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At least 1,567 records · Page 87

The Illumination of Thunderclouds by Lightning: 4. Volumetric Thunderstorm Imagery

Optical instruments such as the Geostationary Lightning Mapper (GLM) detect lightning based on transient changes in cloud illumination. The horizontal location of lightning is determined from the coordinates of the pixels on the imaging array illuminated during the flash. However, the vertical position of the lightning pulses (approximated by GLM “groups”) below the cloud top cannot be routinely measured from a single space-based instrument. In our prior work, we have developed a machine learning algorithm that can infer optical source altitude for a given pulse based on how the optical energy is distributed across the group footprint and the local Advanced Baseline Imager Cloud-Top Height (CTH). In this fourth part of our thundercloud illumination study, we leverage these source altitudes to generate volumetric GLM imagery of a Colombia thunderstorm. We find that 3D versions of the current GLM meteorological imagery products (that describe thunderstorm kinematics) and thundercloud imagery products (that depict how the flashes appear from space) provide additional insights into lightning activity in the thunderstorm that are lost in the vertical integration used to generate the current 2D GLM gridded products. This new volumetric imaging capability provides a more comprehensive picture of where lightning occurs in the storm, how its physical characteristics vary across three-dimensional space, and how its optical emissions interact with surrounding the cloud medium.

54 ENVIRONMENTAL SCIENCES↗

Exploring Gradient-Based Multi-directional Controls in GANs

Generative Adversarial Networks (GANs) have been widely applied in modeling diverse image distributions. However, despite its impressive applications, the structure of the latent space in GANs largely remains as a black-box, leaving its controllable generation an open problem, especially when spurious correlations between different semantic attributes exist in the image distributions. To address this problem, previous methods typically learn linear directions or individual channels that control semantic attributes in the image space. However, they often suffer from imperfect disentanglement, or are unable to obtain multi-directional controls. Furthermore, in this work, in light of the above challenges, we propose a novel approach that discovers nonlinear controls, which enables multi-directional manipulation as well as effective disentanglement, based on gradient information in the learned GAN latent space. More specifically, we first learn interpolation directions by following the gradients from classification networks trained separately on the attributes, and then navigate the latent space by exclusively controlling channels activated for the target attribute in the learned directions. Empirically, with small training data, our approach is able to gain fine-grained controls over a diverse set of bi-directional and multi-directional attributes, and we showcase its ability to achieve disentanglement significantly better than state-of-the-art methods both qualitatively and quantitatively.

97 MATHEMATICS AND COMPUTING↗

The Use of the Deep Convective Cloud Technique (DCCT) to Monitor On-Orbit Performance of the Geostationary Lightning Mapper (GLM): Use of Lightning Imaging Sensor (LIS) Data as Proxy

The Geostationary Lightning Mapper (GLM) on the next generation Geostationary Operational Environmental Satellite-R (GOES-R) will not have onboard calibration capability to monitor its performance. The Lightning Imaging Sensor (LIS) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite has been providing observations of total lightning over the Earth's Tropics since 1997. The GLM design is based on LIS heritage, making it a good proxy dataset. This study examines the performance of LIS throughout its time in orbit. This was accomplished through application of the Deep Convective Cloud Technique (DCCT) (Doelling et al., 2004) to LIS background pixel radiance data. The DCCT identifies deep convective clouds by their cold Infrared (IR) brightness temperatures and using them as invariant targets in the solar reflective portion of the solar spectrum. The GLM and LIS operate in the near-IR at a wavelength of 777.4 nm. In the present study the IR data is obtained from the Visible Infrared Sensor (VIRS) which is collocated with LIS onboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The DCCT is applied to LIS observations for July and August of each year from 1998-2010. The resulting distributions of LIS background DCC pixel radiance for each July August are very similar, indicating stable performance. The mean radiance of the DCCT analysis does not show a long term trend and the maximum deviation of the July August mean radiance for each year is within 0.7% of the overall mean. These results demonstrate that there has been no discernible change in LIS performance throughout its lifetime. A similar approach will used for monitoring the performance of GLM, with cold clouds identified using IR data from the Advanced Baseline Imager (ABI) which will also be located on GOES-R. Since GLM is based on LIS design heritage, the LIS results indicate that GLM should also experience stable performance over its lifetime.

