Limb Corrections and Channel Adjustments for Red-Green-Blue Composites from Geostationary Satellites
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geostationary, limb correction, intercalibration, ↗
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Structure of the Arabidopsis thaliana glutamate receptor-like channel GLR3.4
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Green, Marriah N.↗
Utilizing a Database of Simulated Geometric Albedo Spectra for Photometric Characterization of Rocky Exoplanet Atmospheres
In anticipation of future flagship missions focused on the goal of achieving direct imaging of rocky exoplanets, we have developed a database of models to help the community examine the potential spectral characteristics of a broad range of rocky planet atmospheres. Using the publicly available Planetary Spectrum Generator, we have computed a grid of 141,600 rocky exoplanet geometric albedo spectra across a seven-dimensional parameter space. Using this grid, we have performed a color–color analysis seeking to identify the most useful near-UV and red or near-infrared photometric follow-up channels to combine with a green-optical (discovery) spectral channel. We found that a combination of filters at 0.4, 0.58, and ∼0.8 μm were able to distinguish between atmospheres with moderate-to-high concentrations of four different dominant absorbing constituents, given at least 10 hr of observation on a star at 10 parsec with a 15 m class space telescope; however, more moderate abundances similar to those of solar system rocky bodies would be more challenging to detect. We recommend that future missions seeking to characterize directly imaged rocky exoplanets by colors alone further consider multiband photometry as a first discriminator for planetary characteristics.
79 ASTRONOMY AND ASTROPHYSICS↗
Utilizing a Database of Simulated Geometric Albedo Spectra for Photometric Characterization of Rocky Exoplanet Atmospheres
In anticipation of future flagship missions focused on the goal of achieving direct imaging of rocky exoplanets, we have developed a database of models to help the community examine the potential spectral characteristics of a broad range of rocky planet atmospheres. Using the publicly available Planetary Spectrum Generator, we have computed a grid of 141,600 rocky exoplanet geometric albedo spectra across a seven-dimensional parameter space. Using this grid, we have performed a color–color analysis seeking to identify the most useful near-UV and red or near-infrared photometric follow-up channels to combine with a green-optical(discovery)spectral channel. We found that a combination of filters at 0.4, 0.58, and∼0.8μm were able to distinguish between atmospheres with moderate-to-high concentrations of four different dominant absorbing constituents, given at least 10 hr of observation on a star at 10 parsec with a 15 m class space telescope; however, more moderate abundances similar to those of solar system rocky bodies would be more challenging to detect. We recommend that future missions seeking to characterize directly imaged rocky exoplanets by colors alone further consider multiband photometry as a first discriminator for planetary characteristics.
Adam J R W Smith↗
Color and Luminance Analysis of the Space Shuttle Multifunction Display Units(MDUs)
The purpose of this evaluation is to measure and analyze the colors that can be shown on the Multifunction Display Units (MDUs) of the Space Shuttle cockpit. The evaluation was conducted in the JSC Avionics Engineering Laboratory (JAEL) in building 16A at NASA Johnson Space Center. The JAEL contains a suite of 11 MDUs, each of which can be configured to show colors based on input values of the MDU red, green and blue (RGB) channels. Each of the channels has a range of 0 to 15. For example, bright green is produced by setting RGB to 0,15,0, and orange is produced by setting RGB to 15,4,0. The Cockpit Avionics Upgrade (CAU) program has specified the RGB settings for 14 different colors in the Display Design document (Rev A, 29 June 2001). The analysis in this report may help the CAU program determine better RGB settings for the colors.
McCandless, Jeffrey W.↗
Multi-channel Imager Algorithm (MIA): A novel cloud-top phase classification algorithm
The current Geostationary Operational Environmental Satellites (GOES-16 and 17) cloud-top phase classification algorithm is based primarily on empirical thresholds at multiple wavelengths that have varying absorption capabilities for water and ice. The performance of current GOES-16 cloud-top phase product largely depends on the accuracy of the selection of reflectance ratios. Here this study aims at presenting a novel cloud-top phase classification algorithm (the Multi-channel Imager Algorithm, MIA) that provides a more judicious selection of relationships between channels using a supervised K-mean clustering method on multi-channel Red-Green-Blue images. The K-mean clustering method works analogously to how human eyes separate different colors in a microphysical color rendering set of satellite images, which differentiates water, ice and unclassified thin clouds. For water phase, cloud-top temperature information is used to further distinguish supercooled water. To evaluate the performance of the MIA, an extensive comparison with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer, and current GOES-16 cloud-top phase products is conducted, using CALIOP as the benchmark. Compared to the current GOES-16 cloud-top phase product, MIA demonstrates a substantial improvement in phase classification, where hit rate increases from 69% to 76% over the Continental United States and 58% to 66% over the full disk domain.
