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NASA NTRS2016

A New Operational Snow Retrieval Algorithm Applied to Historical AMSR-E Brightness Temperatures

Snow is a key element of the water and energy cycles and the knowledge of spatio-temporal distribution of snow depth and snow water equivalent (SWE) is fundamental for hydrological and climatological applications. SWE and snow depth estimates can be obtained from spaceborne microwave brightness temperatures at global scale and high temporal resolution (daily). In this regard, the data recorded by the Advanced Microwave Scanning Radiometer-Earth Orbiting System (EOS) (AMSR-E) onboard the National Aeronautics and Space Administration's (NASA) AQUA spacecraft have been used to generate operational estimates of SWE and snow depth, complementing estimates generated with other microwave sensors flying on other platforms. In this study, we report the results concerning the development and assessment of a new operational algorithm applied to historical AMSR-E data. The new algorithm here proposed makes use of climatological data, electromagnetic modeling and artificial neural networks for estimating snow depth as well as a spatio-temporal dynamic density scheme to convert snow depth to SWE. The outputs of the new algorithm are compared with those of the current AMSR-E operational algorithm as well as in-situ measurements and other operational snow products, specifically the Canadian Meteorological Center (CMC) and GlobSnow datasets. Our results show that the AMSR-E algorithm here proposed generally performs better than the operational one and addresses some major issues identified in the spatial distribution of snow depth fields associated with the evolution of effective grain size.

passive microwave↗

NASA NTRS2020

Nitric Oxide Laser-Induced Fluorescence Rotational Thermometry in a Hypersonic Non-Equilibrium Flow

Spatially-resolved nitric oxide (NO) planar laser-induced fluorescence (PLIF) rotational thermometry was performed on a Mach 5 non-equilibrium flow around a blunt-body specimen in the Hypersonic Materials Environmental Test System (HyMETS) arc-heat wind tunnel at the NASA Langley Research Center. Transitions within the (0,0) band in the A(exp⁡ 2)∑(sup⁡ +) - X(exp⁡ 2)Π system of NO were excited with a 10 Hz pulsed ultra-violet laser. A multi-line fitting algorithm was applied to the PLIF spectra and transitions were filtered based on an iterative method that maximizes thermometry accuracy. NO PLIF thermometry results are compared to non-equilibrium computational fluid dynamics (CFD) simulations reported in the literature. Differences between the experiment and CFD are quantified for the free-stream, post-shock, shear-layer, and expansion-fan regions of the flow. Potential sources of error, applicable to both the CFD and experiment, are discussed.

Connor C McDougall↗

NASA NTRS2020

Alaska Transportation & Infrastructure Identifying Permafrost Subsidence Using NASA Earth Observations to Pinpoint Road and Infrastructure Vulnerability in Fairbanks, Alaska

A rapidly warming Arctic has compromised the structural integrity of critical infrastructure through accelerated permafrost thaw and thermokarst development underlying these areas. Infrastructure, including roads, bridges, and airports across the state of Alaska are particularly at risk, as permafrost underlies ~85% of the state. However, monitoring the impacts of permafrost thaw on infrastructure is largely limited to in situ observations and frequently identified after the damage is evident. In order to assist transportation and infrastructure decision-makers in Alaska, this project identified and quantified areas of surface subsidence near critical infrastructure. Seasonal interferograms were created using Sentinel-1 C-band Synthetic Aperture Radar (SAR) and L-band Uninhabited Aerial Vehicle SAR (UAVSAR) data to identify areas experiencing surface deformation. Additionally, Light Detection and Ranging (LiDAR) datasets were used to validate select interferograms created between 2017 and 2019. Validation of subsidence detection across platforms was performed over a 7x8 sq. kilometer field site for 2017. The strongest relationship in spatial deformation is observed between Sentinel-1 and UAVSAR with a residual root mean square error of 20 mm. These results suggest that both UAVSAR and Sentinel-1 platforms are capable of detecting surface subsidence. The higher resolution of UAVSAR is better able to resolve localized subsidence features of less than 80 meters, but is limited by temporal resolution. In conjunction, UAVSAR and Sentinel-1 can provide complementary spatial and temporal resolutions for subsidence analysis in the absence of in situ data.

