Wildfires increasingly endanger people and property due to the growing population in the wildland urban interface, drought, and climate change. In the United States in 2023 over 1,000,000 acres burned in the western CONUS with no fire encompassing over 100,000 acres. Also, tragically the Lahaina Fire in Hawaii caused the deaths of over 100 people. In Canada, the extreme 2023 fire season resulted in almost 18,500,000 hectares burned, which was a factor of 2.6 larger than the previous high in 1995. The economic losses are enormous with resource expenditures running into the billions and insured losses running into the tens of billions of dollars in the United States. We propose the application of an imaging spectrometer for pre- and post-fire assessments and fire detection. MIT Lincoln Laboratory has developed three critical technologies that are applicable to the wildfire problem. The first is a compact spectrometer, the Chrisp Compact VNIR/SWIR Imaging Spectrometer (CCVIS), that can be modularly implemented for a wide-field imaging spectrometer. The second is the digital focal plane array (DFPA) technology with different detector materials, such as InGaAs or Mercury Cadmium Telluride (MCT), and extremely large well depths exceeding 108 electrons. The DFPA is critical for this application since traditional FPAs will saturate even for relatively cool fires with small spatial sample fill fractions. The DFPA also has sufficient signal to noise performance for pre- and post-fire products such as canopy cover, fuel quantification, and burnt area quantification and monitoring. The third is the TeraByte InfraRed Delivery (TBIRD) space-to-ground optical link that has a maximum data rate of 800 Gbps, which will not be addressed here. A small satellite implementation in a low Earth orbit (similar to 450 km) will have an entrance pupil on the order of 10 cm for a 50 m ground sample distance (GSD).

Methane is a greenhouse gas that has a global warming potential (GWP) of 25 relative to carbon dioxide (CO2). In 2021 an estimated 36 billion-tons of CO2 and 640 million-tons (16 billion-tons GWP equivalent) of methane were emitted. Emission consists of anthropogenic and naturally occurring sources with natural emissions accounting for 35-50% of total emissions. Natural emission caused by decaying organic matter in wetlands and melting tundra, increase as global temperatures rise, thus creating a positive feedback loop increasing their significance and exacerbating global warming. Effective mapping of natural emissions requires high field-of-view (FOV) global satellite coverage. Detection of small weak sources and mapping of larger plume nonuniformity requires a small ground-sample-distance (GSD). Methane has several fine spectral features in the SWIR allowing for effective detection and quantification. Methane concentrations can be retrieved by finding the atmosphere that provides the smoothest retrieved ground reflectance, thus fully removing the absorption features of the gas. The retrieval technique uses the uniform background assumption, which assumes that scattered radiance from pixels adjacent to the pixel of interest (POI) share the same material. While scattering is diminished in the short-wave-infrared (SWIR), methane retrieval accuracy will still be affected when there is significant background and POI contrast and the distance of adjacent scattered radiance entering the POI far exceeds the pixel GSD. In this paper we study the effects of the scattered adjacent radiance on retrieval, based on GSD, background and POI reflectance contrast, and the amount of scattering with varying aerosol loading.

The Chrisp Compact Visible-SWIR Spectrometer (CCVIS) was developed by MIT Lincoln Laboratory as a high performance, low Size-Weight-Power (SWAP) slit-based hyperspectral sensor that provides comparable performance to current fielded units but more than an order smaller in packaging volume. The design takes advantage of a flat, immersed grating and a color-corrected catadioptric layout to provide >25mm slit length operating from 380-2500nm. We show results from our efforts to design and build an environmentally robust variant which undergoing Technology Readiness Level 6 testing for future spaceflight.

