NOAA's Geostationary Extended Observations (GeoXO) satellite system will provide advanced hyperspectral resolution infrared observations. The first GeoXO Sounder (GXS) will fly in the mid-2030s and provide an unprecedented level of information. The plans are for the GXS to be located at a longitude over the center of the U.S. The GXS will be as much of an improvement over the legacy Geostationary Operational Environmental Satellite (GOES) broad-spectral resolution sounder as the Advanced Baseline Imager (ABI) was to the legacy imager. The GXS will be the U.S. contribution to the global ring of geostationary advanced infrared sounders. The GXS sensor will provide unique information about the vertical structure of moisture, winds, and temperature to support both Numerical Weather Prediction (NWP) and nowcasting applications.

This paper will present the first radio occultation (RO) electron density profiles of Earth’s atmosphere generated from a Global Positioning System (GPS) receiver in Geostationary orbit. The GPS receivers on the GOES-16 (R) and GOES-17 (S) satellites track GPS signals propagated through the Earth’s atmosphere and can be used to estimate electron density profiles. Radio occultation profiles from geosynchronous orbit holds the potential to generate unique temporal and spatial atmospheric measurements complementary to those from ground and low Earth orbit space based receivers, including limb observations of the upper atmosphere at altitudes above traditional low Earth orbiting RO satellites. This paper will present details of the GOES satellite GPS receivers and the limitations and challenges in generating RO profiles with its current hardware and software configuration. Following, the temporal and geo-spatial coverage for each of the GOES satellites will be presented, quantifying the frequency and number of GPS signals tracked down to sufficiently low enough altitudes to provide useful atmospheric information. Next, the data processing required to generate excess phase and electron density profiles will be described and demonstrated using two examples of GOES profiles. Subsequently, these two example GOES RO profiles will be compared to and calibrated with an ionospheric model, compared with co-located profiles from the low Earth orbit COSMIC-2 constellation and a ground based ionosonde.

The Thermal Infrared Sensor 2 (TIRS-2) payload for the Landsat 9 mission closely follows the design of the TIRS instrument currently flying aboard Landsat 8. The TIRS-2 instrument, however, incorporates an important design change to mitigate the stray light issue that plagued the TIRS instrument. Shortly after launch of Landsat 8 in 2013, calibration errors due to stray light artifacts were observed in Earth imagery from TIRS with magnitudes of 4% (10.8 μm band) and 8% (12.0 μm band). Out-of-field scans of the Moon were conducted to map the angles from which off-axis radiance was detected on the focal plane arrays. Optical modeling, constrained by reverse ray traces of the lunar data, identified the primary scattering sources within the TIRS telescope and these results informed the locations and design of mitigating baffles for TIRS-2. The effect of the modifications to the TIRS-2 instrument were tested pre-flight through the thermal vacuum (TVAC) characterization tests and the optical models were updated to be consistent with the measured data. Preliminary assessments indicated at least an order of magnitude reduction of the total signal due to scattering in TIRS-2. On-orbit lunar scans provided the final confirmations and demonstrated that the new design changes to TIRS-2 have reduced the primary out-of-field scattering by over 40x from the original TIRS design bringing the total scattering to 1% or less. More importantly, Earth imagery produced by Landsat 9 TIRS-2 do not show any stray light related artifacts, as was prevalent in the Landsat 8 TIRS imagery.

The Thermal Infrared Sensor 2 (TIRS-2) on Landsat 9 launched September 27, 2021 and underwent a variety of tests during its commissioning phase to establish its postlaunch performance. We report on the calibration updates performed to maintain its calibration and generate high quality imagery. This is done by transferring the SI-traceable pre-launch calibration to on-orbit while accounting for changes in the TIRS-2 response as detected through on-board calibrator observations. Additional empirical corrections were implemented to mitigate image striping observed on-orbit. The detector arrays were monitored through its commissioning phase to ensure that stable detectors were chosen for operations. TIRS-2 has demonstrated ~0.025% instability over its orbit, ~80 mK noise equivalent delta temperature, and an absolute radiometric uncertainty <1.4% in its nominal temperature range enabling a wide array of Earth science applications.

