The Compact Wide Swath Imaging Spectrometer II (CWIS-II) is an imaging spectrometer built, tested, calibrated, and delivered for the University of Zurich (UZH). CWIS-II will be integrated into an aircraft for Earth science research, algorithm development, and satellite calibration and validation. CWIS-II’s two-mirror telescope and Dyson-type spectrometer are optically fast (F/1.8), span a wide swath (40.2-degree field of view over 1240 spatial pixels), record data at 216 frames per second, and operate over the 380-2500 nm solar-reflected spectrum with 7.4 nm spectral sampling. This work describes the CWIS-II instrument configuration, optical alignment process, and present final laboratory spectral and spatial performance.

The High-resolution Volatiles and Minerals Moon Mapper (HVM³) is a pushbroom shortwave infrared (SWIR) imaging spectrometer developed at NASA’s Jet Propulsion Laboratory (JPL), California Institute of Technology, for the Lunar Trailblazer mission. The mission, a part of NASA’s Small Innovative Missions for Planetary Exploration (SIMPLEx) program, pairs HVM³ with University of Oxford’s Lunar Thermal Mapper (LTM) to determine the form, abundance, and distribution of water on the Moon, while providing a potential reconnaissance opportunity for future landed missions. The HVM³ optical design utilizes heritage from NASA’s Moon Mineralogy Mapper (M³), and maintains a compact form while extending to longer wavelengths. Operating at F/3.4 with a spatial resolution of 70 meters per pixel and a spectral resolution of 10 nm over the 0.6 to 3.6 microns spectral range, HVM³ is optimized for the detection of volatiles to map OH, bound H2O, and water ice at the Moon, including the Moon’s permanently shadowed regions (PSRs). We discuss the optical specifications, optical design, alignment, and initial measured laboratory performance of the HVM³ instrument.

The Visible Mid-wave Dyson Imaging Spectrometer (VMDIS) is a JPL-developed prototype instrument whose main goal is to address three key technical challenges for the next generation of imaging spectrometers for solar system exploration: (1) High signal-to-noise ratio (SNR) measurements for mapping of minerals and volatiles on solar system targets including comets, asteroids, rocky moons, icy moons, and planets especially Mars; (2) Miniaturization for low-cost mission platforms (reducing the size, mass, and power requirements compared to current options); and (3) excellent spectral cross-track and spectral-spatial uniformity required by todays advanced algorithms for rigorous quantitation with uncertainties. The core of VMDIS is the imaging spectrometer instrument: an optically fast F/1.8 Dyson imaging spectrometer covering a spectral range from 600 nm to 3600 nm, with a spectral sampling of 7 nm. Different telescopes can be used with different implementations of VMDIS to tailor the IFOV and FOV of the instrument. With its prototype telescope, the instrument enables a field of view (FOV) of 28°, with an instantaneous FOV of 0.5 milliradians subtended by each 18 μm cross-track pixel. The size of the VMDIS prototype including the telescope and heritage electronics is roughly equal to 3U (3 units – 1 unit measuring approximately 10×10×10 cm), with a mass < 8 kg and payload power < 40 W. With next generation electronics in development this mass falls below 3 kg. We present an overview of the optical, mechanical, and thermal design of VMDIS, which is required to fabricate this instrument within very demanding resource allocations. The design of the signal chain electronics is also detailed. In addition, preliminary alignment, characterization, and calibration measurements, obtained with the instrument operating in relevant space-type environment, are also discussed. While tested with an available 30-μm detector array, VMDIS is designed for a 18-μm digital readout detector array. VMDIS is intended to pave the way for future low-cost, small form factor imaging spectrometers with state-of-the-art performance in terms of combination of spectral range, high throughput, exceptional uniformity, as well as configuration flexibility for both orbital and landed mission, for the next decade and beyond.

The Carbon Plume Mapper (CPM) instrument is a high-fidelity imaging spectrometer developed to pinpoint, quantify, and track methane (CH4) and carbon dioxide (CO2) point source emissions to help enable reduction of greenhouse gases in the Earth’s atmosphere. CPM will operate over the spectral range of 400 – 2500 nm with a spectral sampling of 5.0 nm. CPM will be integrated into an industry partner spacecraft bus and launched into low-Earth orbit (LEO). The optical design comprises a three-mirror anastigmat (TMA) telescope and Dyson form spectrometer which reduces volume and mass for a fast (F/1.8) optical system. An overview of the CPM optical design, development, and current status is discussed.

