DHF
(GOSAT Data Handling Facility of National Institute for Environmental Studies) has been producing CAI
Level 1B and 1B+, FTS/CAI Level 2 and FTS/CAI Level 3 products, receiving FTS Level 1A/1B, and CAI
Level 1A data from JAXA ( FTS: Fourier Transform Spectrometer; CAI: Cloud and Aerosol Imager; JAXA:
Japan Aerospace Exploration Agency).
In addition to the higher level data processing, GOSAT DHF has several additional roles 1) observation
request collection from users and their submission to JAXA 2) Data archive and 3) Data Distribution.
After the calibration and preliminary validation, processed data are distributed to RA researchers at first stage.
Then, after the validation, they are distributed to General users. All the distribution is through GOSAT User
Interface Gateway (GUIG). As of May of 2010, total number of user registration exceeds 800, and a large
number of products are distributed both to the RA researchers and to General Users.
At this moment, validation indicates that the FTS L2 SWIR CO2 and CH4 data show slightly lower values
than validation results. In addition, very high XCO2 values, which seemed caused by aerosol, appeared on
some desert area. But, further improvement of the algorithm was conducted as version 01.XX of FTS L2
products. Preliminary FTS TIR L2 processing is being conducted and TIR processing is starting.
In addition to the L2 products, some Level 3 products are going to be released: FTS L3 global distribution of
CO2 and CH4, and CAI L3 global radiance distribution.
KEYWORDS: Fourier transforms, Data processing, Short wave infrared radiation, Clouds, Carbon dioxide, Aerosols, Data archive systems, Data modeling, Satellites, Calibration
After the 1.5 year operation of GOSAT (Greenhouse gases Observing SATellite), NIES GOSAT DHF (GOSAT Data
Handling Facility of National Institute for Environmental Studies) has been producing CAI Level 1B and 1B+, FTS/CAI
Level 2, and FTS/CAI Level 3 products, receiving FTS Level 1A/1B and CAI Level 1A data from JAXA (FTS: Fourier
Transform Spectrometer; CAI: Cloud and Aerosol Imager; JAXA: Japan Aerospace Exploration Agency). In addition to
the higher level data processing, GOSAT DHF has the following additional roles:
1) Data archive and distribution, and
2) Observational request collection from users and their submission to JAXA.
After calibration and preliminary validation, the processed data are distributed to RA users at the first stage (RA users:
researchers engaging in Research Announcement). The processed data are validated and then they are distributed to
General Users (GU). All the distribution is carried out through the GOSAT User Interface Gateway (GUIG). As of
August 2010, the total number of user registration exceeds 900, and a large number of products are distributed both to
the RA users and GU.
At this moment, validation indicates that the FTS SWIR L2 CO2 and CH4 data show slightly lower values than validation results. Therefore, further improvement of the algorithm is planned as a next version of the FTS L2 products. FTS TIR
data processing is still on the way.
GOSAT ( Ibuki ) was successfully launched on January 23, 2009 and has been operating nominally. NIES GOSAT DHF
( Data Handling Facility) , receiving GOSAT Level 1 data of TANSO-FTS ( Fourier Transform Spectrometer) and
TANSO-CAI ( Cloud and Aerosol Imager), started checking them and generating Higher Level Products of GOSAT. The
Products include Level 1B and 1B+ of CAI and Level 2 ( CO2 and CH4 column amount from SWIR and TIR from FTS and ,
cloud flag, aerosol and cloud properties from CAI).