54 ENVIRONMENTAL SCIENCES↗
Shape- and Orientation-Dependent Scattering of Isolated Gold Nanostructures Using Polarized Dark-Field Microscopy
In this work, we demonstrate a simple and robust method for measuring the shape- and orientation-dependent optical scattering of various plasmonic nanostructures adsorbed onto a solid surface using polarized dark-field microscopy. By analyzing the dark-field scattering images of gold nanostructures using grazing incidence polarized light with a bench-top microscope, we are able to correlate optical scattering from the individual nanostructures with their shape and orientation. Depending on the size, shape, and orientation of the plasmonic nanostructures, they exhibit characteristic angle- and polarization-dependent scattering signals. Extracting the red, green, and blue channels of the scattering signals from a color-imaging detector as a function of azimuthal angle provides a polar plot of color intensity values that is characteristic of the underlying nanostructure. Examples are presented for various nanostructures, including spherical nanoparticles, nanotriangles, and nanorods. Experimental results are complemented by numerical calculations of the scattering spectra of representative model nanostructures. We demonstrate that the polarization- and orientation-dependent scattering behavior is a consequence of various localized surface plasmon modes existing in the nanostructures and can be used to verify the shape of individual objects as well as quickly identify the orientation of numerous objects on a densely populated substrate. We anticipate that this method will provide a rapid and efficient complement to the typical structural analysis of nanoparticles that is achieved by electron microscopy as well as providing a simple method for generating detailed information of the optical scattering of various types of individual plasmonic nanostructures.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
On the spectral reflectance properties of materials exposed at the Viking landing sites
Reflectance data derived from Viking Lander multispectral data were used to characterize the types of soils and blocks exposed at the landing sites and to search for evidence of relatively unaltered igneous rocks. A comprehensive effort was mounted to examine multispectral data that combines testing of camera radiometric calibrations, explicitly removing the effects of atmospheric attenuation and skylight, and quantitatively comparing the corrected data to reflectance data from laboratory materials. Bi-directional reflectances for blue, green and red channels were determined for 31 block and soil exposures at Viking landing sites.
Guinness, E.↗
On the spectral reflectance properties of materials exposed at the Viking landing sites
Bidirectional reflectances for the blue, green, and red channels were determined for 31 block and soil exposures imaged by the two Viking Lander Cameras on Mars and were calibrated to within 10 percent uncertainties. The observed variations in bidirectional reflectance in the visible and relative brightness in the IR could be best explained by varying degrees of oxidation and ferric iron crystallinity, while most block surfaces had reflectances consistent with thin to optically thick covers of palagonitic material. These results are consistent with the conclusion that blocks seen at both sites are mafic rocks coated to varying thicknesses with amorphous oxidized material. The differences observed in reflectance properties for common block surfaces and common soils imply that local weathering of blocks has not contributed significantly to the soil exposed at the landing sites.