The HyperSpectral Imager for Climate Science (HySICS) is the sensor payload for the Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission. It is scheduled to be launched to the International Space Station for its operational mission. HySICS, an Offner-Chrisp imaging spectrometer, is designed to measure spectral reflectance of the Earth across the full reflective solar region of 350-2300 nm at a radiometric uncertainty requirement of 0.6% (k=2), representing a nearly threefold improvement over existing space-borne spectrometers. An independent calibration (IndCal) approach that relies on a pre-launch, detector- based, absolute radiometric calibration (RadCal) with a transfer to orbit using a high-fidelity instrument model will be used to demonstrate that HySICS meets this level of uncertainty. The activities, plans, procedures, personnel, facilities, and equipment needed for a successful pre-launch IndCal testing, in which the instrument's absolute spectral responses (ASRs) are measured by the Goddard Laser for Absolute Measurement of Radiance (GLAMR), are documented in this paper. A Monte-Carlo simulation of the GLAMR testing is run to predict the instrument's outputs, to identify the calibration error sources and verify the error budget. The trades between the various testing needs of the GLAMR calibration are presented. The resulting test plan is shown that was developed based on the modeling to fit within the testing schedule while optimizing the science needed for CPF0s inter-calibration, spectral line shape assessments, and accuracy of the independent calibration. The HySICS GLAMR testing marks the first application of the detector-based absolute radiometric calibration to an operational space-borne imaging spectrometer.

The study of aquatic ecosystems is an important research area addressing diverse problems such as carbon sequestration in coastal margins and wetlands, kelp and seagrass studies, coral reefs, harmful algal blooms and hypoxia, and carbon cycling in this dynamic environment. The application of an imaging spectrometer to aquatic ecosystem study is particularly challenging due to low water-leaving radiance levels adjacent to the shore region with its higher values. The Committee on Earth Observation Satellites (CEOS) has established more stringent performance standards for the visible/near infrared wavelengths than are typically available in imaging spectrometer designs. We have recently developed a compact form imaging spectrometer, the Chrisp Compact VNIR/SWIR Imaging Spectrometer (CCVIS), that facilitates their modular usage with a wide field telescope without sacrificing performance. The CCVIS design and the operational concept have predicted performance that approaches the CEOS standards. The envisioned satellite implementation requires a pitchback maneuver where the imaging of the slit projected onto the surface is slowly scanned while recording focal plane array readouts at a higher rate thereby avoiding saturation over the land surface while obtaining a high signal-to-noise ratio over the water. The effective frame rate is determined by the time it takes to scan the projected slit one ground sample distance (GSD). This approach has the added benefit of measuring a range of angles during a single GSD acquisition, providing insight into the bidirectional reflectance distribution function (BRDF).

Methane is a greenhouse gas that has a global warming potential (GWP) of 25 relative to carbon dioxide (CO2). In 2021 an estimated 36 billion-tons of CO2 and 640 million-tons (16 billion-tons GWP equivalent) of methane were emitted. Emission consists of anthropogenic and naturally occurring sources with natural emissions accounting for 35-50% of total emissions. Natural emission caused by decaying organic matter in wetlands and melting tundra, increase as global temperatures rise, thus creating a positive feedback loop increasing their significance and exacerbating global warming. Effective mapping of natural emissions requires high field-of-view (FOV) global satellite coverage. Detection of small weak sources and mapping of larger plume nonuniformity requires a small ground-sample-distance (GSD). Methane has several fine spectral features in the SWIR allowing for effective detection and quantification. In this paper we design an imaging spectrometer for single pixel methane quantification using a tradeoff study between spectral resolution and sensor SNR. Increases in spectral resolution increase spectral separability of methane from other gases, while decreasing SNR. Increases in GSD increase SNR and FOV, while reducing spatial resolution. Environmental factors such as water absorption and ground reflectance further affect performance. Retrieval performance was tested with simulated noisy at-aperture radiance spectra using a dry vegetation surface, atmospheres with varying water and methane concentrations, and the developed sensor model. Gas concentrations were retrieved by finding the atmosphere providing the smoothest retrieved reflectance. Retrieval errors were studied to find the optimal sensor parameters. Several future and current imaging spectrometers were used for comparison.

