Landsat-9, launched on September 27, 2021, carries the Thermal Infrared Sensor (TIRS). The Landsat-9 TIRS is a close copy of the Landsat-8 TIRS instrument; it is a two spectral-band, pushbroom sensor with three Sensor Chip Assemblies (SCAs) that cover the 15-degree field-of-view. The primary radiometric change between the instruments is the addition of baffling in the Landsat-9 TIRS telescope to mitigate the stray light issue that has impacted the radiometric quality of Landsat-8 TIRS. The on-orbit radiometric performance is monitored using the on-board variable temperature blackbody and views of deep space. Maneuvers to look at and around the moon have provided an assessment of the stray light. The absolute calibration is monitored by vicarious calibration techniques by teams at NASA/Jet Propulsion Lab and the Rochester Institute of Technology. Landsat-9 completed a three-month commissioning phase in January 2022 and has been operational since February 2022. The instrument has demonstrated excellent radiometric performance, as assessed from the on-orbit measurements. The TIRS instrument is radiometrically stable to 0.1% within a power cycle, and has noise levels below 0.1K. The lunar scans and the vicarious calibration data provide evidence that the stray light has been effectively mitigated.
The Landsat-8 Thermal Infrared Sensor (TIRS) has been acquiring two-band thermal infrared images of the Earth’s surface since 2013. The calibration of the two-band system has been monitored using the on-board calibrator and validated with vicarious calibration performed by NASA/Jet Propulsion Laboratory and Rochester Institute of Technology since launch. An update to the radiometric calibration was introduced into the Collection-2 processing system in late 2020 to correct for signal-dependent and time-dependent calibration errors. In November 2020, the Landsat-8 spacecraft experienced two safeholds and, while TIRS seemingly recovered nominally, there were slowly developing changes as a result. By December 2020, the TIRS Band 11 responsivity had decreased by as much as 2%. It was determined that a contaminant has been slowly depositing on a component in the optical path since the safehold and continues as of this writing. As of late June 2021, the responsivity is still decreasing in both spectral bands; Band 11 band-average responsivity has dropped by 3.7% and Band 10 band-average responsivity has dropped by 2.0%, though the decrease in responsivity is not uniform across the focal plane. Since March 2021, the TIRS products have been processed with calibration gains that account for the changing responsivity.
The Landsat-8 Thermal Infrared Sensor (TIRS) has been acquiring two-band thermal infrared images of the Earth’s surface since 2013. The calibration of the two-band system has been monitored using the on-board calibrator and validated with vicarious calibration performed by NASA/JPL and RIT since launch. Soon after launch, it was discovered that the instrument had a significant stray light effect that was affecting the radiometric calibration. The stray light was corrected in the processing system in 2017. Since then, it has become apparent that there was an additional radiometric error, based on the vicarious calibration results. With a failure within the primary electronic system and subsequent switch to the redundant electronic system, the TIRS instrument effectively has two separate calibration regimes. The vicarious calibration found a statistically significant calibration error, primarily a constant over time, in Band 11 on the primary electronics (Feb 11, 2013 through March 5, 2015) of about -0.6K at 300K. The calibration error in Band 10 was smaller though still statistically significant at about 0.2K at 300K. On the redundant side (March 5, 2015 to present), the calibration error is more signal dependent than time dependent. Both bands are affected, with Band 10 having an error between 1K and -0.4K (between 273-320K) and Band 11 having an error between 0.8K and -1.44K (between 273-320K). This calibration error will be corrected within the USGS Landsat Product Generation System with the release of Landsat Collection-2 products. The Collection-2 release also includes a correction to the relative radiometric calibration of TIRS data. Striping as a result of poor detector-to-detector normalization has been increasing in the imagery since launch. The TIRS relative radiometric calibration will be updated based on internal calibrator data to remove the stripes on a quarterly basis. The visible stripes are generally at 0.1-0.2% level, though there are some detectors in each band that have changed by 1% or more. The Collection-2 release will result in much more uniform TIRS images.