DEVELOP Tech Paper↗

DOE OSTI2019

The Velociprobe: An ultrafast hard X-ray nanoprobe for high-resolution ptychographic imaging

Motivated by the advanced photon source upgrade, a new hard X-ray microscope called "Velociprobe" has been recently designed and built for fast ptychographic imaging with high spatial resolution. We are addressing the challenges of high-resolution and fast scanning with novel hardware designs, advanced motion controls, and new data acquisition strategies, including the use of high-bandwidth interferometric measurements. The use of granite, air-bearing-supported stages provides the necessary long travel ranges for coarse motion to accommodate real samples and variable energy operation while remaining highly stable during fine scanning. Scanning the low-mass zone plate enables high-speed and high-precision motion of the probe over the sample. With an advanced control algorithm implemented in a closed-loop feedback system, the setup achieves a position resolution (3σ) of 2 nm. The instrument performance is evaluated by 2D fly-scan ptychography with our developed data acquisition strategies. A spatial resolution of 8.8 nm has been demonstrated on a Au test sample with a detector continuous frame rate of 200 Hz. Using a higher flux X-ray source provided by double-multilayer monochromator, we achieve 10 nm resolution for an integrated circuit sample in an ultrafast scan with a detector's full continuous frame rate of 3000 Hz (0.33 ms per exposure), resulting in an outstanding imaging rate of 9 x 10 4 resolution elements per second

36 MATERIALS SCIENCE↗

DOE OSTI2026

3D printed water-stable Cd-doped Cs 4 MnBi 2 Cl 12 /polylactic acid perovskite/polymer composites for high-flux X-ray scintillation

Stable and efficient X-ray scintillators are crucial for medical diagnostics, industrial, and defense applications. However, conventional scintillator technologies face a trade-off between stability, optimal performance, and sustainability. Herein, we introduce 3D-printed Cs 4 MnBi 2 Cl 12 (Pero1) and Cs 4 Cd 0.68 Mn 0.32 Bi 2 Cl 12 (Pero2) perovskite microcrystals embedded within a polylactic acid (PLA) polymer composite as X-ray scintillators, combining efficiency, stability, and sustainability. The orange luminescent perovskite powder phosphors exhibited poor water stability, which was successfully addressed through incorporation into PLA via filament extrusion and fused deposition modeling (FDM) 3D printing. The resulting composite films demonstrated remarkable water stability while maintaining uniform orange emission throughout the polymer matrix, as confirmed by 3D topography scanning and X-ray fluorescence mapping. Structural characterization revealed minimal chemical interaction between the perovskite and PLA matrix, with the composites retaining their crystalline properties. The PLA-Pero2 composite exhibited superior optical properties, with a photoluminescence quantum yield of 47%, nearly 17 times higher than that of PLA-Pero1 (2.8%), attributed to the effective suppression of non-radiative decay pathways through Cd 2+ doping. Under hard X-ray irradiation at synchrotron beamlines, both composites exhibited excellent radioluminescence, with emission peaks at 605 nm, a linear response across a wide X-ray flux range, and remarkable radiation stability, showing less than 3% intensity degradation after 600 seconds of continuous high-dose exposure. The PLA-Pero2 composite achieved a spatial resolution of 5 line pairs per millimeter and a contrast ratio of 0.255. These performance metrics, combined with the polymer's biodegradability and scalability through additive manufacturing, position PLA-based composites as a more sustainable alternative to conventional petroleum-based polymer scintillators for next-generation medical imaging, radiation monitoring, and industrial radiography applications.

3D Printing↗

DOE OSTI2024

A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps

Effective monitoring of global water resources is increasingly critical due to climate change and population growth. Advancements in remote sensing technology, specifically in spatial, spectral, and temporal resolutions, are revolutionizing water resource monitoring, leading to more frequent and high-quality surface water extent maps using various techniques such as traditional image processing and machine learning algorithms. However, satellite imagery datasets contain trade-offs that result in inconsistencies in performance, such as disparities in measurement principles between optical (e.g., Sentinel-2) and radar (e.g., Sentinel-1) sensors and differences in spatial and spectral resolutions among optical sensors. Therefore, developing accurate and robust surface water mapping solutions requires independent validations from multiple datasets to identify potential biases within the imagery and algorithms. However, high-quality validation datasets are expensive to build, and few contain information on water resources. For this purpose, we introduce a globally sampled, high-spatial-resolution dataset labeled using 3 m PlanetScope imagery. Our surface water extent dataset comprises 100 images, each with a size of 1024×1024 pixels, which were sampled using a stratified random sampling strategy covering all 14 biomes. We highlighted urban and rural regions, lakes, and rivers, including braided rivers and coastal regions. We evaluated two surface water extent mapping methods using our dataset – Dynamic World, based on Sentinel-2, and the NASA IMPACT model, based on Sentinel-1. Dynamic World achieved a mean intersection over union (IoU) of 72.16 % and F1 score of 79.70 %, while the NASA IMPACT model had a mean IoU of 57.61 % and F1 score of 65.79 %. Performance varied substantially across biomes, highlighting the importance of evaluating models on diverse landscapes to assess their generalizability and robustness. Our dataset can be used to analyze satellite products and methods, providing insights into their advantages and drawbacks. Our dataset offers a unique tool for analyzing satellite products, aiding the development of more accurate and robust surface water monitoring solutions. The dataset can be accessed via https://doi.org/10.25739/03nt-4f29.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction.

