The Earth surface Mineral dust source InvesTigation (EMIT) is a remote visible to shortwave infrared (VSWIR) imaging spectrometer that has been operating onboard the International Space Station since July 2022. This article describes EMIT's on-orbit spectroradiometric calibration and validation. Accurate spectroscopy is vital to achieve consistent mapping results with orbital imaging spectrometers. EMIT takes a unique approach to this challenge, with just six optical elements, no shutter, and no onboard calibration systems. Its simple design focuses on uniformity and stability to enable vicarious spectroradiometric calibration. Our experiments demonstrate that this approach is successful, approaching the fidelity of manual field spectroscopy in some cases, and enabling new and more accurate products across diverse Earth science disciplines. EMIT achieves several notable firsts for an instrument of its class. It demonstrates successful on-orbit adjustments of Focal Plane Array (FPA) alignment with sub-micron precision. It offers spectral uniformity better than 98%. Optical artifacts in the measurement channels are at least three orders of magnitude below the primary solar-reflected surface signals. Its noise performance enables percent-level discrimination in the depths of mineral absorption features. In these aspects, EMIT satisfies the stringent performance needs for the next generation of VSWIR imaging spectrometers to observe the Earth's ecosystems, geology, and water resources.

The Airborne Visible / Infrared Imaging Spectrometer-3 (AVIRIS-3) instrument is the newest member of NASA’s AVIRIS airborne imaging spectrometer family. A Dyson pushbroom spectrometer similar to the satellite-based Earth Mineral Dust Source Investigation (EMIT) instrument, AVIRIS-3 offers higher throughput, a higher signal-to-noise ratio, and a more compact form factor than previous AVIRIS generations. AVIRIS-3 relies upon in-flight data to create updates to the wavelength, flatfield, and radiometric calibration using features from Earth’s surface and atmosphere. This technique of applying calibration updates derived from in-flight, solar-illuminated Earth scenes will be used in NASA’s upcoming Surface Biology and Geology (SBG) mission. We discuss the calibration method and first results from the first year of flights from AVIRIS-3.

In the search for evidence of extant or extinct life on Mars, characterization of the physical and geochemical properties of a sample - as well as the physicochemical conditions under which that sample was collected - may be critical in the interpretation of any biosignatures discovered. To ensure collection of a statistically meaningful set of samples for biosignature assessment, multiple samples should be collected in these same locations, as well as in nearby areas of the same material (i.e., similar in physical and geochemical properties). To determine the optimal spatial sampling for such a sample set, we explored four volcanic regions of Iceland: two recent tephra fields (Holuhraun and Fimmvorouhals) and two older glaciovolcanic sand sheets, or sandur (Dyngjusandur and Maelifellssandur). These regions have a similar mafic rock source but span different time periods and experience geomorphological forces to differing degrees. Such differences can lead to micro-variability in the physical material that make up these Mars analog sites, thus we aimed to characterize the differences in composition and physical aspects of material between and within these four locations. We selected areas that appeared repetitive and homogeneous from visible satellite and uncrewed aerial vehicle (UAV) imagery, and collected samples over a range of spatial scales (10 cm-1 km). We utilized visible to near-infrared and short-wavelength infrared (VNIR/SWIR) reflectance spectroscopy, X-ray fluorescence (XRF), and measurements of sampled sediment moisture content and grain size to characterize the physical and geochemical properties. VNIR/SWIR spectra contained features consistent with iron-bearing minerals such as pyroxene, basaltic glass and ferric oxides/oxyhydroxides. The two tephra fields had a larger contribution of iron phases compared to the two sandurs, and Holuhraun spectra in particular showed evidence of Fe-bearing glass. Average spectra depicted trends that appear to correlate with location age, including an increase in Fe oxide absorption (0.54 mu m), a shift of the broad absorption at 1.0 mu m to shorter wavelengths, an increase in structural and molecular water at 1.4 and 1.9 mu m, and an increase in the hydroxylated mineral (likely Si-OH) absorption near 2.2 mu m. The bulk geochemical compositions of the four sites were largely undifferentiable within SiO2, Al2O3, MgO, MnO, Na2O, and TiO2, whereas other elements (K2O, CaO, FeO, and P2O5) showed trends that grouped the two northern sites (Dyngjusandur and Holuhraun) and the two southern sites (Maelifellssandur and Fimmvorouhals) together. While there were some differences between the four regions studied, statistical analysis of moisture content, grain size, and summary products derived from VNIR/SWIR data indicate comparable variability in sample geochemical and physical properties up to the 10-m scale, and substantially increased variability at the 100-m and 1-km scales, suggesting that current and future missions in search of biosignatures should target separate sampling areas no more than 10 m apart for repeat measurements of the same material.