Landsat-8 has been operating on-orbit for 5+ years. Its two sensors, the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), are continuing to produce high quality data. The OLI has been radiometrically stable at the better than 0.3% level on a band average basis for all but the shortest wavelength (443 nm) band, which has degraded about 1.3% since launch. All on-board calibration devices continue to perform well and consistently. No gaps in across track coverage exist as 100% operability of the detectors is maintained. The variability over time of detector responsivity within a band relative to the average is better than 0.05% (1 sigma), though there are occasional detectors that jump up to 1.5% in response in the Short-Wave InfraRed (SWIR) bands. Signal-to-Noise performance continues at 2-3x better than requirements, with a small degradation in the 443 nm band commensurate with the loss in sensitivity. Pre-launch error analysis, combined with the stability of the OLI indicates that the absolute reflectance calibration uncertainty is better than 3%; comparisons to ground measurements and comparisons to other sensors are consistent with this. The Landsat-8 TIRS is similarly radiometrically stable, showing changes of at most 0.3% over the mission. The uncertainty in the absolute calibration as well as the detector to detector variability are largely driven by the stray light response of TIRS. The current processing corrects most of the stray light effects, resulting in absolute uncertainties of ~1% and reduced striping. Efforts continue to further reduce the striping. Noise equivalent delta temperature is about 50 mK at typical temperatures and 100% detector operability is maintained. Landsat-9 is currently under development with a launch no earlier than December 2020. The nearly identical OLI-2 and upgraded TIRS-2 sensors have completed integration and are in the process of instrument level performance characterization including spectral, spatial, radiometric and geometric testing. Component and assembly level measurements of the OLI-2, which include spectral response, radiometric response and stray light indicate comparable performance to OLI. The first functional tests occurred in July 2018 and spatial performance testing in vacuum is scheduled for August 2018. Similarly, for TIRS-2, partially integrated instrument level testing indicated spectral and spatial responses comparable to TIRS, with stray light reduced by approximately an order of magnitude from TIRS.
The Thermal Infrared Sensor (TIRS) instrument is the thermal-band imager on the Landsat-8 platform. The initial onorbit calibration estimates of the two TIRS spectral bands indicated large average radiometric calibration errors, -0.29 and -0.51 W/m2 sr μm or -2.1K and -4.4K at 300K in Bands 10 and 11, respectively, as well as high variability in the errors, 0.87K and 1.67K (1-σ), respectively. The average error was corrected in operational processing in January 2014, though, this adjustment did not improve the variability. The source of the variability was determined to be stray light from far outside the field of view of the telescope. An algorithm for modeling the stray light effect was developed and implemented in the Landsat-8 processing system in February 2017. The new process has improved the overall calibration of the two TIRS bands, reducing the residual variability in the calibration from 0.87K to 0.51K at 300K for Band 10 and from 1.67K to 0.84K at 300K for Band 11. There are residual average lifetime bias errors in each band: 0.04 W/m2 sr μm (0.30K) and -0.04 W/m2 sr μm (-0.29K), for Bands 10 and 11, respectively.
Now in its 17th year of operation, the Enhanced Thematic Mapper + (ETM+), on board the Landsat-7 satellite, continues to systematically acquire imagery of the Earth to add to the 40+ year archive of Landsat data. Characterization of the ETM+ on-orbit radiometric performance has been on-going since its launch in 1999. The radiometric calibration of the reflective bands is still monitored using on-board calibration devices, though the Pseudo-Invariant Calibration Sites (PICS) method has proven to be an effective tool as well. The calibration gains were updated in April 2013 based primarily on PICS results, which corrected for a change of as much as -0.2%/year degradation in the worst case bands. A new comparison with the SADE database of PICS results indicates no additional degradation in the updated calibration. PICS data are still being tracked though the recent trends are not well understood. The thermal band calibration was updated last in October 2013 based on a continued calibration effort by NASA/Jet Propulsion Lab and Rochester Institute of Technology. The update accounted for a 0.036 W/m2 sr μm or 0.26K at 300K bias error. The updated lifetime trend is now stable to within +/- 0.4K.