Buechler, Dennis E.↗

Multispectral combination and display of ERTS-1 data

A significant problem in the use of ERTS-1 data is the extraction of information pertinent to each application and the presentation of that information in a form most suitable to users. When the information is to be displayed for visual study by an observer, the problem can be reduced to two steps: (1) Dimensionality reduction, an objective procedure which attempts to preserve most of the ERTS-1 information in a smaller number of components. (2) Display of the reduced number of components for optimum visibility by an observer. A specific dimensionality reduction technique has been applied to ERTS-1 data for several geographical areas in California and distinct types of earth resources. In the display of the reduced number of components, consideration has to be given to properties of the human visual system and the statistics of the data to be displayed. Previous work on digital image enhancement was applied to this problem to generate color composites which contain and display most of the information provided by the ERTS-1 sensors. Results of this approach were interesting, both in terms of the small mean-square caused by the dimensionality reduction, as well as for the examples of enhanced images that have been obtained.

Algazi, V. R.↗

Simulation studies of the GOES-I Image Navigation and Registration (INR) system

The GOES-I Image Navigation and Registration (INR) system will fly on the next generation of NOAA geostationary meteorological satellites. This system uses observations of stars and earth landmarks made by the Imager and Sounder Instruments themselves to determine the orbit, attitude, and misalignment state of the spacecraft and instruments. An extensive program of simulation and analysis has been conducted to assess the expected performance of the INR system. This paper discusses these activities and presents some computer simulation results showing expected system performance under a variety of conditions including station-keeping.

Carr, James L.↗

Magnetospheric Image Unfolding

The Grant was a three year grant funded under the Space Physics Supporting Research and Technology and Suborbital Program. Our objective was to develop automated techniques needed to unfold or "invert" global images of the magnetospheric ion populations obtained by the new magnetospheric imaging techniques (ENA, EUV) in anticipation of future missions such as the Magnetospheric Imager and, now, IMAGE. Our focus on the present three year grant is to determine the degree to which such images can quantitatively constrain the global electromagnetic properties of the magnetosphere. In a previous three year grant period we successfully automated a forward modeling inversion algorithm, demonstrated that these inversions are robust in the face of realistic instrumental considerations such as counting statistics and backgrounds, applied error analysis techniques to the extracted parameters using variational procedures, implemented very realistic magnetospheric test images to test the inversion algorithms using the Rice University Magnetospheric Specification Model, and began the process of generating parametric models with the flexibility to handle the realistic magnetospheric images (e.g. Roelof et al, 1992; 1993). Our plan for the present 3 year grant period was to complete the development of the inversion tools needed to handle realistic magnetospheric images, assess the degree to which global electrodynamics is quantitatively constrained by ENA images of the magnetosphere, and bring the inversion of EUV images up to the maturity that we will have achieved for the ENA imaging. Below the accomplishments of our three year effort are present followed by a list of our presentations and publications. The accomplishments of all three years are presented here, and thus some of these items appeared on interim progress reports.

Source record↗

Semi-Supervised Data Summarization: Using Spectral Libraries to Improve Hyperspectral Clustering

Hyperspectral imagers produce very large images, with each pixel recorded at hundreds or thousands of different wavelengths. The ability to automatically generate summaries of these data sets enables several important applications, such as quickly browsing through a large image repository or determining the best use of a limited bandwidth link (e.g., determining which images are most critical for full transmission). Clustering algorithms can be used to generate these summaries, but traditional clustering methods make decisions based only on the information contained in the data set. In contrast, we present a new method that additionally leverages existing spectral libraries to identify materials that are likely to be present in the image target area. We find that this approach simultaneously reduces runtime and produces summaries that are more relevant to science goals.

Wagstaff, K. L.↗

Making A Circular-Harmonic Filter

Optical image-correlating system made rotationally invariant. Experiment shows circular-harmonic filter generated optically. Hologram made by phase-shifted-double-exposure procedure. Filter used in optical image-recognition system based on correlation between target (image to be recognized) and matched spatial filter. In addition to usual invariance under translation of target, circular harmonic filter invariant under rotation of target; peak intensity of illumination at origin of correlation plane does not vary when target rotated about optical axis.

Cheng, Yeou Yen↗

Systems and methods for in situ assessment of mooring lines

A system can include at least one measuring device that captures and collects multiple two-dimensional images of a mooring line disposed in water. The system can also include a mooring line assessment system that includes a controller communicably coupled to the at least one measuring device. The controller can receive the two-dimensional images from the at least one measuring device. The controller can also generate a three-dimensional reconstruction of the mooring line based on the two-dimensional images. The controller can further present the three-dimensional reconstruction to a user. The two-dimensional images can be captured and the recommendation can be made while the mooring line is in situ.