The Ultra-Compact Imaging Spectrometer Moon (UCIS-Moon) instrument is a pushbroom shortwave infrared (SWIR) imaging spectrometer prototype developed at NASA’s Jet Propulsion Laboratory (JPL), California Institute of Technology under the Development and Advancement of Lunar Instrumentation (DALI) program. It is designed for integration with a lander or rover for lunar surface science missions. Operating over a 0.6 to 3.6 micron spectral range with 10 nm sampling and a 36 degree field of view, UCIS-Moon is capable of detecting spectral absorptions from common lunar materials, OH species, molecular H2O, water ice, organics, and placing mineral identifications within an established geologic context at the cm to m scale. We discuss instrument assembly, alignment, and measured laboratory optical performance, which meets or exceeds the high-uniformity and high-resolution requirements while achieving a wide spectral range, field of view, and environmental tolerance, with limited mass and power resources. As such, the UCIS-Moon imaging spectrometer is well-suited to address key science questions about lunar geology, the abundance, sources, and sinks of volatiles at the Moon, and the distribution of possible in situ resources for future human exploration.

The Airborne Visible/Infrared Imaging Spectrometer 3 (AVIRIS-3) is the third of the NASA AVIRIS spectrometer series and is being developed in parallel with the Compact Wide-swath Imaging Spectrometer II (CWIS-II) being developed with the University of Zurich, Switzerland. The core spectrometer of AVIRIS-3 is a copy of the optically fast, F/1.8 Dyson imaging spectrometer used by the Earth Surface Mineral Dust Source Investigation (EMIT) that is in development and scheduled for launch to the International Space Station (ISS) in 2022. AVIRIS-3 is intended to provide state-of-the-art imaging spectroscopy measurements for NASA science and application through the next decade and beyond. AVIRIS-3 uses the EMIT spectrometer design interfaced with a scaled two-mirror telescope enclosed in a compact vacuum vessel to enable measurements from airborne platforms ranging from a Twin Otter to a business jet or a NASA ER-2. AVIRIS-3 is a cryogenic instrument with advanced system control and real-time onboard spectroscopic data processing algorithms evolved from AVIRIS-NG. The spectral range of AVIRIS-3 is 380 to 2500 nm with 7.4 nm sampling. The radiometric range is from 0 to max terrestrial Lambertian radiance with higher signal-to-noise ratio performance than AVIRIS-Classic or AVIRIS-Next Generation. The spatial field-of-view is 39.5 degrees with 0.56 milliradian sampling. This paper describes the design and development of AVIRIS-3 and presents its characteristics in comparison to the previous generation imaging spectrometers.

The Permian Basin is the largest and fastest growing oil and gas (O&G) producing region in the United States. We conducted an extensive airborne campaign across the majority of the Permian in September-November, 2019 with imaging spectrometers to quantify strong methane (CH4) point source emissions at facility-scales, including high frequency sampling to evaluate intermittency. We identified 1100 unique and heavy-tailed distributed sources that were sampled at least 3 times (average 8 times), showing 26% average persistence. Sources that were routinely persistent (50-100%) make up only 11% of high emitting infrastructure but 29% of quantified emissions from this population, potentially indicative of leaking equipment that merits repair. Sector attribution of plumes shows that 50% of detected emissions result from O&G production, 38% from gathering and boosting, and 12% from processing. This suggests a 20% relative shift from upstream to midstream compared to other US O&G basins for large emitters. Simultaneous spectroscopic identification of flares found that 12% of detected Permian CH4 plume emissions were associated with either active or inactive flares. Frequent, high-resolution monitoring is necessary to accurately understand intermittent methane superemitters across large, heterogeneous O&G basins and efficiently pinpoint persistent leaks for mitigation.