Our work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply Petrov-Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over all space and time in a weighted ℓ 2 -norm. This norm can be de ned to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time GNAT variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include: (1) a reduction of both the spatial and temporal dimensions of the dynamical system, (2) the removal of spurious temporal modes (e.g., unstable growth) from the state space, and (3) error bounds that exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRSDate not supplied

Measurement Techniques for the High-Contrast and in-Field Stray-Light Performance of OCI

Scheduled for launch in January 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records [1]. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. A critical requirement for OCI is the high-contrast or spatial cross-talk specification (also referred to as in-field stray-light response). The requirement states that for global top-of-atmosphere radiances based on measured MODIS radiances, the global average residual contamination shall be less than 0.15% for any multispectral band. Accurate resolution of high contrast in TOA radiance images is important to estimate stray light contamination due to clouds, for studying small scale features like ocean fronts and for working in coastal and estuarine areas where the scales are 1km. This occurs in all wavelengths in the spatial direction. Knowledge of high contrast resolution makes up part of the artifact budget. Accurate measurement of the high-contrast performance of OCI requires laboratory Ground Support Equipment (GSE) that projects a scene of sufficient quality that the unwanted stray light of the GSE itself is not confused with the stray light response of the telescope. This paper concerns the development, analyses and test of the GSE to ensure the quality of the projected image is sufficient to verify the OCI requirements. Optical models were developed for both the instrument as well as the GSE and laboratory environment. Simulation of various non-ideal parameters were critical to accurately predict performance. Measurements using COTS cameras and lenses were also made of the projected GSE image to reasonably verify the optical model predictions. Measured and modelled results from OCI are discussed.

OCI, PACE, LSF, PSF, Stray-light, Contrast, Cross-↗

NASA NTRSDate not supplied

Measurement Techniques for the High-Contrast and in-Field Stray-Light Performance of Oci

OCI↗

NASA NTRS1989

Improved reading performance using individualized compensation filters for observers with losses in central vision

A method to improve the reading performance of subjects with losses in central vision is proposed in which the amplitudes of the intermediate spatial frequencies are boosted relative to the lower spatial frequencies. In the method, words are filtered using an image enhancement function which is based on a subject's losses in visual function relative to a normal subject. It was found that 30-70 percent less magnification was necessary, and that reading rates were improved 2-3 times, using the method. The individualized compensation filters improved the clarity and visibility of words. The shape of the enhancement function was shown to be important in determining the optimum compensation filter for improving reading performance.

Lawton, Teri B.↗

NASA NTRS1998

Fractal Characterization of Multitemporal Scaled Remote Sensing Data

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISS. Scale is fundamental to the characterization of geo-spatial data as represented in GISS, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data, radiometric, configurations. This is particularly true in the emerging era of Integrated GISs (IGIS), wherein spatial data in a variety of formats (e.g., raster, vector) are combined with multiscaled remote sensing data, capable of performing highly sophisticated space-time data analyses and modeling. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective; i.e., "scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which can lead to substantive confusion in the input, manipulation, analyses, and output of IGISs (Quattrochi, 1993). Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale" across a wide number of spatial disciplines that use GISs.

Quattrochi, Dale A.↗

NASA NTRSDate not supplied

Behavioral consequences of low dose radiation and sex differences in MCAT mouse model