The mid and thermal infrared (MTIR) for the Earth surface is defined between 3 and 14µm. In the outer solar system, objects are colder and their Planck response shifts towards longer wavelengths. Hence for these objects (e.g. icy moons, polar caps, comets, Europa), the thermal IR definition usually stretches out to 50µm and beyond. Spectroscopy has been a key part of this scientific exploration because of its ability to remotely determine elemental and mineralogical composition. Many key gas species such as methane, ammonia, sulfur, etc. also have vibrational bands which show up in the thermal infrared spectrum above the background response.
Over the past few decades, the Jet Propulsion Laboratory has been building up a portfolio of technology to capture the MTIR for various scientific applications. Three recent sensors are briefly reviewed: The airborne Hyperspectral thermal emission spectrometer (HyTES), the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and Mars Climate Sounder (MCS)/DIVINER. Each of these sensors utilize a different technology to provide a remote sensing product based on MTIR science. For example, HyTES is a push-brooming hyperspectral imager which utilizes a large format quantum well infrared photodetector (QWIP). The goal is to transition this to a new complementary barrier infrared photodetector (CBIRD) with a similar long wave cut-off and increased sensitivity. ECOSTRESS is a push-whisk Mercury Cadmium Telluride (MCT) based high speed, multi-band, imager which will eventually observe and characterize plant/vegetation functionality and stress index from the International Space Station (ISS) across the contiguous United States (CONUS). MCS/DIVINER utilizes thermopile technology to capture the thermal emission from the polar caps and shadow regions of the moon. Each sensor utilizes specific JPL technology to capture unique science.
The ASTER instrument onboard the NASA’s Terra satellite launched in December 1999 has three subsystems divided by the spectral regions. ASTER thermal infrared (TIR) subsystem has five TIR bands with a spatial resolution of 90 m. Since March 2000 after the initial checkout period, many vicarious calibration (VC) experiments have been conducted for ASTER/TIR in lakes such as Lake Tahoe (NV/CA), Salton Sea (CA), and Lake Kasumigaura (Japan), and in dry lakes such as Railroad Valley (NV), Alkali Lake (NV), and Coyote Lake (CA). In the present paper, 307 VC matchup data obtained by three organizations were analyzed. Overall results show that a typical difference between the at-sensor radiance acquired by onboard calibration (OBC) and that predicted by VC is about 0.5 to 1 K in the water sites and about 1 to 2 K in the land sites. The results of the responsivity analysis indicate that VC is well tracking the responsivity changes measured by OBC, though the recent discrepancy at band 10 should be investigated with more VC results. The results of the offset analysis indicate that the short term calibration (STC) which is performed at a blackbody temperature of 270 K before every Earth observation has worked normally. It is therefore concluded that the ASTER/TIR instrument has been keeping the designed accuracy (1 K for the temperature range of 270 to 340 K) since the launch.
KEYWORDS: Sensors, Mirrors, Optical filters, Black bodies, Signal to noise ratio, Readout integrated circuits, Multiplexers, Prototyping, Staring arrays, Temperature metrology
The Prototype Hyspiri-TIR (PHyTIR) instrument was developed under NASA’s instrument incubator program and is now operational in the laboratory. The scan head uses state-of-the-art focal plane technology to rapidly acquire data from an eight inch telescope focused at infinite, reflective relay and continuously rotating scan mirror. A series of narrowband interference filters are placed in close proximity to the focal plane. Arrays of 256×16 Mercury Cadmium detectors are under each filter. The detectors have their long wave cutoff at 13.2μm. The filters serve to block out unwanted radiation from other spectral channels, hence forming a high performance multi-band imager with the use of the scanning mirror.
The hyperspectral thermal emission spectrometer was developed under NASA’s instrument incubator program and has
now completed three deployments. The scan head uses a state-of-the-art Dyson spectrometer cooled to 100K coupled to
a quantum well infrared photodetector array held at 40K. The combination allows for 256 spectral channels between
7.5μm and 12μm with 512 cross track spatial pixels. Spectral features for many interesting gases fall within the
instrument passband.