Prelaunch absolute, SI-traceable radiometric calibration of satellite-based sensors is key to ensuring the utility of imaging spectrometer-based data products. The development of detector-based calibration techniques leads to the feasibility of meeting the 0.3% uncertainty level needed to provide climate quality data sets. Detector-based calibration is a method in which a well-understood and stable transfer radiometer is calibrated in a standards laboratory to SI-traceable standards, and transported to a facility calibrating a sensor of interest. The transfer radiometer provides the calibration of the source used in the radiometric calibration. A detector-based calibration approach is part of the prelaunch calibration of the CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF) sensor with the Goddard Laser for Absolute Measurement of Radiance (GLAMR) system. The SI-traceability of GLAMR is through the electric watt as part of the absolute radiometric calibration of the detectors at the National Institute of Standards and Technology using the Primary Optical Watt Radiometer. The current work uses GLAMR data collected with a visible and near-infrared imaging spectrometer calibration demonstration system to develop a source/sensor modeled calibration data set as part of a sensitivity study to evaluate uncertainties from the spectral sampling and processing methods that accompany the GLAMR calibration process. The spectral "supersets" include realistic instrumental features as well as effects from the GLAMR source. The methods needed to ensure that spurious sensor and GLAMR data are excluded are described. Results are given from the sensitivity study related to GLAMR spectral sampling and signal-to-noise ratio (SNR) effects, sensor integration time, and frame averaging of the imaging spectrometer data. The study shows that the 6 nm bandwidth sensor simulation requires a 1 nm spectral sampling of the GLAMR source with a radiance level that provides an in-band peak SNR > 200 to ensure that climate quality accuracies can be achieved. The results are also used to refine the test plan for the independent calibration for the CLARREO Pathfinder sensor calibration to optimize test time while meeting the required accuracy levels.

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.

The HyperSpectral Imager for Climate Science (HySICS) is the core instrument of the Climate Absolute Refractivity and Reflectance Observatory (CLARREO) Pathfinder (CPF) mission and is currently 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) over its entire spectral range of 350–2300 nm. The approach represents the need for significant improvement over the Radiometric Calibration (RadCal) of existing space-borne spectrometers. One strategy to demonstrate that HySICS achieves this level of accuracy is through an Independent Calibration (IndCal) effort that can provide an alternative referencing RadCal, which follows a traceability chain independent of the operational RadCal of ratioing approach. The IndCal relies on a pre-launch detector-based absolute RadCal of HySICS, using a tunable laser system as source, and the system planned for the HySICS absolute RadCal is the Goddard Laser for Absolute Measurement of Radiance (GLAMR). GLAMR was developed at NASA’s Goddard Space Flight Center and has been used to calibrate multiple operational remote sensing instruments, as well as the SOlar, Lunar Absolute Reflectance Imaging Spectroradiometer (SOLARIS), a calibration demonstration system developed for the CLARREO mission. In this work, the data of SOLARIS GLAMR RadCal conducted in 2019 are processed to derive the Absolute Spectral Response (ASR) functions and other key characterization parameters of SOLARIS detectors. The results are further analyzed with the goals to plan the HySICS GLAMR RadCal, in particular to optimize its configuration, to demonstrate the traceability route to the NIST standard, and to develop the error budget of the calibration approach. The SOLARIS calibration is also compared with other source- and detector-based calibrations to validate the absolute radiometric accuracy achieved.

Current imaging spectrometer forms for terrestrial remote sensing in the visible, near-, and shortwave infrared (VNR/SWIR) spectral range have been implemented in hardware and achieve a high level of performance in terms of both aberration control and signal-to-noise level. These forms are compact, relative to prior art, but more size, weight, and power optimization, while maintaining performance, is desirable for usage on small satellite platforms. Pursuant to that goal, we have developed a compact breadboard prototype VNIR/SWIR imaging spectrometer that maintains the current aberration control and has a large number of spatial samples. The new form utilizes a catadioptric lens and a flat dual-blaze immersion grating yielding a compact design that is relatively easy to manufacture.

Grayscale lithography is a widely known but underutilized microfabrication technique for creating three-dimensional (3-D) microstructures in photoresist. One of the hurdles for its widespread use is that developing the grayscale photolithography masks can be time-consuming and costly since it often requires an iterative process, especially for complex geometries. We discuss the use of PROLITH, a lithography simulation tool, to predict 3-D photoresist profiles from grayscale mask designs. Several examples of optical microsystems and microelectromechanical systems where PROLITH was used to validate the mask design prior to implementation in the microfabrication process are presented. In all examples, PROLITH was able to accurately and quantitatively predict resist profiles, which reduced both design time and the number of trial photomasks, effectively reducing the cost of component fabrication. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.

Longwave infrared (LWIR) hyperspectral imaging (HSI) sensors provide valuable information for numerous military, scientific, and commercial applications. The hyperspectral signal exploitation principles are the same in the reflective and emissive regions of the spectrum. However, the underlying phenomenology and interaction with the environment are different in the two regimes of the spectrum. These differences affect all aspects of thermal IR HSI, from sensor design to data exploitation. The main objective of this article is to explain the unique aspects of thermal IR HSI, review the progress that has been made, and highlight existing challenges and areas for future research.