Our study used 1-year old C57BL/6NJ male and female mice (astronaut-relevant age) that underwent exposure to 0.5 gray of gamma radiation and were euthanized 12 weeks after. In this study, we used an MCAT mouse model for mitochondrial ROS quenching, which overexpress human catalase. MCAT mice were shown to live longer and age better. Hence, in this study we determined whether quenching ROS in the mitochondria will mitigate the adverse effects of ionizing radiation exposure on spaceflight-relevant tissues. As part of the analysis, we have completed 5 different behavioral tests which focus on memory, physical stance, stress, anxiety, and other mission relevant behaviors. In the Neuro-score battery, performed after both 1and 8 weeks post IR we saw that all female groups had significantly higher scores compared to males. When comparing the baseline vs 8 weeks of radiation, we saw that all the male groups (including the sham) had lower neuro-score, pointing out to aging effect in addition to IR. In the female groups only the female IR group had lower neuro-score and the MCAT group was protected from this effect. In the Nestlet building test we saw similarly that only females were affected by radiation, having lower scores and this effect was mitigated in the MCAT animals as well. In the Catwalk test we saw that females were faster, had higher swing speed and stride length in all four paws. Males had higher stand, step cycle and max contact area. Aging is associated with slowing of gait speed, swing speed and shortening of stride length which we see in males, this is consistent with physical appearance where males look markedly older. In the Light-Dark Box test we saw that females were more frequently present in the light side and altered zones more frequently, pointing out to a more exploratory and less anxious pattern of behavior. Similarly, to what was detected in the Nest building and Neuro-score test, in the Barnes maze test, during the acquisition phase (learning) we saw that IR affected more the females who did not do better in the maze after 4 days. On the other hand, during the probe phase of the test (spatial memory) the females visited the target hole and the box quadrant more often, but also had more errors vs males, which points out to possible serial escape vs spatial escape strategy. Overall, we see that older females look physically better are faster and perform better almost in all behavioral tests compared to their male counterparts. On the other hand, they are more sensitive to low dose radiation in many cases, in some cases this effect was mitigated in the MCAT model pointing out to the importance of ROS in these stressors. In the near future we will focus on corelating these behavioral tests with molecular findings such as for example brain IHC, plasma and hippocampal cytokines in order to find specific biomarkers for behavioral deficits.

radiation↗

DOE OSTI2024

Quantifying concentration distributions in redox flow batteries with neutron radiography

Abstract The continued advancement of electrochemical technologies requires an increasingly detailed understanding of the microscopic processes that control their performance, inspiring the development of new multi-modal diagnostic techniques. Here, we introduce a neutron imaging approach to enable the quantification of spatial and temporal variations in species concentrations within an operating redox flow cell. Specifically, we leverage the high attenuation of redox-active organic materials (high hydrogen content) and supporting electrolytes (boron-containing) in solution and perform subtractive neutron imaging of active species and supporting electrolyte. To resolve the concentration profiles across the electrodes, we employ an in-plane imaging configuration and correlate the concentration profiles to cell performance with polarization experiments under different operating conditions. Finally, we use time-of-flight neutron imaging to deconvolute concentrations of active species and supporting electrolyte during operation. Using this approach, we evaluate the influence of cell polarity, voltage bias and flow rate on the concentration distribution within the flow cell and correlate these with the macroscopic performance, thus obtaining an unprecedented level of insight into reactive mass transport. Ultimately, this diagnostic technique can be applied to a range of (electro)chemical technologies and may accelerate the development of new materials and reactor designs.

Science & Technology - Other Topics↗

NASA NTRS2010

Utilization of Hydrologic Remote Sensing Data in Land Surface Modeling and Data Assimilation: Current Status and Challenges

Recent advances in remote sensing technologies have enabled the monitoring and measurement of the Earth's land surface at an unprecedented scale and frequency. The myriad of these land surface observations must be integrated with the state-of-the-art land surface model forecasts using data assimilation to generate spatially and temporally coherent estimates of environmental conditions. These analyses are of critical importance to real-world applications such as agricultural production, water resources management and flood, drought, weather and climate prediction. This need motivated the development of NASA Land Information System (LIS), which is an expert system encapsulating a suite of modeling, computational and data assimilation tools required to address challenging hydrological problems. LIS integrates the use of several community land surface models, use of ground and satellite based observations, data assimilation and uncertainty estimation techniques and high performance computing and data management tools to enable the assessment and prediction of hydrologic conditions at various spatial and temporal scales of interest. This presentation will focus on describing the results, challenges and lessons learned from the use of remote sensing data for improving land surface modeling, within LIS. More specifically, studies related to the improved estimation of soil moisture, snow and land surface temperature conditions through data assimilation will be discussed. The presentation will also address the characterization of uncertainty in the modeling process through Bayesian remote sensing and computational methods.

