The Airborne Visible/Infrared Imaging Spectrometer-4 (AVIRIS-4) represents the next generation in the series of airborne imaging spectrometers built by NASA JPL. Commissioned by the Swiss ARES research consortium, AVIRIS-4 is geared towards delivering cutting-edge imaging spectroscopy data for scientific and practical applications as a replacement for its predecessor APEX. AVIRIS-4 is based on a Dyson-type imaging spectrometer design, also employed by NASA-operated AVIRIS-3 and EMIT, and integrates a scaled two-mirror telescope housed in a compact vacuum vessel. This enables airborne measurements in unpressurized aircraft at altitudes ranging from 500 m to 7620 m, achieving image resolutions between 0.3 and 4.5 m with a field of view of 40.2° in 1241 spatial pixels. AVIRIS-4 surpasses previous state-of-the-art sensor heads in signal-to-noise ratio performance and features a spectral range of 375 to 2504 nm and 7.4 nm spectral sampling. The operation, data capture and mission control hardware as well as the calibration and data processing software is developed by UZH, EPFL, and ZHAW. This paper outlines the design and calibration strategies implemented in AVIRIS-4’s development and highlights its performance during its first year of operation in 2024.

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.

Earth and planetary sciences often rely upon the detailed examination of spectroscopic data for rock and mineral identification. This typically requires the collection of high resolution spectroscopic measurements. However, they tend to be scarce, as compared to low resolution remote spectra. This work addresses the problem of inferring high-resolution mineral spectroscopic measurements from low resolution observations using probability models. We present the Deep Gaussian Conditional Model, a neural network that performs probabilistic super resolution via maximum likelihood estimation. It also provides insight into learned correlations between measurements and spectroscopic features, allowing for the tractability and interpretability that scientists often require for mineral identification. Experiments using remote spectroscopic data demonstrate that our method compares favorably to other analogous probabilistic methods. Finally, we show and discuss how our method provides human-interpretable results, making it a compelling analysis tool for scientists.

With the advent of existing high resolution spectrometers in space (GOSAT, GOME-2, OCO-2), global observations of solar induced chlorophyll fluorescence (SIF) became feasible for the first time. The potential of SIF is to provide an independent and more direct proxy for photosynthetic activity and, depending on retrieval methodology, be less susceptible to atmospheric scattering. Empirically, strong linear correlations between SIF and gross primary production (GPP) have been shown in several studies, albeit with somewhat different slopes per biome type. Here, we show the first full year of data acquired by the Orbiting Carbon Observatory-2, which provides unprecendendet spatial resolution (1.3·2.3 km), data volume (more than 1 million measurements per day) and signal-to-noise ratios (>500). In addition, we show the first direct validation of space-based OCO-2 SIF measurements using the newly built Chlorophyll Fluorescence Imaging Spectrometer (CFIS), an imaging spectrometer optimized for SIF retrievals and OCO-2 validation. To conclude, we will present a new ground-based measurement system developed by UCLA for long term observations of SIF at ground-based stations.

The Orbiting Carbon Observatory (OCO) by NASA's Jet Propulsion Laboratory (JPL) and Greenhouse gases Observing SATellite (GOSAT) by JAXA were built to provide independent measures of the global distributions of carbon dioxide (CO2) from space. GOSAT achieved a successful orbit on January 23, 2009, and OCO failed its launch attempt on February 24, 2009. Both sensors detect absorptions at the 0.76-¿m oxygen band and at the weak and strong CO2bands at 1.6 and 2.0 ¿m, respectively. In order to establish the uncertainties and biases between the respective data products, the OCO and GOSAT teams have planned a number of cross-comparison studies. The first of these, discussed here, is the validation of the prelaunch absolute radiometric calibrations, specified at ±5%. The cross-comparison campaign to validate this OCO approach was performed at NASA's JPL in April 2008. In this paper, the OCO reference detectors and three GOSAT radiometers viewed the OCO sphere and radiometric standard. The overall agreements between the OCO calibration and GOSAT measurement of the OCO integrating sphere were 1.5% at 0.76 ¿m, 2.7% ± 1.1% at 1.6 ¿m, and 0.2% ± 4.1% at 2.0 ¿m. To validate the GOSAT preflight calibration, the cross-calibration experiment continued at JAXA's Tsukuba Space Center in December 2008, where the same radiometers measured the two GOSAT spheres. Agreements are better than 1.8% at 0.76 ¿m, 1.6% at 1.6 ¿m, and 1.4% at 2 ¿m. These studies give confirmation that the flight instruments have been calibrated to within their uncertainty requirements.

As part of NASA's Instrument Incubator Program (IIP), we have been developing enabling technologies for the Multiangle SpectroPolarimetric Imager (MSPI), a candidate instrument for the Aerosol-Cloud-Ecosytem (ACE) mission. ACE is one of several satellite concepts identified in the 2007 National Research Council Earth Sciences Decadal Survey. MSPI is a multiangle, multispectral, high-accuracy polarization imager, and is envisioned to contain multiple cameras pointed at different viewing angles, with intensity imaging in several spectral bands between the ultraviolet and shortwave infrared, and accurate polarimetric imaging in a subset of the bands. To achieve a degree of linear polarization (DOLP) uncertainty of 1%, we temporally modulate the linear-polarization component of the incoming light at a rapid rate, enabling each detector within a focal-plane array-combined with polarization analyzers-to measure the relative proportions of the linear Stokes components Q or U to the total intensity I. Our system uses tandem photoelastic modulators (PEMs) within a reflective camera design. We report on the status of our prototype camera development, with particular emphasis on theoretical and experimental work on the required and measured performance of optical elements within the system including: the spectropolarimetric filters, quarter wave plates, and tandem PEMs. We also report on the end-to-end measurement and calibration of camera polarization aberrations using a custom polarization state generator (PSG). Careful design and control of scattered light enables the PSG to generate polarization states between DOLP of 0.07% and 40% with an uncertainty of 0.05%, making it a precision tool for polarimetric calibration and validation of MSPI.