We first review the pre-flight calibration and validation process for HyTES using a suite of instrumentation. This
includes a smile measurement at two wavelengths (8.18μm and 10.6μm) as well as a concentration determination using
large aperture gas cells. We then show positive gas plume detection at ranges >1000m for various cases: Ammonia gas
detection from Salton Sea fumaroles, Methane detection from staged releases points in Wyoming as well as naturally
occurring methane hot spots off the coast of Santa Barbara.
Monitoring of IR Clear-Sky Radiances over Oceans for SST nearreal
time web-based system has been established in July 2008. It analyzes Model (Community Radiative Transfer Model,
CRTM) minus Observation (M-O) biases in clear-sky ocean brightness temperatures (BT) in AVHRR bands 3.7 (IR37),
11 (IR11), and 12μm (IR12) onboard NOAA-16, -17, -18, -19 and Metop-A. In January 2012, AVHRR-like bands of
VIIRS onboard the Suomi National Polar Partnership (S-NPP; launched in October 2012), and two MODIS instruments
onboard Terra and Aqua, were included in MICROS. Double-differences are employed to check various sensors for
radiometric consistency. The VIIRS and AVHRR have been in-family, and the consistency further improved after the
VIIRS IR calibration was fine-tuned on 7 March 2012. However, MODIS M-O biases have been out of family (by -0.6K
in IR 11, and -0.3K in IR12). Analyses have shown that these anomalies in MODIS M-O biases are caused by the "M"
term, i.e., incorrect MODIS transmittance coefficients in CRTM v2.02. Based on feedback from NESDIS SST and U.
Wisconsin Teams, CRTM Team updated transmittance coefficients in CRTM v2.10. As a result, MODIS M-O biases are
now in agreement with AVHRR/VIIRS. However, cross-platform Terra/Aqua bias of ~0.3 K in Ch20 (3.9μm) remains,
likely due to calibration uncertainties in MODIS L1b product. This paper documents the joint effort by the SST, MODIS
Characterization Support and CRTM Teams towards identifying and resolving observed cross-platform inconsistencies.
The Jet Propulsion Laboratory is currently developing an end-to-end instrument which will provide a proof of concept prototype vehicle for a high data rate, multi-channel, thermal instrument in support of the Hyperspectral Infrared Imager (HyspIRI)–Thermal Infrared (TIR) space mission. HyspIRI mission was recommended by the National Research Council Decadal Survey (DS). The HyspIRI mission includes a visible shortwave infrared (SWIR) pushboom spectrometer and a multispectral whiskbroom thermal infrared (TIR) imager. The prototype testbed instrument addressed in this effort will only support the TIR. Data from the HyspIRI mission will be used to address key science questions related to the Solid Earth and Carbon Cycle and Ecosystems focus areas of the NASA Science Mission Directorate. Current designs for the HyspIRI-TIR space borne imager utilize eight spectral bands delineated with filters. The system will have 60m ground resolution, 200mK NEDT, 0.5C absolute temperature resolution with a 5-day repeat from LEO orbit. The prototype instrument will use mercury cadmium telluride (MCT) technology at the focal plane array in time delay integration mode. A custom read out integrated circuit (ROIC) will provide the high speed readout hence high data rates needed for the 5 day repeat. The current HyspIRI requirements dictate a ground knowledge measurement of 30m, so the prototype instrument will tackle this problem with a newly developed interferometeric metrology system. This will provide an absolute measurement of the scanning mirror to an order of magnitude better than conventional optical encoders. This will minimize the reliance on ground control points hence minimizing post-processing (e.g. geo-rectification computations).