GOSAT Project (GOSAT stands for Greenhouse gases Observation SATellite) is a joint project of MOE (Ministry of
the Environment), JAXA (Japan Aerospace Exploration Agency) and NIES (National Institute for Environmental
Studies (NIES). Data acquired by TANSO-FTS (Fourier Transform Spectrometer) and TANSO-CAI (Cloud and Aerosol
Imager) on GOSAT (TANSO stands for Thermal And Near infrared Sensor for carbon Observation) will be
collected at Tsukuba Space Center @ JAXA. The level 1A and 1B data of FTS (interferogram and spectra,
respectively) and the level 1A of CAI (uncorrected data) will be generated at JAXA and will be transferred to
GOSAT Data Handling facility (DHF) at NIES for further processing. Radiometric and geometric correction will be
applied to CAI L1A data to generate CAI L1B data. From CAI L1B data, cloud coverage and aerosol information (CAI
Level 2 data) will be estimated. The FTS data that is recognized to have "low cloud coverage" by CAI will be processed
to generate column concentration of carbon dioxide CO2 and methane CH4 (FTS Level 2 data). Level 3 data will be
"global map column concentration" of green house gases averaged in time and space. Level 4 data will be global
distribution of carbon source/sink model and re-calculated forward model estimated by inverse model. Major data flow
will be also described. The Critical Design Review (CDR) of the DHF was completed in early July of 2007 to prepare
the scheduled launch of GOSAT in early 2009. In this manuscript, major changes after the CDR are discussed. In
addition, data acquisition scenario by FTS is also discussed. The data products can be searched and will be open to the
public through GOSAT DHF after the data validation process. Data acquisition plan is also discussed and the discussion
will cover lattice point observation for land area, and sun glint observation over water area. The Principal Investigators
who submitted a proposal for Research Announcement will have a chance to request the specific observation, early
standard data delivery and research data delivery.
For the effective evaluation of the hazard, the data should have been acquired before the hazard occurrence and should
be quickly acquired after it. While there have been a lot of discussions on application of remote sensing data to hazard
evaluation, there are few results on effective application of remote sensing data. To fulfill the first condition, it is
necessary to have world coverage of data. For the second condition, flexible and timely data acquisition is mandatory.
ASTER seems to fulfill the both conditions. In case of the giant landslide (Hattian slide) occurred in Pakistan on October
8, 2005, the data acquired before and just after the landslide are both available. And the damage was quantitatively
evaluated by using DEM generated from ASTER stereo pairs obtained before and after it.
KEYWORDS: Fourier transforms, Data modeling, Data centers, Data storage, Clouds, Data processing, Atmospheric modeling, Short wave infrared radiation, Aerosols, Data acquisition
GOSAT Project is a joint project of MOE (Ministry of the Environment), JAXA (Japan Aerospace Exploration Agency) and NIES (National Institute for Environmental Studies). Data acquired by TANSO-FTS (Fourier Transform Spectrometer) and TANSO-CAI (Cloud and Aerosol Imager) on GOSAT will be collected at Tsukuba Space Center at JAXA. The level 1A and 1B data of FTS (interferogram and spectra, respectively) and the level 1A of CAI (uncorrected data) will be generated at JAXA and will be transferred to GOSAT Data Handling facility (DHF) at NIES for further processing. Radiometric and geometric correction will be applied to CAI L1A data to generate CAI L1B data. From CAI L1B data, cloud coverage and aerosol information (CAI Level 2 data) will be estimated. The FTS data that is recognized to have "low cloud coverage" by CAI will be processed to generate column amount of carbon dioxide CO2 and methane CH4 (FTS Level 2 data). Level 3 data will be "global map column amount" of green house gases averaged in time and space. Level 4 data will be global distribution of carbon source/sink model and re-calculated forward model estimated by inverse model. Major data flow will be also described. The Critical Design Review of the DHF was completed in the end of July of 2007 to prepare the scheduled launch of GOSAT in December 2008. The data products can be searched and will be open to the public through GOSAT DHF after the data validation process.
Since the launch in December of 1999, ASTER (Advanced Thermal Emission and Reflection Radiometer) has collected more than 1,000,000 scenes of data and generated more than 10,000 DEM and ortho-rectified images (Level 3A) from them, covering 20% of the whole land. The relative and absolute accuracy of geolocation and DEM will be discussed by comparing GCPs (Ground Control Point), GIS (Geographic Information System) and other existing topographic map. ASTER has shown very high geometric accuracy even if any GCP is not available. Contributing factors to this high accuracy are the stability and knowledge of the space craft orbit and attitude, ASTER sensors geometry, information on the Earth movement, algorithm to calculate the line of site vectors, and so on. Discussion will also cover the applicability of the DEM and ortho-rectified image data, based on the accuracy, and the discussion on further improvement.
Space-borne optical remote sensor, ASTER instrument, has VNIR, SWIR and TIR bands and stereo capability. The author had made a preliminary study for the Ethiopian Rift Valley by using only TIR data by his previous paper[11]. In this study, more comprehensive study for geologic interpretation is performed by using all the VNIR, SWIR and TIR, and the topographic information extracted from along track stereo pair data.