In 1996, the original HEIFTS paper described a totally new FT imaging spectrometer with no moving parts. Papers in 1997 and 2000 followed. In 1998 US US granted Patent #5,777,736, covering the device’s unique optical geometry and data reduction scheme. Light interfering at the image plane need not come from a single aperture. Two new geometries are proposed. The first uses light from two separate but identical objectives. The second uses light from a single objective split by mirrors situated at a pupil image. The physics of the original device will be reviewed and specific examples of the two new optical geometries.

We describe newly developed voltage-tunable lithium-niobate (LiNbO3) Fabry-Perot etalons for solar near-infrared filtergraph. Two etalons were fabricated for tandem use: One etalon is 0.9 mm thick and the other is 1.2 mm thick, optimized in ordinary ray transmission for both He I 1083.035 nm and magnetic sensitive Fe I 1564.85 nm lines. The etalons are Y-cut lithium-niobate wafers coated with highly reflective and conductive (ITO) layers. We examined optical and voltage-tunable properties of the etalons using the horizontal spectrograph of the Domeless Solar Telescope at Hida Observatory, Kyoto University. Some solar observations with tandem etalons were also ran and their good imaging quality was demonstrated. Some results from the measurements are reported.

JPL's Hyper-Spectral Thermal Emission Spectrometer (HyTES) is an airborne imaging spectrometer with 256 spectral bands in the Thermal Infrared (TIR) wavelength region and 512 spatial pixels across track. It was designed to image the ground with each spatial pixel capturing a high-resolution spectrum of light over the full 7.5 to 12 µm spectral range. HyTES is now using a new detector technology. The sensor is characterized with the new detector and results from a recent campaign are discussed. Data included enhanced methane detection from permafrost in Sweden as well as angular land surface temperature (LST) measurements in controlled agricultural sites.

Hyperion is a Far-UV (FUV) mission that investigates the birth clouds of stars by probing the nature, extent, and state of H2 at the crucial atomic-to-molecular interstellar medium boundary layer. Hyperion examines the fuel for star formation directly by observing the molecular interface between dense, star-forming clouds, the diffuse interstellar environment, and the stars that arise from these regions. Hyperion observes over the 138.5-161.5 nm spectral range with resolution greater than R==50,000. Mapping faint clouds over large areas of sky requires an efficient, high-etendue spectrometer. Conventional cross-dispersed Echelle spectrometers suffer from low efficiency (due to the need for a cross-disperser) and limited etendue due to the aberration correction. We describe an efficient high-etendue spectrometer approach that uses a single grating and a 64 mega-pixel array. The spectrometer is a compact f/5 Offner derivative with free-form surfaces and a single diffraction grating.

Multispectral imaging is an attractive sensing modality for small unmanned aerial vehicles (UAVs) in numerous military and civilian applications such as reconnaissance, target detection, and precision agriculture. Cameras based on patterned filters in the focal plane, such as conventional colour cameras, represent the most compact architecture for spectral imaging, but image reconstruction becomes challenging at higher band counts. We consider a camera configuration where six bandpass filters are arranged in a periodically repeating pattern in the focal plane. In addition, a large unfiltered region permits conventional monochromatic video imaging that can be used for situational awareness (SA), including estimating the camera motion and the 3D structure of the ground surface. By platform movement, the filters are scanned over the scene, capturing an irregular pattern of spectral samples of the ground surface. Through estimation of the camera trajectory and 3D scene structure, it is still possible to assemble a spectral image by fusing all measurements in software. The repeated sampling of bands enables spectral consistency testing, which can improve spectral integrity significantly. The result is a truly multimodal camera sensor system able to produce a range of image products. Here, we investigate its application in tactical reconnaissance by pushing towards on-board real-time spectral reconstruction based on visual odometry (VO) and full 3D reconstruction of the scene. The results are compared with offline processing based on estimates from visual simultaneous localisation and mapping (VSLAM) and indicate that the multimodal sensing concept has a clear potential for use in tactical reconnaissance scenarios.

We explore some variants of “Gaussianization” for characterizing the distribution of background pixels in multi-spectral and hyperspectral imagery, and then use this characterization to develop algorithms for target detection. We consider two very different problems – anomalous change detection and gas-phase plume detection – as ways to explore the applicability of Gaussianization for remote sensing image analysis. One variant is an extension of the Gaussianization concept to non-Gaussian reference distributions, and in particular, we show that using the multivariate t as the reference distribution often leads to better target detection performance. Since we are no longer, strictly speaking, Gauss-ianizing, we call the method iterative rotation and remarginalization. In our scheme, the remarginalization is achieved with a parametric transformation function that is built up from a linear basis of (hard or soft) hinge functions, which provide explicitly differentiable and enforcably monotonic remarginalization functions. An efficient knot-pruning strategy enables rapid training of these functions. Also, for remote sensing imagery with many spectral channels, we have found it advantageous to pre-whiten the data with axes aligned to principal components, and then selectively to Gaussianize only the top principal components, treating the lower-variance directions as “already Gaussian.” This provides a computationally faster and empirically more effective Gaussianization for spectral imagery.