The Thermal Infrared Sensor-2 (TIRS-2) that will be onboard Landsat 9 has undergone a prelaunch testing campaign to characterize its radiometric, spectral, and spatial performances and demonstrate compliance to its requirements. This work reviews the key elements of the instrument-level radiometric testing using an SI-traceable source to derive its uncertainties. Those arising from on-orbit calibration using the TIRS-2 onboard blackbody are also discussed. We use a Monte Carlo approach to propagate the uncertainties through a nonlinear calibration equation and address both random and systematic uncertainty terms. Achieving the required performance demonstrates the instrument's potential for enhancing our understanding of the Earth's environment.

Landsat 9 is currently under development as a joint effort between NASA and the United States Geological Survey (USGS). Landsat 9 is largely a rebuild of Landsat 8 and has the same two sensors, an Operational Land Imager (OLI) and a Thermal InfraRed Sensor (TIRS). The OLI-2 on Landsat 9, being built by Ball Aerospace, has completed its pre-launch characterization and calibration and is scheduled to be delivered in the summer of 2019. The TIRS-2, with improved stray light performance and increased redundancy for improved reliability, is being built by Goddard Space Flight Center. TIRS-2 is undergoing testing through Spring 2019 and is also scheduled for summer 2019 delivery. Several improvements to the characterization of both instruments have been incorporated into the testing plan, including improved spectral and radiometric characterization. The instruments will then be integrated onto the spacecraft being built by Northrop Grumman Innovation Systems (NGIS). The mission is targeted to launch as early as December 2020 on an Atlas V.

Landsat 9 will continue the Landsat data record into its fifth decade with launch scheduled for December 2020. The two instruments on Landsat 9 are Thermal Infrared Sensor-2 (TIRS-2) and Operational Land Imager-2 (OLI-2). OLI-2 is a nine-channel pushbroom imager with a 15-degree field of view that will have a 16-day measurement cadence from its nominal 705-km orbit altitude. A key aspect of the data that will be produced by OLI-2 is its spectral fidelity which enables countless science applications. The prelaunch test campaign for spectral characterization of OLI-2 was substantially improved relative to the methodology used for OLI: the full spectral response of every detector was characterized with greater accuracy, sampling, and precision. This paper will describe how this was accomplished with a tunable laser-based light source called Goddard Laser for Absolute Measurement of Radiance (GLAMR).

The 17th Geostationary Operational Environmental Satellite (GOES-17) was launched on 1 March 2018. The Advanced Baseline Imager (ABI) is the primary instrument on the GOES-R series for weather and environmental monitoring. The GOES-17 ABI (flight model 2) experienced a degradation in its thermal system that limits ABI's ability to shed solar heat load. This limitation resulted in significant reduction in performance after initial turn on with only 3 of 16 spectral channels expected to be available for much of the year. A combined government/vendor team was tasked with optimizing the operation of ABI to recapture as much performance as possible. By modifying the operational configuration and sensor parameters, the team was able to regain over 97% imaging capability. This was accomplished by taking advantage of the considerably flexible nature of ABI's design to adapt its configuration to the new reality and improve capabilities for many of ABI's subsystems. The significant differences in operational configuration, sensor parameter optimization, and algorithm optimization will be discussed as well as their impact on performance and data availability.

The Thermal Infrared Sensor 2 (TIRS-2) that will fly aboard Landsat 9 has undergone pre-launch spectral characterization to demonstrate that its spectral response requirements will be met with few waivers. The test was conducted both at the subsystem level and, after upgrading the test setup and improving the alignment methodology, at instrument-level as well. This work reviews these upgrades and alignment methodology that contributed to a reduction in spectral response uncertainties to a relatively small value relative to the overall TIRS-2 radiometric uncertainty requirements. The spectral response results show an increase in signal to noise ratio and reference detector stability from subsystem-level to instrument-level measurements. Spectral response testing is part of a comprehensive pre-launch test program that ensures TIRS-2 will achieve the performance necessary for a variety of environmental applications.