The Jet Propulsion Laboratory is currently developing an end-to-end instrument which will provide a proof of concept
prototype vehicle for a high data rate, multi-channel, thermal instrument in support of the Hyperspectral Infrared Imager
(HyspIRI)-Thermal Infrared (TIR) space mission. HyspIRI mission was recommended by the National Research
Council Decadal Survey (DS). The HyspIRI mission includes a visible shortwave infrared (SWIR) pushboom
spectrometer and a multispectral whiskbroom thermal infrared (TIR) imager. The prototype testbed instrument
addressed in this effort will only support the TIR. Data from the HyspIRI mission will be used to address key science
questions related to the Solid Earth and Carbon Cycle and Ecosystems focus areas of the NASA Science Mission
Directorate. Current designs for the HyspIRI-TIR space borne imager utilize eight spectral bands delineated with filters.
The system will have 60m ground resolution, 200mK NEDT, 0.5C absolute temperature resolution with a 5-day repeat
from LEO orbit. The prototype instrument will use mercury cadmium telluride (MCT) technology at the focal plane
array in time delay integration mode. A custom read out integrated circuit (ROIC) will provide the high speed readout
hence high data rates needed for the 5 day repeat. The current HyspIRI requirements dictate a ground knowledge
measurement of 30m, so the prototype instrument will tackle this problem with a newly developed interferometeric
metrology system. This will provide an absolute measurement of the scanning mirror to an order of magnitude better
than conventional optical encoders. This will minimize the reliance on ground control points hence minimizing postprocessing
(e.g. geo-rectification computations).
KEYWORDS: Calibration, Error analysis, Earth observing sensors, Data acquisition, Data archive systems, Camera shutters, Data centers, Landsat, Mirrors, Temperature metrology
Landsat-7 ETM+, launched in April 1999, and Landsat-5 TM, launched in 1984, both have a single thermal band. Both
instruments' thermal band calibrations have been updated: ETM+ in 2001 for a pre-launch calibration error and TM in
2007 for data acquired since the current era of vicarious calibration has been in place (1999). This year, the vicarious
calibration teams have made regular collects of very hot targets, and have been able to make use of archived buoy data to
extend the TM calibration back in time. The new data has made it clear that both instruments require slight adjustments
in their thermal calibration coefficients. These new coefficients will be generated and put into the operational processing
system to remove the calibration errors.
The JPL vicarious calibration team has long operated automated buoys on Lake Tahoe for the purpose of vicarious
calibration. This year, the Salton Sea station came on line. Salton Sea, located in southern California, gets far hotter
than Lake Tahoe. Vicarious calibration results of the Salton Sea for both instruments added to the understanding of a
small gain error that the Tahoe data had suggested. With the Salton Sea data, an ETM+ gain error became statistically
significant. Though it causes errors as large as 1.2K at high temperatures (35C), at more usual earth temperatures (4-20C) the calibration error is within the noise of the calibration methodology (+/-0.6K). With an ETM+ calibration
update, the RMSE will be +/-0.6K for all temperatures.
The RIT vicarious calibration team mined the archive of the NOAA National Data Buoy Center for sites on the Great
Lakes and in the Atlantic Ocean where buoy data was regularly available between 1984 and 2007 and there were
radiosonde data within close proximity to allow for atmospheric correction. Four Landsat scenes were chosen and the
study made use of almost 200 separate acquisitions of these scenes. The technique was first tested with Landsat-7 data,
and was shown to be as reliable as the standard RIT vicarious calibration methods. The TM calibration was largely
unmonitored for most if it's lifetime. The buoy results suggest a lifetime error in gain and a change in the offset after
1997. The 2007 TM calibration update accounted for much of the offset error but was only implemented for data
acquired after 1999. With the additional buoy data, the calibration will be corrected for the earlier time period and the
result will be a consistent calibration to within +/-0.6K for the lifetime of the TM.
An airborne thermal hyperspectral imager is underdevelopment which utilizes the compact Dyson optical configuration
and quantum well infrared photo detector (QWIP) focal plane array. The Dyson configuration uses a single monolithic
prism-like grating design which allows for a high throughput instrument (F/1.6) with minimal ghosting, stray-light and
large swath width. The configuration has the potential to be the optimal imaging spectroscopy solution unmanned aerial
vehicles (UAV) due to its small form factor and relatively low power requirements. The planned instrument
specifications are discussed as well as design trade-offs. Calibration testing results (noise equivalent temperature
difference, spectral linearity and spectral bandwidth) and laboratory emissivity plots from samples are shown using an
operational testbed unit which has similar specifications as the final airborne system. Field testing of the testbed unit
was performed to acquire plots of emissivity for various known standard minerals (quartz). A comparison is made using
data from the ASTER spectral library.