Guinness, Edward A.↗
Seeing the Soils of Meridiani Planum Through the Eyes of Pancam and Microscopic Imager
We are using data from the Pancam and Microscopic Imager (MI) on the Opportunity rover to characterize the soil grains at Meridiani Planum. We have traced individual grains in all MI images of the soils using the software application ImageJ distributed by NIH, and subsequently derived size and shape properties about the grains. The resolution of the MI is 31 microns per pixel [1] so we limit our measurements to those grains larger than about 0.3 mm in size. In cases where the grain is partially or substantially buried by other grains or finer soil particles, we do not make a measurement. False-color composites from Pancam images that cover the same location imaged by MI are made from the Left 2,5,6 (753, 535, 482 nm) filters or Right 2,7,1 (753, 1009, 430 nm) filters [2] in the Red, Green, and Blue channels, respectively. These color images are then merged with the MI images to illustrate color properties of particular grains. Pancam spectra are also extracted from grains when there is sufficient spatial coverage. in diameter. Figure 2 illustrates the dominance of these small grains at this particular location, which happens to be on the southern wall of Eagle crater. The Pancam color merge with this MI image suggests that the small spherules are more consistent with the basalt grains than the blueberries (spherulitic concretions derived from outcrop rocks [7]). The resolution of Pancam images of this location is on the order of 0.5 mm so the grains are only barely resolved. A Mossbauer measurement taken on an adjacent soil (Sol 53 Vanilla) that is composed solely of these smaller spherules (Fig 1) is consistent with a basaltic composition for the grains. Their concentration at this particular location in a brighter, elongate patch along the southeastern wall compared to elsewhere inside Eagle crater suggests wind activity favored their transport and subsequent deposition here. Their spherical shape is also possibly the result of wind action rounding them during transport, though water action cannot be ruled out.
Weitz, C. M.↗
Microfluidic Devices for Chemical and Biochemical Analysis in Microgravity
One often touted benefit of "Lab-on-a-Chip" devices is their potential for use in remote environments. The ultimate remote environment is outer space, and NASA has multiple needs in the area of analytical sensing capability in such an environment. In particular, we are interested in integrating microfluidic devices with NASA bioreactor systems. In such an integrated system, the microfluidic device will serve as a biosensor and be used for both feedback control and for detecting various bioproducts produced by cells cultured in the NASA bioreactors. As a first step in demonstrating the ability of microfluidic devices to operate under the extreme environmental conditions found in outer space, we constructed a portable, battery operated platform for testing under reduced gravity conditions on a NASA KC-135 reduced gravity research aircraft, (AKA "the vomit comet"). The test platform consisted of a microchip, two 0-8kV high voltage power supplies, a high voltage switch, a solid-state diode-pumped green laser, a channel photomultiplier, and an inertial mass measurement unit, all under the control of a laptop computer and powered by 10 D-cell alkaline batteries. Over the course of 4 KC-135 flights, 1817 fast electrophoretic separations of 4 amino acids and/or proteins were performed in a variety of gravitational environments including zero-G, Martian-G, lunar-G, and 2-G. Results from these experiments will be presented and discussed.
Roman, Gregory T.↗
Least squares restoration of multichannel images
Multichannel restoration using both within- and between-channel deterministic information is considered. A multichannel image is a set of image planes that exhibit cross-plane similarity. Existing optimal restoration filters for single-plane images yield suboptimal results when applied to multichannel images, since between-channel information is not utilized. Multichannel least squares restoration filters are developed using the set theoretic and the constrained optimization approaches. A geometric interpretation of the estimates of both filters is given. Color images (three-channel imagery with red, green, and blue components) are considered. Constraints that capture the within- and between-channel properties of color images are developed. Issues associated with the computation of the two estimates are addressed. A spatially adaptive, multichannel least squares filter that utilizes local within- and between-channel image properties is proposed. Experiments using color images are described.
Galatsanos, Nikolas P.↗
NASA/SPoRT's GOES-R Activities in Support of Product Development, Management, and Training
The NASA Short-term Prediction Research and Transition (SPoRT) Center supports many activities within the GOES-R Proving Grounds (PG). These include the development of imagery from existing instrumentation as a proxy to future Advanced Baseline Imager (ABI) capabilities on GOES-R. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible/Infrared Imager/Radiometer Suite (VIIRS) instruments are used to provide a glimpse of the multi-spectral capabilities that will become the norm as the number of channels and data rate dramatically increase with GOES-R. The NOAA/NWS has plans to provide operational users with all ABI channels at the highest resolution. Data fusion of individual channels into composite red, green, and blue imagery products will assist the end user with this future wave of information. While increasing the efficiency in the operational use of ABI channels, these composites provide only qualitative information. Within the GOES-R PG, SPoRT and other partners are exploring ways to include quantitative information as part of the composite imagery. However, limitations in local hardware processing and/or data bandwidth for users of the GOES-R data stream are challenges to overcome. This presentation will discuss the creation of these composite images as well as possible solutions to address these processing challenges. In a similar manner the Geostationary Lightning Mapper (GLM) to be launched on GOES-R presents several data management challenges. The GLM is a pioneering instrument to quantify total lightning from a geostationary platform. The expected data frequency from the GLM is to be at a sub-minute interval. Users of such a data set may have little experience in handling such a rapid update of information. To assist users, SPoRT is working with the NWS to develop tools within the user fs decision support system to allow tracking and analysis of total lightning from a storm-based perspective. This presentation will discuss the challenges and progress of this tool development work. With new data and products comes the need for user Training. Within the GOES-R PG SPoRT is supporting the demonstration of these future products by providing various training materials to end users. A summary of training provided to operational users will be discussed.