KEYWORDS: Short wave infrared radiation, Data acquisition, Calibration, Space operations, Telescopes, Space telescopes, Sensors, Thermography, Infrared radiation, Lamps
ASTER instrument on Terra spacecraft is operating over 4 years since early 2000. The total number of acquired data exceeds 800 thousand scenes. The radiometric coefficients are frequently updated to compensate the degradation. The geometric performance is kept in good accuracy since the initial normal operation stage. The performance for radiometric, geometric and stereo capabilities will be comprehensively presented.
KEYWORDS: Clouds, Data acquisition, Data archive systems, Data centers, Data processing, Data modeling, Calibration, Sensors, Satellites, Short wave infrared radiation
ASTER (Advanced Thermal Emission and Reflection Radiometer) was launched on December 19th, 1999, from Vandenberg, California, USA, and has been circulating the Earth on a NASA platform called Terra. After the Initial Checkout Phase, ASTER started the normal operation on September 20th, 2000, and ERSDAC started ASTER data distribution on December 1st, 2000. Data Acquisition by ASTER is quite stable at a daily rate of about 600 scenes. The resulting total number of acquired scenes is 439 thousands scenes as of June 28th, 2002. This number is equivalent to more than ten times the number of scenes covering all the land areas on the earth. ASTER GDS takes an operational sequence in which the observation schedule is updated by using Cloud Prediction Data immediately before the observation. Therefore, this scheduling operation allows us to acquire the data with less cloud cover. All the acquired data are downloaded at NASA and are shipped to ERSDAC via physical media and, for some small number, via network. All the acquired data are processed to Level 1A at ASTER GDS first, and the total number as of June 28th, 2002, is about 352 thousands scenes. Next, Level 1B processing is performed for the data requested by users and the data with less than 20% cloud cover. The total number of Level 1B data is about 80 thousands scenes as of June 28th, 2002.
Japanese remote sensor ASTER was successfully launched on the NASA's Satellite Terra on December 18, 1999 by the cooperation between METI and NASA HQ, and ASTER is working without any major problems and continues to provide ASTER data. This is a result of the cooperation between US and Japan, especially ASTER Science Team, NASA GSFC, JPL, JAROS and ERSDAC. After the period of the Initial Checkout, ASTER GDS started ASTER data distribution to the public, and ASTER data is currently available without any restriction. In this paper, activities of ASTER operation and some scientific results are provided.
KEYWORDS: Short wave infrared radiation, Spatial resolution, Modulation transfer functions, Signal to noise ratio, Radiometry, Telescopes, Multispectral imaging, Thermography, Infrared radiation, Data acquisition
12 The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a high spatial resolution multispectral imaging radiometer, and is onboard the NASA's Terra spacecraft launched on December 18, 1999. It spectrally covers the visible and near-infrared, short-wave- infrared, and thermal infrared regions with 14 spectral bands, and creates high-spatial-resolution (15-90 m) multispectral images of the Earth's surface. The observation performances of the ASTER instrument were evaluated by the early images, e.g. spatial resolution, modulation transfer functions (MTF), signal-to-noise-ratios (SNRs), band-to-band registrations, and so on. It was confirmed that the ASTER instrument generally exceeds the specified observation performance, and the early images exhibit excellent quality even in the preliminary processing level. In the initial check-out phase, ASTER was operationally used for intensive monitoring of volcanic eruptions in Japan, and successfully provided useful information to volcanologists.
12 ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer) which has been developed by MITI (Ministry of International Trade and Industry) and JAROS was successfully launched on December 18 10:57 PST on the satellite called Terra by the Launch Vehicle Atlas II. On the ground, ASTER Ground DATA System (ASTER GDS) has been developed also by MITI and ERSDAC together with EOSDIS (EOS Data and Information System) that has been developed by NASA and GSFC (Goddard Space Flight Center). Currently, Terra is orbiting around the Earth on the nominal polar orbit and ASTER is collecting data from all over the world. The comprehensive operation of Terra is performed by GSFC, while ASTER operation is conducted by ASTER GDS. As of September 2000, ASTER is working well and producing good image data of VNIR (Visible and Near Infrared Radiometer), SWIR (Short Wavelength Infrared Radiometer) and TIR (Thermal Infrared Radiometer). The details at the development stage of ASTER GDS have been described three times in foregoing SPIE Conferences. In this paper, the first data and experiences during the Initial Checkout will be discussed.