47 OTHER INSTRUMENTATION↗

Analysis of coseismic surface displacement gradients using radar interferometry: New insights into the Landers earthquake

The map of the coseismic displacement field generated by interferometric processing of synthetic aperture radar (SAR) images taken before and after the June 28, 1992, Landers earthquake sequence brings new insights into the nature of deformation caused by these earthquakes. We use the interferometric map generated by Massonnet et al. (1993) to analyze the surface displacement field in the vicinity of the fault trace. Complexities in the fringe pattern near the fault reflect short-wavelength variations of the surface rupture and slip distribution, and attest to large displacement gradients. Along two sections of the fault, characteristic fringe patterns can be recognized, contrasting in density and direction with patterns observed away from the rupture. In order to understand the observed fringe patterns, we compute synthetic interferograms in three simple cases: (1) rigid-body rotations about a vertical axis, (2) about a horizontal axis (tilt), and (3) distributed, simple shear. The orientation and spatial separation of interferometric fringes predicted by these models help constrain near-field deformation and rupture parameters. Where the Kickapoo fault connects with the Homestead Valley fault, the interferogram shows a clear pattern of parallel N20 deg W fringes separated by about 160 m. This pattern and vertical offsets measured along the Kickapoo fault suggest that the block between this fault and the Johnson Valley fault may have been tilted, down to the west. A 5-km block lifted by 1 m on one side would be tilted by an angle of 0.01 deg (190 microrad), producing fringes separated by about 160 m, parallel to the tilt axis. Such a tilt, parallel to a N20 deg W direction, would account for the gradual, northward increase of the vertical slip component observed along the Kickapoo fault. This tilt may also explain the 1 m of reverse slip observed along the 'slip gap' section of the Homestead Valley break. Between the southern end of the Johnson Valley fault and the Eureka Peak fault, where no surface rupture has been mapped, the dense pattern of fringes implies distributed shear, probably resulting from fault slip at depth. The density and direction of the fringes in the gap are consistent with a right-lateral slip of 1.2-3.8 m on a blind fault locked above the depth of 1.5-2 km. Such observations of small wavelength features in the SAR interferogram bring new insights into the near-field displacement gradient and thus on response of the uppermost crust to seismic rupture.

Peltzer, Gilles↗

2024 roadmap on magnetic microscopy techniques and their applications in materials science

Considering the growing interest in magnetic materials for unconventional computing, data storage, and sensor applications, there is active research not only on material synthesis but also characterisation of their properties. In addition to structural and integral magnetic characterisations, imaging of magnetisation patterns, current distributions and magnetic fields at nano- and microscale is of major importance to understand the material responses and qualify them for specific applications. In this roadmap, we aim to cover a broad portfolio of techniques to perform nano- and microscale magnetic imaging using superconducting quantum interference devices, spin centre and Hall effect magnetometries, scanning probe microscopies, x-ray- and electron-based methods as well as magnetooptics and nanoscale magnetic resonance imaging. The roadmap is aimed as a single access point of information for experts in the field as well as the young generation of students outlining prospects of the development of magnetic imaging technologies for the upcoming decade with a focus on physics, materials science, and chemistry of planar, three-dimensional and geometrically curved objects of different material classes including two-dimensional materials, complex oxides, semi-metals, multiferroics, skyrmions, antiferromagnets, frustrated magnets, magnetic molecules/nanoparticles, ionic conductors, superconductors, spintronic and spinorbitronic materials.

2D materials↗

Experimental image alignment system

A microcomputer-based instrument for image alignment with respect to a reference image is described which uses the DEFT sensor (Direct Electronic Fourier Transform) for image sensing and preprocessing. The instrument alignment algorithm which uses the two-dimensional Fourier transform as input is also described. It generates signals used to steer the stage carrying the test image into the correct orientation. This algorithm has computational advantages over algorithms which use image intensity data as input and is suitable for a microcomputer-based instrument since the two-dimensional Fourier transform is provided by the DEFT sensor.

Moyer, A. L.↗

Directivity of a Sparse Array in the Presence of Atmospheric-Induced Phase Fluctuations for Deep Space Communications

Widely distributed (sparse) ground-based arrays have been utilized for decades in the radio science community for imaging celestial objects, but have only recently become an option for deep space communications applications with the advent of the proposed Next Generation Deep Space Network (DSN) array. But whereas in astronomical imaging, observations (receive-mode only) are made on the order of minutes to hours and atmospheric-induced aberrations can be mostly corrected for in post-processing, communications applications require transmit capabilities and real-time corrections over time scales as short as fractions of a second. This presents an unavoidable problem with the use of sparse arrays for deep space communications at Ka-band which has yet to be successfully resolved, particularly for uplink arraying. In this paper, an analysis of the performance of a sparse antenna array, in terms of its directivity, is performed to derive a closed form solution to the expected array loss in the presence of atmospheric-induced phase fluctuations. The theoretical derivation for array directivity degradation is validated with interferometric measurements for a two-element array taken at Goldstone, California. With the validity of the model established, an arbitrary 27-element array geometry is defined at Goldstone, California, to ascertain its performance in the presence of phase fluctuations. It is concluded that a combination of compact array geometry and atmospheric compensation is necessary to ensure high levels of availability.