Fuell, Kevin K.↗
RadVolViz: An Information Display-Inspired Transfer Function Editor for Multivariate Volume Visualization
In volume visualization transfer functions are widely used for mapping voxel properties to color and opacity. Typically, volume density data are scalars which require simple 1D transfer functions to achieve this mapping. If the volume densities are vectors of three channels, one can straightforwardly map each channel to either red, green or blue, which requires a trivial extension of the 1D transfer function editor. Here, we devise a new method that applies to volume data with more than three channels. These types of data often arise in scientific scanning applications, where the data are separated into spectral bands or chemical elements. Our method expands on prior work in which a multivariate information display, RadViz, was fused with a radial color map, in order to visualize multi-band 2D images. In this work, we extend this joint interface to blended volume rendering. The information display allows users to recognize the presence and value distribution of the multivariate voxels and the joint volume rendering display visualizes their spatial distribution. We design a set of operators and lenses that allow users to interactively control the mapping of the multivariate voxels to opacity and color. This enables users to isolate or emphasize volumetric structures with desired multivariate properties. Furthermore, it turns out that our method also enables more insightful displays even for RGB data. We demonstrate our method with three datasets obtained from spectral electron microscopy, high energy X-ray scanning, and atmospheric science.
36 MATERIALS SCIENCE↗
Deep learning for in situ data compression of large turbulent flow simulations
As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.
97 MATHEMATICS AND COMPUTING↗
AEflow (Autoencoder fluid flow compression network) [SWR-22-29]
As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.
King, Ryan↗
Optimizing cloud motion estimation on the edge with phase correlation and optical flow
Abstract. Phase correlation (PC) is a well-known method for estimating cloud motion vectors (CMVs) from infrared and visible spectrum images. Commonly, phase shift is computed in the small blocks of the images using the fast Fourier transform. In this study, we investigate the performance and the stability of the blockwise PC method by changing the block size, the frame interval, and combinations of red, green, and blue (RGB) channels from the total sky imager (TSI) at the United States Atmospheric Radiation Measurement user facility's Southern Great Plains site. We find that shorter frame intervals, followed by larger block sizes, are responsible for stable estimates of the CMV, as suggested by the higher autocorrelations. The choice of RGB channels has a limited effect on the quality of CMVs, and the red and the grayscale images are marginally more reliable than the other combinations during rapidly evolving low-level clouds. The stability of CMVs was tested at different image resolutions with an implementation of the optimized algorithm on the Sage cyberinfrastructure test bed. We find that doubling the frame rate outperforms quadrupling the image resolution in achieving CMV stability. The correlations of CMVs with the wind data are significant in the range of 0.38–0.59 with a 95 % confidence interval, despite the uncertainties and limitations of both datasets. A comparison of the PC method with constructed data and the optical flow method suggests that the post-processing of the vector field has a significant effect on the quality of the CMV. The raindrop-contaminated images can be identified by the rotation of the TSI mirror in the motion field. The results of this study are critical to optimizing algorithms for edge-computing sensor systems.
54 ENVIRONMENTAL SCIENCES↗
Least squares restoration of multi-channel images
In this paper, a least squares filter for the restoration of multichannel imagery is presented. The restoration filter is based on a linear, space-invariant imaging model and makes use of an iterative matrix inversion algorithm. The restoration utilizes both within-channel (spatial) and cross-channel information as constraints. Experiments using color images (three-channel imagery with red, green, and blue components) were performed to evaluate the filter's performance and to compare it with other monochrome and multichannel filters.
Chin, Roland T.↗