KEYWORDS: Data acquisition, Space operations, Data processing, Data archive systems, Data centers, Sensors, Telecommunications, Adaptive optics, Remote sensing, Interfaces
ASTER is a remote sensor developed by MITI, Japan, on the platform EOS AM1, recently renamed Terra, fabricated by NASA, USA. The operation of the ASTER sensor will be jointly performed by Japan and USA. Currently, the launch of Terra is scheduled on early October at Vandenberg Launch Site, CA, USA. To keep this target date, ASTER Team is working with NASA. So far, many tests connecting the spacecraft Terra and Ground Segments including ASTER GDS have been conducted and it was shown that the interface between ASTER GDS and NASA is almost ready for Launch. The operation of ASTER will involve both Japan and US sides. Mission operation, which will accept complicated data acquisition schedule will be performed connecting US and Japan, and the test and exercises are being performed. The level 1 data processing will be done at ASTER GDS after having received the Level 0 data from NASA, either by media or by network. After the launch of Terra, ASTER Team expects to have 118 days of the Initial Checkout and the data distribution is planned after this time period.
ASTER is an imaging remote sensor developed by MITI, Japan, on the platform EOS-AM1 fabricated by NASA, USA. The operation of the ASTER sensor will be jointly performed by Japan and USA. The ASTER Ground Data System (ASTER GDS) will be responsible for keeping track of the sensor status, sending data acquisition schedule and for processing ASTER Level 1 and higher level data. The preliminary design concept was discussed in the literature. The ASTER GDS seems to have several challenging aspects such as: (1) The ASTER GDS handles huge data volume. (2) The ASTER GDS accepts flexible mission operation, including cloud prediction. (3) The ASTER GDS makes a correction for the Band-to-Band misregistration, including inter-telescope registration. (4) User Interface including data search by browse data which will be shown to user electronically, and data acquisition request and data processing request. According to the Data Exchange Principle, the ASTER Data will be delivered at the lowest possible price. Therefore, user community of remote sensing is expected to widely spread and to have a chance to familiarize the remote sensing data. (5) ASTER GDS has a Direct Receiving station which is capable to receive and process high rate data downlinked by X-band, in real time. In this paper, challenging aspects (1) and (2) of the ASTER GDS will be discussed in detail. The issue relating to (3) was discussed in the reference.
Planned for launch in June 1998, the Earth Observing System (EOS) AM1-spacecraft will carry five instruments which will be placed into a polar, sun-synchronous, 705 km orbit. EOS AM-1 will cross the equator at 10:30 am local time when daily cloud cover is typically at a minimum over land, such that surface features can be more easily observed. The Ministry of International Trade and Industry of Japan is providing the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument. The ASTER instrument is a high performance spatial imager which has three sensors. The interval between the nearest two orbits is 172 km at the equator. The swath of sensors is 60 km. Therefore ASTER must have pointing capability in order to cover the whole surface of the earth. ASTER accept xARs form many users. Because of constrained spacecraft data capacity, ASTER's data acquisition scheduling algorithm which will perform the most effective scheduling from the inputs which consist of many xARs and which is derived from prioritization information.
KEYWORDS: Data acquisition, Data processing, Sensors, Data archive systems, Ions, Short wave infrared radiation, Data storage, Satellites, Adaptive optics, Algorithm development
ASTER instrument is a high performance spatial imager on board the EOS-AM1 spacecraft, which will be launched in June 1998. The ASTER raw data will be captured by U.S. ground system via TDRSS, processed to level-0 data, and then transferred to the ASTER Ground Data System in Japan for level-1 data products generation. The ASTER Ground Data System consists of the Communication and System Management System (CSMS), ASTER Operation Segment (AOS), Science Data Processing Segment (SDPS), and Direct Receiving Station (DRS). The ASTER Ground Data System adopts a challenging design concept to handle approximately 780 sets of scenes of 14 spectral bands one stereo band (about 80 Gbytes) per day.
The advanced spaceborne thermal emission and reflection radiometer (ASTER) is a multi- spectral imaging radiometer with 14 spectral bands, 60 km imaging swath, and 15 - 90 m spatial resolutions. Since operation of the ASTER instrument will be affected by various constraints such as duty cycle and pointing frequencies, it is necessary to optimize the operation scenario for efficient data acquisition during the 6 year mission period. In addition, many possible combinations of the observation modes of the three ASTER subsystems (VNIR, SWIR, and TIR), which can be operated independently with different gain setting for each spectral band, complicate the data acquisition scenario. There are four data acquisition categories; local observations, regional monitoring, global mapping, and engineering team requests. Local observations will be made in response to data acquisition requests (DARs) from individual investigators. Regional monitoring and global mapping will be scheduled in response to science team acquisition requests (STARs). Prioritization of data acquisition requests will be done using the factors such as user status and observation categories. Three types of schedules; long term schedule (LTS), short term schedule (STS), and one day schedule (ODS) will be generated for ASTER observation activities.