Kumar, Sujay V.↗

NASA NTRS2017

Scale Dependence of Cirrus Horizontal Heterogeneity Effects on TOA Measurements: MODIS Brightness Temperatures in the Thermal Infrared - Part I

This paper presents a study on the impact of cirrus cloud heterogeneities on MODIS simulated thermal infrared (TIR) brightness temperatures (BTs) at the top of the atmosphere (TOA) as a function of spatial resolution from 50 meters to 10 kilometers. A realistic 3-D (three-dimensional) cirrus field is generated by the 3DCLOUD model (average optical thickness of 1.4, cloudtop and base altitudes at 10 and 12 kilometers, respectively, consisting of aggregate column crystals of D (sub eff) equals 20 microns), and 3-D thermal infrared radiative transfer (RT) is simulated with the 3DMCPOL (3-D Monte Carlo Polarized) code. According to previous studies, differences between 3-D BT computed from a heterogenous pixel and 1-D (one-dimensional) RT computed from a homogeneous pixel are considered dependent at nadir on two effects: (i) the optical thickness horizontal heterogeneity leading to the plane-parallel homogeneous bias (PPHB); and the (ii) horizontal radiative transport (HRT) leading to the independent pixel approximation error (IPAE). A single but realistic cirrus case is simulated and, as expected, the PPHB mainly impacts the low-spatial resolution results (above approximately 250 meters), with averaged values of up to 5-7 K (thousand), while the IPAE mainly impacts the high-spatial resolution results (below approximately 250 meters) with average values of up to 1-2 K (thousand). A sensitivity study has been performed in order to extend these results to various cirrus optical thicknesses and heterogeneities by sampling the cirrus in several ranges of parameters. For four optical thickness classes and four optical heterogeneity classes, we have found that, for nadir observations, the spatial resolution at which the combination of PPHB and HRT effects is the smallest, falls between 100 and 250 meters. These spatial resolutions thus appear to be the best choice to retrieve cirrus optical properties with the smallest cloud heterogeneity-related total bias in the thermal infrared. For off-nadir observations, the average total effect is increased and the minimum is shifted to coarser spatial resolutions.

TOA↗

DOE OSTI2025

A robust fourth-order finite-difference discretization for the strongly anisotropic transport equation in magnetized plasmas

We propose a second-order temporally implicit, fourth-order-accurate spatial discretization scheme for the strongly anisotropic heat transport equation characteristic of hot, fusion-grade plasmas. Following Du Toit et al. (2018), the scheme transforms mixed-derivative diffusion fluxes (which are responsible for the lack of a discrete maximum principle) into nonlinear advective fluxes, amenable to nonlinear-solver-friendly monotonicity-preserving limiters. The scheme enables accurate multi-dimensional heat transport simulations with up to seven orders of magnitude of heat-transport-coefficient anisotropies with low cross-field numerical error pollution and excellent algorithmic performance, with the number of linear iterations scaling very weakly with grid resolution and grid anisotropy, and scaling with the square-root of the implicit timestep. We propose a multigrid preconditioning strategy based on a lower-order approximation that renders the scheme efficient and scalable under grid refinement. Several numerical tests are presented that display the expected spatial convergence rates and strong algorithmic performance, including fully nonlinear magnetohydrodynamics simulations of kink instabilities in a Bennett pinch in 2D helical geometry and of ITER in 3D toroidal geometry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Space–Time Least-Squares Petrov–Galerkin Projection for Nonlinear Model Reduction

This work proposes a space--time least-squares Petrov--Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply (Petrov--)Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space--time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space--time trial subspace by minimizing the residual arising after time discretization over all space and time in a weighted $\ell^2$-norm. This norm can be defined to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space--time collocation and space--time Gauss--Newton with Approximated Tensors (GNAT) variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov--Galerkin projection include a reduction of both the spatial and temporal dimensions of the dynamical system, and a priori error bounds that bound the solution error by the best space--time approximation error and whose stability constants exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy for a fixed spatio-temporal discretization.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2007

Dual-Photoelastic-Modulator-Based Polarimetric Imaging Concept for Aerosol Remote Sensing

A dual-photoelastic-modulator- (PEM-) based spectropolarimetric camera concept is presented as an approach for global aerosol monitoring from space. The most challenging performance objective is to measure degree of linear polarization (DOLP) with an uncertainty of less than 0.5% in multiple spectral bands, at moderately high spatial resolution, over a wide field of view, and for the duration of a multiyear mission. To achieve this, the tandem PEMs are operated as an electro-optic circular retardance modulator within a high-performance reflective imaging system. Operating the PEMs at slightly different resonant frequencies generates a beat signal that modulates the polarized component of the incident light at a much lower heterodyne frequency. The Stokes parameter ratio q = Q/I is obtained from measurements acquired from each pixel during a single frame, providing insensitivity to pixel responsivity drift and minimizing polarization artifacts that conventionally arise when this quantity is derived from differences in the signals from separate detectors. Similarly, u = U/I is obtained from a different pixel; q and u are then combined to form the DOLP. A detailed accuracy and tolerance analysis for this polarimeter is presented.

spectropolarimetric imaging↗