FIREFLY (Fluorescence Imaging of REd and Far-red Light Yield) is a compact, fine-resolution imaging spectrometer that was designed and assembled by Headwall Photonics (Fitchburg, MA, USA) in collaboration with NASA scientists for airborne measurements of Solar-Induced Fluorescence (SIF). FIREFLY is integrated into the next generation of NASA Goddard's Lidar, Hyperspectral and Thermal airborne imager (G-LiHT; www.gliht.nasa.gov), providing a complete system for measuring, interpreting and scaling SIF emissions. Characterization of FIREFLY was performed here to evaluate its performance and suitability for retrieving SIF.

Results from the Thermal Infrared Sensor 2 (TIRS-2) prelaunch spectral characterization at telescope and detector subsystem level are presented. The derived relative spectral response (RSR) shape is expected to be very similar to the instrument-level spectral response and provides an initial estimate of the RSR and its differences to the component-level RSR measurements. Such differences were observed at TIRS-1 and are likely a result of angular dependence of the spectral response of the detector. The subsystem RSR measurements also provide an opportunity for a preliminary assessment of the spectral requirements. Final requirements verification will be performed at future thermal vacuum environmental testing with the fully assembled TIRS-2 instrument.

The Thermal Infrared Sensor 2 (TIRS-2) will fly aboard the Landsat 9 spacecraft and leverages the Thermal Infrared Sensor (TIRS) design currently flying on Landsat 8. TIRS-2 will provide similar science data as TIRS, but is not a build-to-print rebuild due to changes in requirements and improvements in absolute accuracy. The heritage TIRS design has been modified to reduce the influence of stray light and to add redundancy for higher reliability over a longer mission life. The TIRS-2 development context differs from the TIRS scenario, adding to the changes. The TIRS-2 team has also learned some lessons along the way.

Landsat 9 will continue the Landsat data record into its fifth decade with a near-copy build of Landsat 8 with launch scheduled for December 2020. The two instruments on Landsat 9 are Thermal Infrared Sensor-2 (TIRS-2) and Operational Land Imager-2 (OLI-2). TIRS-2 is a two-channel pushbroom imager with a 15-degree field of view that will have a 16-day measurement cadence from its nominal 705-km orbit altitude. Its carefully developed instrument performance requirements and associated characterization plan will result in stable and well-understood science-quality imagery that will be used for environmental, economic and legal applications. This paper will present a summary of the plan for TIRS-2 prelaunch characterization at the component, subsystem, and instrument level.

Although the Thermal Infrared Sensor 2 (TIRS-2) is a near-identical copy of the Landsat 8/TIRS-1 instrument, an important design change to the optical system was designed to mitigate the stray light issue that plagued the TIRS-1 instrument [1, 2, 3]. This change involved the addition of several baffles strategically placed within the optical telescope to block the stray light paths that were present in the TIRS-1 design. The specific optical changes were determined by first characterizing the TIRS-1 stray light paths on-orbit and then deriving a detailed optical model that was used to determine the locations and shapes of the mitigating baffles. The stray light design changes to the TIRS-2 instrument were confirmed through the initial thermal-vacuum characterization tests. Preliminary assessments of TIRS-2 indicate that the total stray light magnitude has been drastically reduced to a total magnitude of approximately 1% or less.

Spaceborne spectrometers require spectral-temporal stability characterization to aid in validation of derived data products. Earth Observation 1 (EO-1) began orbital precession in 2011 after exhausting onboard fuel resources. In the Libya-4 pseudoinvariant calibration site (PICS), this resulted in a progressive shift from a mean local equatorial crossing time of ~10:00 A.M. in 2011 to ~8:30 A.M. in late 2015. Here, we studied precession impacts to Hyperion surface reflectance products using three atmospheric correction approaches from 2004 to 2015. Combined difference estimates of surface reflectance were2) in VNIR from 0.25 to 0.94 and in SWIR from 0.12 to 0.88 (p <; 0.01). The uncertainties in all the models increased with a terrain slope up to 15° and selecting dune flats could reduce errors. We conclude that these data remain a valuable resource over this period for sensor intercalibration despite orbital decay.