Target detection under poorly illuminated conditions or in shadows is a challenging problem due to low signal and strong atmospheric scattering relative to well-illuminated pixels. We will use The Monte Carlo Scene (MCScene), a high fidelity and radiometrically accurate ray tracing model, to simulate targets in shadow and explore the parameter space that effects target detectability including variable illumination intensity and target spectral characteristics. An advantage of using MCScene for this type of simulation is that atmospheric effects, including the strong wavelength dependent aerosol scattering that contributes to diffuse illumination in shadows, are properly modeled.

Systems modeling of hyperspectral instruments is effective for forecasting instrument performance of subpixel target detection. A new reconfiguration of the statistical model-based tool FASSP (Forecasting and Analysis of Spectroradiometric System Performance) is currently in development at the Rochester Institute of Technology, for purposes of exploring systems limitations in subpixel detection. To validate the baseline functioning of the statistical model, empirical analyses using real data were cross-examined with model predictions. The real data were collected from a field experiment using a hyperspectral sensor on-board an unmanned aerial system (UAS). To assist in model validation, a variety of novel subpixel targets, spanning a range of constant target percentages, were designed and deployed in the field. The UAS was advantageous in enabling the research team to maintain full end-to-end control of the system parameters within the experiment. This includes selecting specific flight lines, collecting ground truth spectral measurements, deploying specific targets, and processing raw data into geophysical units of surface reflectance. The study revealed close alignment between the empirical results and modeled predictions.

The IEEE P4001 Hyperspectral Standard concluded the first draft of its initial standard as of December 2021. The document is under formal review now by IEEE and will be heading to general voting in 2022 with potential for publication in 2023. This talk will give an overview of the radiometric, spectral, spatial, data structures, terminology and verification testing that was done as the final push to finish the work.

Modeling and simulation of imaging systems is a critical capability used throughout the lifetime of a remote sensing system. Simulating HSI systems is challenging because the mathematical methods and models used for a normal PAN or MSI system with filters cannot be used, as the vast shape diversity of the Point Spread Function (PSF) across the image plane prevents the use of an Optical Transfer Function (OTF). Provided that the HSI system satisfies the condition t_int∆f ≫ 1, where t_int is the integration time and ∆f is the channel bandwidth, one can avoid the complexities of partial coherence and add intensities at the focal plane. For every sub-sampled wavelength and sub-sampled location in the image plane, a unique superposition PSF needs to be computed. This requires optimized GPU CUDA kernels running in a high performance computing environment controlled with Message Passing Interface (MPI). The simulation is broken into five key steps: (1) creation of EAR hyper-cubes for each step of the CONOPS using RIT's Digital Imaging and Remote Sensing Image Generation (DIRSIG), (2) GPU accelerated Fourier Optics propagation to create superposition kernels derived from local PSFs, (3) application of the kernels to the processed DIRSIG hyper-cubes using superposition integration, (4) simulation of Focal Plane Array (FPA) detector properties, and (5) assembling the final hyper-cube image and metadata from the sequence of FPA data sets.

The HyperSpectral Imager for Climate Science (HySICS) is the core instrument of the CLARREO Pathfinder (CPF) mission and scheduled to be launched to the International Space Station (ISS) in 2023. HySICS is an Offner-Chrisp imaging spectrometer designed to meet an unprecedented radiometric uncertainty requirement of 0.3% (k=1) across its 350-2300 nm spectral range. The requirement represents a need for significant improvement over the radiometric calibration (RadCal) of existing space-borne spectrometers. The strategy to demonstrate that HySICS achieves this level of uncertainty includes an Independent Calibration (IndCal) using a pre-launch, detector-based RadCal relying on a tunable laser source. The system planned for the IndCal is the Goddard Laser for Absolute Measurement of Radiance (GLAMR) that has been developed at NASA’s Goddard Space Flight Center and used recently in the absolute radiometric calibration of several multi-spectral instruments. GLAMR data from a calibration demonstration system developed for the CLARREO mission have been combined with HySICS characterization data to develop an imaging spectrometer model that simulates HySICS’ behavior. The goal of the HySICS instrument and GLAMR model is to prepare for GLAMR testing of HySICS, optimize the test configuration, and verify the RadCal error budget. A Monte-Carlo simulation of the GLAMR RadCal based on the model is conducted to predict the detectors’ outputs at miscellaneous testing parameters. The main application of the simulation is a sensitivity study through the tuning of these parameters to identify the calibration error sources and determine quality metrics that can define the need for repeat HySICS measurements. The HySICS instrument model developed will be maintained and improved to support the CPF IndCal.