ASTER has three telescopes corresponding to VNIR, SWIR, and TIR. Unfortunately, there will be a band-to-band misregistration among the data of different telescopes, which is caused by pointing inaccuracy of the telescopes. Knowledge of the pointing has an error of several pixels in VNIR unit. So, the registration techniques are needed to get the registered image. In this study, these techniques are investigated. VNIR data is currently considered as reference. Consequently, registration between VNIR and SWIR and the one between VNIR and TIR is calculated and corrected. The primary candidate of the evaluation of the amount of misregistration is image correlation. It will work for VNIR and SWIR registration. But, another approach seems to be needed for the registration between VNIR and TIR, whose registration may or may not have good correlation.
ASTER is an advanced multispectral imager with high spatial, spectral, and radiometric performances for an EOS-AM1 polar orbiting platform which will be launched with four other instruments in June 1998 and covers a wide spectral region from visible to thermal infrared by 14 spectral bands. To meet a wide spectral coverage, optical sensing units of ASTER are separated into three subsystems, that is, visible and near infrared subsystem, a short wave infrared subsystem, and a thermal infrared subsystem, depending on the spectral region from a technical point of view. This ASTER instrument configuration with multi-telescopes leads to necessity of the ground processing on the generation of level-1 data products which are radiometrically calibrated and geometrically registered. The concept of level-1 processing algorithm on the ASTER Ground Data System is described.
KEYWORDS: Short wave infrared radiation, Algorithm development, Computer simulations, Data modeling, Data acquisition, Data processing, Sensors, Thermography, Infrared radiation, Space telescopes
ASTER data has two kinds of misregistrations, (1) inter-telescope misregistration among VNIR, SWIR, and TIR, and (2) intra-telescope misregistration of SWIR. These misregistrations are caused by pointing inaccuracy and different look direction for each band of SWIR. To make registered images, these misregistrations should be corrected. Before the launch of ASTER, we need to establish the correction algorithms for these misregistrations. To evaluate the algorithms, we made the ASTER misregistered simulation data. This data includes the two misregistrations mentioned above. We used NASA/JPL's AVIRIS data for VNIR and SWIR bands, and NASA/JPL's TIMS data for TIR bands. We also used a digital elevation model (DEM) of 15 m grid interval to simulate the misregistration. The misregistrations of the data were corrected by the developers of algorithms, and we evaluated each correction algorithm. As the first step, we have made only the misregistered simulation data. However our goal is to evaluate the entire algorithms of ASTER level-1 processing, including misregistration corrections. So, we will make the ASTER simulation data, which includes other factors, in the future.
An airborne ASTER simulator (AAS) is being developed by the Geophysical Environmental Research Corporation (GER) to study land surface temperature and emittance in the thermal infrared. Laboratory tests in October 1992 at NASA's Stennis Space Center (SSC) measured the AAS's spectral, approximate NEdT, and approximate spatial response characteristics. The spectral FWHM for most channels is smaller than 0.3 micrometers ; the NEdT for most TIR channels is better than 0.4 K; and the nominal IFOV is 5 mrad. Flight data was collected over Cuprite and Goldfield, Nevada and near Valencia, California in November 1992. The silicified and opalized zones at Cuprite could be discriminated using decorrelation-stretch images. AAS decorrelation-stretch images agree, qualitatively, with data from NASA's thermal infrared mapping spectrometer (TIMS). These results indicate the AAS may be a good tool for remote sensing studies of geological materials. Lower noise detector arrays and linear variable (optical) filters for the TIR channels will be tested in flights over Cuprite, Nevada later this year. These and other improvements may reduce the NEdT and improve the signal-to-noise ratio.
An ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) simulator is described which is designed to simulate visible, near infrared, and thermal infrared (TIR) bands. The ASTER simulator will be applied to geological mapping, refinement of the specifications for ASTER, exploration of the mid-wavelength infrared spectral region, and climatic modeling.
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