Nessel, James A.↗

Referenceless, grating-based, single shot X-ray phase contrast imaging with optimized laser-driven K-α sources

With its ability to efficiently probe low-Z materials, X-ray phase imaging methods have recently raised high interest in multiple fields from biology and medical applications to high energy density (HED) physics. Initially developed with synchrotron light and X-ray tubes, we present a novel grating based Talbot X-ray deflectometer (TXD) diagnostic that was coupled with laser-generated K-α X-ray sources. The multi-terawatt laser (I > 1 × 10 14 W cm -2 ) was used as a testbed for diagnostic development. It was found that X-ray source chromaticity plays an important role in TXD. Indeed, the broadband spectrum of laser-generated X-ray sources may strongly impact image quality and thus diagnostic performance. We qualified X-ray emission from different laser-produced sources and determined laser, target, and deflectometer parameters that optimize TXD performance. We present the first results of referenceless grating-based X-ray imaging at high-power laser facilities and discuss the implications of this new development in HED research.

47 OTHER INSTRUMENTATION↗

Virtual Sensing with Unsupervised Image-to-Image Translation

Earth observing satellites carrying multi-spectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have different vantage points above the earth and different spectral imaging bands resulting in inconsistent imagery from one to another. This presents challenges in building downstream applications. What if we could generate synthetic bands for existing satellites from the union of all domains? We tackle the problem of generating synthetic spectral imagery for multispectral sensors as an unsupervised image-to-image translation problem with partial labels and introduce a novel shared spectral reconstruction loss. Simulated experiments performed by dropping one or more spectral bands show that cross-domain reconstruction outperforms measurements obtained from a second vantage point. On a downstream cloud detection task, we show that generating synthetic bands with our model improves segmentation performance beyond our baseline. Our proposed approach enables synchronization of multispectral data and provides a basis for more homogeneous remote sensing datasets.

Geostationary satellites↗

On Advanced Estimation Techniques for Exoplanet Detection and Characterization using Ground-based Coronagraphs

The direct imaging of planets around nearby stars is exceedingly difficult. Only about 14 exoplanets have been imaged to date that have masses less than 13 times that of Jupiter. The next generation of planet-finding coronagraphs, including VLT-SPHERE, the Gemini Planet Imager, Palomar P1640, and Subaru HiCIAO have predicted contrast performance of roughly a thousand times less than would be needed to detect Earth-like planets. In this paper we review the state of the art in exoplanet imaging, most notably the method of Locally Optimized Combination of Images (LOCI), and we investigate the potential of improving the detectability of faint exoplanets through the use of advanced statistical methods based on the concepts of the ideal observer and the Hotelling observer. We propose a formal comparison of techniques using a blind data challenge with an evaluation of performance using the Receiver Operating Characteristic (ROC) and Localization ROC (LROC) curves. We place particular emphasis on the understanding and modeling of realistic sources of measurement noise in ground-based AO-corrected coronagraphs. The work reported in this paper is the result of interactions between the co-authors during a week-long workshop on exoplanet imaging that was held in Squaw Valley, California, in March of 2012

coronagraphs↗

On Advanced Estimation Techniques for Exoplanet Detection and Characterization using Ground-Based Coronagraphs

The direct imaging of planets around nearby stars is exceedingly difficult. Only about 14 exoplanets have been imaged to date that have masses less than 13 times that of Jupiter. The next generation of planet-finding coronagraphs, including VLT-SPHERE, the Gemini Planet Imager, Palomar P1640, and Subaru HiCIAO have predicted contrast performance of roughly a thousand times less than would be needed to detect Earth-like planets. In this paper we review the state of the art in exoplanet imaging, most notably the method of Locally Optimized Combination of Images (LOCI), and we investigate the potential of improving the detectability of faint exoplanets through the use of advanced statistical methods based on the concepts of the ideal observer and the Hotelling observer. We provide a formal comparison of techniques through a blind data challenge and evaluate performance using the Receiver Operating Characteristic (ROC) and Localization ROC (LROC) curves. We place particular emphasis on the understanding and modeling of realistic sources of measurement noise in ground-based AO-corrected coronagraphs. The work reported in this paper is the result of interactions between the co-authors during a week-long workshop on exoplanet imaging that was held in Squaw Valley, California, in March of 2012.

instrumentation↗

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