The problem of spectral reflectance retrieval of surfaces via remote hyperspectral imaging is challenging even in benign scenarios, and becomes dramatically more difficult under complex illumination conditions. Shadows, reflections from nearby structures, and atmospheric scattering can all severely impact the observed radiance from ground-level surfaces. In order to study this problem, MIT Lincoln Laboratory recently conducted an airborne data collection experiment that included hyperspectral, laser radar, and pan-chromatic modalities. A comprehensive ground truth data set and extensive efforts directed at sensor characterization makes this data set ideal for the development of hyperspectral exploitation algorithms.

The intense development in imaging spectrometers and related technology has yielded systems that are highly performing. Current grating-based designs utilize focal plane arrays with aberrations controlled to a fraction of a detector element and low F-numbers for high étendue to maximize the signal to noise performance. Tailored grating facets using two or more blaze angles optimize the optical efficiency across the full 400-2500 nm solar reflective spectral range. Two commonly used forms, the Offner-Chrisp and Dyson designs, are adaptations of microlithographic projectors with a concave or convex mirror replaced by a shaped grating; maintain a high degree of spatial-spectral uniformity. These gratings are relatively difficult to manufacture using either e-beam lithography or diamond machining. The challenge for optical designers is to create optical forms with reduced size, weight, and power (SWaP) requirements while maintaining high performance. We have focused our work in this area and are developing a breadboard prototype imaging spectrometer that covers the full VNIR/SWIR spectral range at 10 nm spectral sampling, has a large swath of 1500 spatial samples, and is compact. The current prototype is for an F/3.3 system that is 7 cm long with an 8 cm diameter with aberration control better than 0.1 pixel assuming an 18 μm pixel pitch. The form utilizes a catadioptric lens and a flat dual-blaze immersion grating. The flat grating simplifies manufacturing and we are currently exploring the manufacture of the grating through grayscale optical lithography where the entire pattern can be exposed at once without stitching errors.

Hyperspectral image exploitation algorithms typically require inputs of reflectance spectra, which must be retrieved from the observed radiance spectra. This retrieval process is very challenging under the complex illumination conditions typical of urban settings due the influence of three-dimensional structure in the form of shadows and reflections, which must be taken into account by the algorithms. In order to advance the state of the art on this problem, MIT Lincoln Laboratory recently conducted an airborne data collection experiment in a light urban environment that included hyperspectral, laser radar, and pan-chromatic modalities. A comprehensive ground truth data set was collected and extensive efforts were directed at sensor characterization to enable the development of hyperspectral exploitation algorithms. Additionally, the laboratory is developing an extremely compact but high performance imaging spectrometer that will be ideal for the data collections required by this new image processing paradigm.

The development of remote sensing using an imaging spectrometer is traced from its origins to the current highly performing spectral sensors. The advancement of the technology has primarily been driven by novel optical designs and focal plane array development. Current state-of-the-art dispersive sensors, employing innovative grating or prism arrangements, operate at low F-numbers while maintaining a high degree of aberration control. These challenging designs have been implemented in hardware with alignment tolerances on the order of microns. The application of imaging spectrometers to science problems that require highly accurate radiometry necessitates new characterization approaches that combine state-of-the-art radiometric sources and detailed sensor models. Future challenges are to reduce the size, weight, and power requirements while maintaining the performance of current systems.

The next processing step for calibrated imaging spectrometer data is the conversion from the at-aperture radiance to a surface reflectance signature, for the VNIR/SWIR spectral range, or to a surface emissivity signature and temperature, for the LWIR spectral range. This requires that the transmission and emission of the atmosphere be quantified from the aggregated information that is present in the at-aperture radiance. In the solar reflective range this includes estimates of the amount of water in the scene, which is highly variable, and of the aerosol loading in order to calculate both the diffuse radiance and the contribution from light that is scattered and reflected from the directly viewed pixel and the surrounding area. Similarly, for a sensor operating in the emissive regime, the water and the atmospheric thermal emission is quantified in order to retrieve the ground-leaving radiance that is used to estimate the temperature and emissivity of the surface.