An airborne thermal hyperspectral imager is underdevelopment which utilizes the compact Dyson optical configuration
and quantum well infrared photo detector (QWIP) focal plane array. The Dyson configuration uses a single monolithic
prism-like grating design which allows for a high throughput instrument (F/1.6) with minimal ghosting, stray-light and
large swath width. The configuration has the potential to be the optimal imaging spectroscopy solution unmanned aerial
vehicles (UAV) due to its small form factor and relatively low power requirements. The planned instrument
specifications are discussed as well as design trade-offs. Calibration testing results (noise equivalent temperature
difference, spectral linearity and spectral bandwidth) and laboratory emissivity plots from samples are shown using an
operational testbed unit which has similar specifications as the final airborne system. Field testing of the testbed unit
was performed to acquire plots of emissivity for various known standard minerals (quartz). A comparison is made using
data from the ASTER spectral library.
Preliminary results are presented for an ultra compact long-wave infrared slit spectrometer based on the Dyson
concentric design. The spectrometer has been integrated in a dewar environment with a quantum well infrared
photodetecor (QWIP), concave electron beam fabricated diffraction grating and ultra precision slit. The entire system is
cooled to cryogenic temperatures to maximize signal to noise ratio performance, hence eliminating thermal signal from
transmissive elements and internal stray light. All of this is done while maintaining QWIP thermal control. A general
description is given of the spectrometer, alignment technique and predicated performance. The spectrometer has been
designed for optimal performance with respect to smile and keystone distortion. A spectral calibration is performed with
NIST traceable targets. A 2-point non-uniformity correction is performed with a precision blackbody source to provide
radiometric accuracy. Preliminary laboratory results show excellent agreement with modeled noise equivalent delta
temperature and detector linearity over a broad temperature range.
During the Tahoe 2006 field effort, the NASA ER-2 aircraft flew 2 nighttime science missions (September 29
and October 13, 2006) over California and the nearby Pacific Ocean. Because of its high cruising altitude
(above ~95% of the atmosphere), the ER-2 platform closely simulates satellite-based observations of the
earth-atmosphere system. Each Tahoe 2006 mission included overpasses of the Lake Tahoe Validation
Network and an underflight of the Aqua satellite. An 8+ minute ER-2 flight segment of clear sky data over
the Pacific Ocean on the October 13 flight has been used to assess the MODIS thermal band (bands 20-36)
radiometric performance. For the assessment MODIS radiances are simulated using the MAS high spatial
resolution and SHIS high spectral resolution radiances (the calibration backbone of the MODIS assessment),
and compared to the co-located MODIS observations. The assessment (286 matchups) shows that Aqua
MODIS thermal bands continue to perform within or very nearly within their 1% radiometric specification
(0.5% for window bands 31, 32; 0.75% for window band 20) with the exception of band 30 (ozone) and band
36 (CO2). There is low confidence in the ozone band 30 assessment due to lack of information on the ozone
profile above the ER-2 flight level; band 36 however, appears to be consistently about 0.7 K warmer than
expected. These results are consistent with a previous Aqua MODIS comparison to SHIS and MAS in 2002
and with previously reported1 comparisons of Aqua AIRS and MODIS observations.
KEYWORDS: Calibration, Earth observing sensors, Landsat, Sensors, Stanford Linear Collider, Data acquisition, Black bodies, Databases, Camera shutters, Satellites
Landsat-5 Thematic Mapper (TM) has been imaging the Earth since March 1984 and Landsat-7 Enhanced Thematic
Mapper Plus (ETM+) was added to the series of Landsat instruments in April 1999. The stability and calibration of the
ETM+ has been monitored extensively since launch. Though not monitored for many years, TM now has a similar
system in place to monitor stability and calibration. University teams have been evaluating the on-board calibration of
the instruments through ground-based measurements since 1999. This paper considers the calibration efforts for the
thermal band, Band 6, of both the Landsat-5 and Landsat-7 instruments.