Snow and ice melt processes are key variables in Earth energy-balance and hydrological modeling. Their quantification facilitates predictions of meltwater runoff and distribution and availability of fresh water. Furthermore, they are indicators of climate change and control the balance of the Earth's ice sheets. These processes decrease the surface reflectance with unique spectral patterns due to the accumulation of liquid water and light absorbing particles (LAP), making imaging spectroscopy a powerful tool to measure and map this phenomenon. Here we present a new method to retrieve snow grain size, liquid water fraction, and LAP mass mixing ratio from airborne and space borne imaging spectroscopy acquisitions. This methodology is based on a simultaneous retrieval of atmospheric and surface parameters using optimal estimation (OE), a retrieval technique which leverages prior knowledge and measurement noise in the inversion and also produces uncertainty estimates. We exploit statistical relationships between surface reflectance spectra and snow and ice properties to estimate their most probable quantities given the reflectance. To test this new algorithm we conducted a sensitivity analysis based on simulated top-of-atmosphere radiance spectra using the upcoming EnMAP orbital imaging spectroscopy mission, demonstrating an accurate estimation performance of snow and ice surface properties. An additional validation experiment using in-situ measurements of glacier algae mass mixing ratio and surface reflectance from the Greenland Ice Sheet yields promising results. Finally, we evaluated the retrieval capacity for all snow and ice properties with an AVIRIS-NG acquisition from the Greenland Ice Sheet demonstrating this approach’s potential and suitability for upcoming orbital imaging spectroscopy missions.

Remote sensing instruments, both aircraft and on-orbit platforms, undergo extensive laboratory calibrations to determine their geometric, spectral, and radiometric responses. Additional in-flight radiometric calibrations can be performed using well-characterized earth targets. The Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign provided such an opportunity when the ER-2 aircraft overflew Railroad Valley on August 13 and 15, 2019. Surface reflectances were available from the August 4, 2019 field team and from the Radiometric Calibration Network (RadCalNet) portal, and spectral aerosol optical depths from an on-site AERosol RObotic NETwork (AERONET) sunphotometer. The Enhanced MODIS Airborne Simulator (eMAS), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), and the “Classic” Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-C) sensors individually performed a vicarious calibration using their respective methodologies and selection of input parameters. A comparison of the at-sensor radiances predicted from these independent analyses highlights some of the uncertainties in the inputs, including choice of solar irradiance model. Although good agreement, within 5%, is found at visible wavelengths, difference can be as large as 15% in the shortwave infrared (SWIR). This highlights the need for the remote sensing community to agree upon a standard solar model, to remove sensor-to-sensor biases derived from in-flight calibrations.

Abstract. In the fall of 2017, an airborne field campaign was conducted from the NASAArmstrong Flight Research Center in Palmdale, California, to advance theremote sensing of aerosols and clouds with multi-angle polarimeters (MAP)and lidars. The Aerosol Characterization from Polarimeter and Lidar (ACEPOL)campaign was jointly sponsored by NASA and the Netherlands Institute forSpace Research (SRON). Six instruments were deployed on the ER-2 high-altitude aircraft. Four were MAPs: the Airborne Hyper Angular RainbowPolarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager(AirMSPI), the Airborne Spectrometer for Planetary EXploration (SPEXairborne), and the Research Scanning Polarimeter (RSP). The remainder werelidars, including the Cloud Physics Lidar (CPL) and the High SpectralResolution Lidar 2 (HSRL-2). The southern California base of ACEPOL enabledobservation of a wide variety of scene types, including urban, desert,forest, coastal ocean, and agricultural areas, with clear, cloudy, polluted,and pristine atmospheric conditions. Flights were performed in coordinationwith satellite overpasses and ground-based observations, including theGround-based Multiangle SpectroPolarimetric Imager (GroundMSPI), sunphotometers, and a surface reflectance spectrometer. ACEPOL is a resource for remote sensing communities as they prepare for thenext generation of spaceborne MAP and lidar missions. Data are appropriatefor algorithm development and testing, instrument intercomparison, andinvestigations of active and passive instrument data fusion. They are freelyavailable to the public. The DOI for the primary databaseis https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/DATA001 (ACEPOL Science Team, 2017), whilefor AirMSPI it is https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006 and https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/TERRAIN_V006 (ACEPOL AirMSPI 75 Science Team, 2017a, b). GroundMSPI data are at https://doi.org/10.5067/GROUND/GROUNDMSPI/ACEPOL/RADIANCE_v009 (GroundMSPI Science Team, 2017). Table 3 lists further details of these archives.This paper describes ACEPOL for potential data usersand also provides an outline of requirements for future field missions withsimilar objectives.

Vicarious calibration methods use well-characterized surface sites to complement other on-orbit radiometric calibration techniques. Since 2009, NASA’s Orbiting Carbon Observatory-2 (OCO-2) and Japan’s Greenhouse gasses Observing SATellite teams have conducted annual campaigns at Railroad Valley, NV, USA, for this purpose. These sensors pose special challenges due to their large footprint sizes and view angles. OCO-2 sweeps the playa surface during a targeted overpass of the test site, and records data at a number of viewing angles. The smallest of these is selected for processing, thereby minimizing the off-nadir correction. Surface reflectances at nadir are recorded by the field team, and the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product is used to provide the small, off-nadir correction. Another MODIS product, the Level 1B top-of-atmosphere radiance product, is used to validate the results and to provide input into the OCO-2 calibration uncertainty estimate. From 11 experiments, the ratio of radiances reported by the OCO-2 Level 1B data product to those from the field campaigns is 1.01, 1.04, and 1.01 for the three OCO-2 spectral bands. These analyses validate the data product absolute calibration, to within the 5% requirement. The need for executing these experiments will be of continued importance to OCO-3. This sensor has an on-board calibrator that provides a dark signal and lamps for response trends but does not have the on-board solar-diffuser present on OCO-2, and thus cannot track degradations relative to the Sun.