The land surface imaging (LSI) virtual constellation approach promotes the concept of increasing Earth observations from multiple but disparate satellites. We evaluated this through spectral and spatial domains, by comparing surface reflectance from 30-m Hyperion and 2-m resolution WorldView-2 (WV-2) data in the Libya-4 pseudoinvariant calibration site. We convolved and resampled Hyperion to WV-2 bands using both cubic convolution and nearest neighbor (NN) interpolation. Additionally, WV-2 and WV-1 same-date imagery were processed as a cross-track stereo pair to generate a digital terrain model to evaluate the effects from large (>70 m) linear dunes. Agreement was moderate to low on dune peaks between WV-2 and Hyperion (R22> 0.6). Our results provide a satellite sensor intercomparison protocol for an LSI virtual constellation at high spatial resolution, which should start with geolocation of pixels, followed by NN interpolation to avoid tall dunes that enhance surface reflectance differences across this internationally utilized site.

An inter-calibration method is developed to provide absolute radiometric calibration of narrow-swath imaging sensors with reference to non-coincident wide-swath sensors. The method predicts at-sensor radiance using non-coincident imagery from the reference sensor and knowledge of spectral reflectance of the test site. The imagery of the reference sensor is restricted to acquisitions that provide similar view and solar illumination geometries to reduce uncertainties due to directional reflectance effects. Spectral reflectance of the test site is found with a simple iterative radiative transfer method using radiance values of a well-understood wide-swath sensor and spectral shape information based on historical ground-based measurements. At-sensor radiance is calculated for the narrow-swath sensor using this spectral reflectance and atmospheric parameters that are also based on historical in-situ measurements. Results of the inter-calibration method show agreement on the 2-5% level in most spectral regions with the vicarious calibration technique relying on coincident ground-based measurements referred to as the reflectance-based approach. While the variability of the inter-calibration method based on non-coincident image pairs is significantly larger, results are consistent with techniques relying on in-situ measurements. The method is also insensitive to spectral differences between the sensors by transferring to surface spectral reflectance prior to prediction of at-sensor radiance. The utility of this inter-calibration method is made clear by its flexibility to utilize image pairings with acquisition dates differing in excess of 30 days allowing frequent absolute calibration comparisons between wide- and narrow-swath sensors.

There exist numerous methods for accomplishing on-orbit calibration. Methods include the reflectance-based approach relying on measurements of surface and atmospheric properties at the time of a sensor overpass as well as invariant scene approaches relying on knowledge of the temporal characteristics of the site. The current work examines typical cross-calibration methods and discusses the expected uncertainties of the methods. Data from the Advanced Land Imager (ALI), Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), Moderate Resolution Imaging Spectroradiometer (MODIS), and Thematic Mapper (TM) are used to demonstrate the limits of relative sensor-to-sensor calibration as applied to current sensors while Landsat-5 TM and Landsat-7 ETM+ are used to evaluate the limits of in situ site characterizations for SI-traceable cross calibration. The current work examines the difficulties in trending of results from cross-calibration approaches taking into account sampling issues, site-to-site variability, and accuracy of the method. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The results show that cross calibrations with absolute uncertainties <; 1.5% (1σ) are currently achievable even for sensors without coincident views.

The National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) will fly an imaging spectrometer, small footprint waveform LiDAR and high-resolution digital camera to observe both the human drivers of climate change and the biological consequences of environmental change at a continental scale. The project is planned for a 30-year period. To be meaningful as an ecological climate data record, the AOP data set must have a continuous and consistent calibration effort. This paper briefly describes plans for the development of a robust calibration and validation plan to ensure data continuity from instrument-to-instrument, flight-to-flight, and year-toyear over the lifetime of the NEON project.

The reflectance-based method is a vicarious approach providing absolute radiometric calibration. A desire to increase the number of possible reflectance-based calibrations led the University of Arizona Remote Sensing Group (RSG) to deploy multispectral, downlooking radiometers at the RSG's Railroad Valley test site in Nevada. The radiometers are coupled with data from a sun photometer to provide the information needed for reflectance-based calibration without the need for on-site personnel. Results from these radiometers show similar uncertainties as on-site methods, and early results have led to their use with geostationary sensors, for derivation of surface bi-directional reflectance effects, and for comparisons of biases between sensors. The results show that radiometers with a single view angle are sufficient to characterize BRDF effects for Railroad Valley Playa. The results also give confidence in the automated approach as a means for cross-calibration relative to the vicarious results providing similar intercomparison results as with on-site personnel.