Initial calibration results for the Landsat-7 ETM+ thermal band found a bias error which was corrected through changes
in the processing systems in late 2000. Recent results are suggesting a calibration error in gain, apparent with high
temperature targets. For typical earth temperature targets, from about 5-20C, the gain error is small enough to be within
the noise of the vicarious calibration process. However, for very high temperature targets (greater then 35C), Landsat-7
appears to be predicting several degrees too low. Questions remain on whether the change happened suddenly or is
varying slowly, so the team will wait for another collection season before making any updates to the calibration.
The calibration efforts for Landsat-5 TM considers only data collected since 1999, though there are efforts underway to
extend the calibration history prior to the Landsat-7 launch. The latest data suggests that the Landsat-5 thermal band has
a bias error of about 0.65K too low since 1999. Studies early in the life of Landsat-5 show that the instrument was
calibrated within the error of the calibration process. It is impossible to tell, at this point, when or how the change in
bias may have occurred. A correction will be calculated and implemented in the US processing system in 2006 for data
acquired since April 1999.
Five cases using NASA ER-2 aircraft based SHIS and MAS radiances have been used to assess the L1B radiometric performance of Terra and Aqua MODIS Collection 5 radiances for LWIR bands 31-36. The composite results of these cases show that the split window bands 31 (11 μm) and 32 (12 μm) have performed well within the 0.5% radiometric specification over their lifetime. This is in agreement with results from other ground based and satellite based comparisons that are discussed in the paper. However, the LWIR CO2-sensitive bands 34-36 appear to be performing outside of their 1% accuracy specification, especially for Terra MODIS. This is also observed in global Aqua AIRS-MODIS comparisons. Possible causes for this behavior are under investigation, with the most likely contributors being spectral characterization error, OOB influences due to spectral filter leaks, or possibly scan mirror characterization. It seems that an optical leak from Terra MODIS band 31 into bands 32-36 is probably not a significant contributor to the large residuals of bands 34-36, owing to an effective radiometric correction. Calibration coefficient error is probably only a small contributor since, after adjustments in 2002, the on-orbit calibration now closely follows that of the pre-launch calibration.
Since shortly after launch the radiometric performance of band 6 of the ETM+ instrument on Landsat 7 has been evaluated using vicarious calibration techniques for both land and water targets. This evaluation indicates the radiometric performance of band 6 has been both highly stable and accurate. Over a range corresponding to a factor of two in radiance (5 to 55 C in kinetic temperature terms) the difference between the in-situ derived radiance and the image derived radiance is on average 0.5% or less. Water targets are the easiest to use but are limited to the temperature range from 0 to about 32 C. Land targets can reach 55 C or more but are far less spatially homogeneous than water targets with respect to both local surface temperature and spectral emissivity. The techniques used and the results are described.
An atmospheric correction tool has been developed on a public access web site for the thermal band of the Landsat-5 and Landsat-7 sensors. The Atmospheric Correction Parameter Calculator uses the National Centers for Environmental Prediction (NCEP) modeled atmospheric global profiles interpolated to a particular date, time and location as input. Using MODTRAN radiative transfer code and a suite of integration algorithms, the site-specific atmospheric transmission, and upwelling and downwelling radiances are derived. These calculated parameters can be applied to single band thermal imagery from Landsat-5 Thematic Mapper (TM) or Landsat-7 Enhanced Thematic Mapper Plus (ETM+) to infer an at-surface kinetic temperature for every pixel in the scene.