To date, a large number of existing applications in India have used multi-band observations from airborne and spaceborne platforms.New sensors are providing additional capabilities thanks to special aerial missions with the compact airborne spectrographic imager (CASI), the short-wave infrared (SWIR) full spectrum imager (SFSI) and the National Aeronautics and Space Administration's (NASA's) Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG).Opportunities to exploit quantitative spectroscopic signatures and high spatial resolution have garnered great interest among the scientific community, and the success of these missions will rely on accurate calibration.Here we focus on a vicarious calibration experiment conducted for the AVIRIS-NG India campaign.We discuss initial validation results, with descriptions of in situ and remote calibration and measurement protocols, geometric processing with precise position and attitude data, and atmospheric simulations used to validate the remote measurement.A partnership between Indian Space Research Organisation (ISRO) and NASA investigators proved a unique opportunity to assess the empirical variability in results, indicating their sensitivity to modelling choices and assumptions.The vicarious calibration exercise uses multiple radiative transfer models, including MODTRAN 6.0 and a new version of the 6S radiative transfer code, viz.6SV2.1, which is capable of accounting for polarization.

We describe advanced spectral and radiometric calibration techniques developed for NASA's Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). By employing both statistically rigorous analysis and utilizing in situ data to inform calibration procedures and parameter estimation, we can dramatically reduce undesirable artifacts and minimize uncertainties of calibration parameters notoriously difficult to characterize in the laboratory. We describe a novel approach for destriping imaging spectrometer data through minimizing a Markov Random Field model. We then detail statistical methodology for bad pixel correction of the instrument, followed by the laboratory and field protocols involved in the corrections and evaluate their effectiveness on historical data. Finally, we review the geometric processing procedure used in production of the radiometrically calibrated image data.

Vicarious calibration is the determination of an on-orbit sensor’s radiometric response using measurements over test sites such as Railroad Valley (RRV), Nevada. It has the highest accuracy when a remote sensor’s view angle is aligned with that of the surface measurements, namely at a nadir view. For view angles greater than 10°, the dominant error is the uncertainty in the off-nadir correction factor. The factor is largest in the back-scatter principal plane and can reach 20%. The Orbiting-Carbon Observatory has access to a number of datasets to determine this deviation. These include measurements from field instruments such as the Portable Apparatus for Rapid Acquisition of Bidirectional Observation of the Land and Atmosphere (PARABOLA), as well as satellite measurements from Multi-angle Imaging SpectroRadiometer (MISR) and MODerate resolution Imaging Spectroradiometer (MODIS). The correction factor derived from PARABOLA is consistent in time and space to within 2% for view angles as large as 30°. Field spectrometer data show that the correction term is spectrally invariant. For this reason, a time-invariant model of RRV surface reflectance, along with empirically derived coefficients, is sufficient to use in the calibration of off-nadir sensors, provided there has been no recent rainfall. With this off-nadir correction, calibrations can be expected to have uncertainties within 5%.

We present a new method for atmospheric correction of remote Visible Shortwave Infrared (VSWIR) imaging spectroscopy. Our approach fits a combined model of atmospheric scattering, absorption, and surface reflectance across the solar reflected interval from 380 to 2500 nm. This can estimate spectrally-broad atmospheric perturbations such as aerosol effects that are difficult to retrieve with narrow spectral windows. A probabilistic formulation from Optimal Estimation inversion theory accounts for uncertainties in model parameters and measurement noise. This paper presents a field experiment using NASA's Next Generation Visible/Near Infrared Imaging Spectrometer (AVIRIS-NG) with analysis of retrieval accuracy and information content. The inversion outperforms traditional approaches, achieving mean reflectance accuracy of 1.0% on diverse validation surfaces. Predicted posterior distributions fully explain the observed discrepancies, demonstrating the first closed uncertainty budget for VSWIR imaging spectrometer atmospheric correction. This shows the potential of combined surface/atmosphere fitting to advance the accuracy and statistical rigor of remote reflectance measurements.