DMSAT-1 (Dubai Municipality Satellite) is a high-performance small microsatellite designed to perform multi‐spectral observations in visual and near-infrared bands for aerosol and greenhouse gas monitoring. DMSAT-1 has two independent telescopes (one with 0-degree polarization and the second with 90-degree polarization) each containing a linear polarizer. The polarizers are mounted perpendicularly. DMSAT-1 captures images in three bands – Blue, Red, and Near-Infrared. This paper puts forward customized algorithms for Mohammed Bin Rashid Space Centre (MBRSC), which are developed in Python for radiometric validation and tested on images captured by the primary instrument (polarimeters) on the DMSAT-1 microsatellite. Radiometric validation includes the validation of the Signal-Noise Ratio, Non-Uniformity Correction, and Modulation Transfer Function of the images. The proposed method validates the images across different bands as well as different polarizers and confirms that satellite images can be readily used.

Identifying methane gas emissions sources is crucial to the mitigation of greenhouse gas emissions, and hyperspectral imagery is effective at methane leak detection. Hyperspectral sensors in both the shortwave infrared (SWIR) and longwave infrared (LWIR) can detect methane plumes, but surface background and atmospheric conditions cause methane detectability to vary depending on the sensor’s spectral region. This study compared methane detectability under varying background conditions for two airborne hyperspectral sensors: AVIRIS-NG in the SWIR, and HyTES in the LWIR. The trade study modeled methane plumes under a wide variety of conditions by making use of synthetic images generated using MODTRAN radiance curves, and applying a matched filter for methane detection. The modeling method was validated through comparison with real AVIRIS-NG and HyTES data. In the SWIR, the factors which most strongly influenced methane detectability were surface reflectance of the background and surface reflectance directly underneath the methane plume. In the LWIR, the temperature of the methane plume and the temperature of the surface had the highest impact on methane detection. We computed the specific boundaries on these conditions which make methane most detectable for each instrument. The results of this trade study can help inform decision making about which sensors are most useful for various methane studies, such as leak detection, plume mapping, and emissions rate quantification.

While the concentrations of trace gases in Earth’s atmosphere were roughly constant for thousands of years, human activities such as the burning of fossil fuels have caused significant changes ever since the industrial revolution. The remote sensing of trace gases has proved to be a useful technique for mapping and monitoring on the global scale. We introduce a novel snapshot imaging instrument concept for measuring trace gases that is compact and lightweight compared to current state-of-the-art instruments. It uses polarization optics to create a spectral filter that turns the molecular absorption strength of a gas into a linear polarization signal. By measuring this signal with a polarization camera based on a beamsplitter or a micropolarizer array, the linear fractional polarization is retrieved instead of a full spectrum for every spatial resolution element which greatly reduces the sampling requirements for such an instrument. The combination of a linear polarizer, multiple-order retarder and quarter-wave plate make it possible to measure the complete fractional linear polarization, which is linearly related to the absorption strength of the trace gas in the instrument’s field of view. While only 2 channels (in/out of phase) are necessary to get a valid gas measurement, a polarization camera based on a pixelated micropolarizer array measures in quadrature, making this instrument robust in case of spectral filter instability issues. In this study, we present simulations and performance optimizations of the instrument concept as well as plans for laboratory measurements that demonstrate its functionality. Simulations based on NO₂ at 400 - 500 nm demonstrate proof of principle, and constitute the basis of an optimization of the spectral filter consisting of a custom design for measuring NO₂ in a gas cell by including custom band-pass filter and multiple-order retarder. We are constructing the first prototype called GasCam using off-the-shelf components for laboratory measurements. Both the simulations and laboratory measurements are fundamental steps to the realization of a ground- and/or space-based instrument network in the future.

The continuous monitoring of methane emissions from oil and gas infrastructure is low-hanging fruit in the effort to combat climate change and one way to address this is with low-cost, installed imaging systems. One such system completed comprehensive field testing in 2021 at the Methane Emissions Technology Evaluation Center (METEC) at Colorado State University. Here we present test procedures and blind test results from a novel scanning, multispectral imaging instrument. We address the multivariate nature of the detection classification task and present a sensitivity analysis against wind speed, range to the leak source and SNR of the imaging instrument.

This PDF file contains the front matter associated with SPIE Proceedings Volume 12235 including the Title Page, Copyright information, Table of Contents, and Conference Committee Page.