The derivation of the correction parameters is similar to the methods used by the independent Landsat calibration validation teams at NASA/Jet Propulsion Laboratory and at Rochester Institute of Technology. This paper presents a validation of the Atmospheric Correction Parameter Calculator by comparing the top-of-atmosphere temperatures predicted by the two teams to those predicted by the Calculator. Initial comparisons between the predicted temperatures showed a systematic error of greater then 1.5K in the Calculator results. Modifications to the software have reduced the bias to less then 0.5 ± 0.8K. Though not expected to perform quite as well globally, the tool provides a single integrated method of calculating atmospheric transmission and upwelling and downwelling radiances that have historically been difficult to derive. Even with the uncertainties in the NCEP model, it is expected that the Calculator should predict atmospheric parameters that allow apparent surface temperatures to be derived within ±2K globally, where the surface emissivity is known and the atmosphere is relatively clear. The Calculator is available at http://atmcorr.gsfc.nasa.gov.
Calibration of the five EOS ASTER instrument emission bands (90 m pixels at surface) is being checked during the operational life of the mission using field measurements simultaneous with the image acquisition. For water targets, radiometers, temperature measuring buoys and local radiosonde atmospheric profiles are used to determine the average water surface kinetic temperature over areas roughly 3 X 3 pixels in size. The in-band surface leaving radiance is then projected through the atmosphere using the MODTRAN radiation transfer code allowing an at sensor radiance comparison. The instrument at sensor radiance is also projected to the water surface allowing a comparison in terms of water surface kinetic temperature. Over the first year of operation, the field measurement derived at sensor radiance agrees with the image derived radiance to better than plus/minus 1% for all five bands indicating both stable and accurate operation.
Recovery of land surface temperature (LST) from remotely sensed data requires correction for atmospheric effects and decoupling surface temperature and emissivity. In this study, we have applied the Temperature Emissivity Separation (TES) method to several flight lines of the Thermal Infrared Multispectral Scanner (TIMS) acquired as part of the HAPEX- Sahel experiment. Atmospheric correction of at-sensor radiances is done by means of nearly coincident radiosondes and the MODTRAN radiative transfer code. The sensitivity of the method to the atmospheric corrections has been checked by using different radiosonde data. Even for low altitude flights, ignorance of atmospheric correction can lead to large errors in the retrieved emissivities and temperatures. Errors depend on the surface type, but in all cases channel 1 and 6 of TIMS are the most affected. The TES method is based on an empirical relationship relating the maximum-minimum emissivity difference (or contrast) with the minimum value for the 6 TIMS channels. Residual atmospheric effects dictate the max-min difference, especially for flat targets (e.g. vegetation). Since channels 1 and 6 have shown a greater sensitivity to atmospheric effects, a modified version using only the 4 central channels has been proposed and applied to the TIMS scenes. Preliminary results suggest that this modified version yields better values for vegetation targets, with emissivities around 0.98 and very little spectral variation.
KEYWORDS: Nanoelectromechanical systems, Temperature metrology, Atmospheric corrections, Numerical simulations, Reflectivity, Black bodies, Calibration, Image restoration, Monte Carlo methods, Remote sensing
The ASTER scanner on NASA's EOS-AM1 satellite (launch: 1998) will collect five channels of TIR data with an NE(Delta) T of less than or equal to 0.3 degrees Kelvin to estimate surface kinetic temperatures and emissivity spectra, especially over land, where emissivities are not known in advance. Temperature/emissivity separation (TES) is difficult because there are five measurements but six unknowns. Various approaches have been used to constrain the extra degree of freedom. ASTER's TES algorithm hybridizes three established algorithms, first estimating the temperature by the normalized emissivity method, and then using it to calculate emissivity band ratios. An empirical relationship predicts the minimum emissivity from the spectral contrast (min-max difference: MMD) of the ratioed values, permitting recovery of the emissivity spectrum. TES uses an iterative approach to remove reflected sky irradiance. Based on numerical simulation, TES can recover temperatures within about plus or minus 1.5 degrees Kelvin, and emissivities within about plus or minus 0.015. Limitations arise from the empirical relationship between emissivity values and spectral contrast, compensation for reflected sky irradiance, and ASTER's precision, calibration and atmospheric correction. Improvements of TES before launch will focus on refining the MMD relationship.
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