Prospects for High Angular Resolution at Low Frequencies
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Interferometry Low Frequency↗
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Deciphering the 3D Orion Nebula. II. A Low Ionization Region of Multiple Velocity Components Southwest of θ 1 Ori C Confounds Interpretation of Low Velocity Resolution Studies of Temperature, Density, and Abundance
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C. R. O’Dell↗
Super-resolution and segmentation deep learning for breast cancer histopathology image analysis
Traditionally, a high-performance microscope with a large numerical aperture is required to acquire high-resolution images. However, the images’ size is typically tremendous. Therefore, they are not conveniently managed and transferred across a computer network or stored in a limited computer storage system. As a result, image compression is commonly used to reduce image size resulting in poor image resolution. Here, we demonstrate custom convolution neural networks (CNNs) for both super-resolution image enhancement from low-resolution images and characterization of both cells and nuclei from hematoxylin and eosin (H&E) stained breast cancer histopathological images by using a combination of generator and discriminator networks so-called super-resolution generative adversarial network-based on aggregated residual transformation (SRGAN-ResNeXt) to facilitate cancer diagnosis in low resource settings. The results provide high enhancement in image quality where the peak signal-to-noise ratio and structural similarity of our network results are over 30 dB and 0.93, respectively. The derived performance is superior to the results obtained from both the bicubic interpolation and the well-known SRGAN deep-learning methods. In addition, another custom CNN is used to perform image segmentation from the generated high-resolution breast cancer images derived with our model with an average Intersection over Union of 0.869 and an average dice similarity coefficient of 0.893 for the H&E image segmentation results. Finally, we propose the jointly trained SRGAN-ResNeXt and Inception U-net Models, which applied the weights from the individually trained SRGAN-ResNeXt and inception U-net models as the pre-trained weights for transfer learning. The jointly trained model’s results are progressively improved and promising. We anticipate these custom CNNs can help resolve the inaccessibility of advanced microscopes or whole slide imaging (WSI) systems to acquire high-resolution images from low-performance microscopes located in remote-constraint settings.
60 APPLIED LIFE SCIENCES↗
Comparison of Observations and Predictions of Daytime Planetary-Boundary-Layer Heights and Surface Meteorological Variables in the Columbia River Gorge and Basin During the Second Wind Forecast Improvement Project
The second Wind Forecast Improvement Project (WFIP2) is an 18-month field campaign in the Pacific Northwest U.S.A., whose goal is to improve the accuracy of numerical-weather-prediction forecasts in complex terrain. The WFIP2 campaign involved the deployment of a large suite of in situ and remote sensing instrumentation, including eight 915-MHz wind-profiling radars, and surface meteorological stations. The evolution and annual variability of the daytime convective planetary-boundary-layer (PBL) height is investigated using the wind-profiling radars. Three models with different horizontal grid spacing are evaluated: the Rapid Refresh, the High-Resolution Rapid Refresh, and its nested version. The results are used to assess errors in the prediction of PBL height within the experimental and control versions of the models, with the experimental versions including changes and additions to the model parametrizations developed during the field campaign, and the control version using the parametrizations present in the National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction operational version of the models at the start of the project. Results show that the high-resolution models outperform the low-resolution versions, the experimental versions perform better compared with the control versions, model PBL height estimations are more accurate on cloud-free days, and model estimates of the PBL height growth rate are more accurate than model estimates of the rate of decay. Finally, using surface sensors, we assess surface meteorological variables, finding improved surface irradiance and, to a lesser extent, improved 2-m temperature in the experimental version of the model.
54 ENVIRONMENTAL SCIENCES↗
Advanced marine information delivery
The paper examines the information delivery challenges of the follow-on programs to Seasat-1 as they may progress through the next decade. These challenges include coping with the vast amounts of data to be transferred, fulfilling the temporal requirements on data delivery, and the tradeoffs and developments needed to accomplish the various levels of processing required to convert sensor output into useful information. A need for critical development is clearly identifiable in the areas of (1) low cost ground terminals capable of image extraction and image correlation; (2) dynamic data assimilation to accommodate forecasters; (3) low resolution onboard correlators; and (4) low cost user advisory (display) terminals. The system planners for the Ocean Satellite advanced programs are using an end-to-end data systems approach in meeting these challenges.
Durstenfeld, R.↗
Shuttle imaging radar - Research sensor for earth resources observation
The operating characteristics of the Shuttle Imaging Radar (SIR) and intended experimentation to study the effects of the incidence angle, look direction, frequency, and polarization are described. SIR will be flown in 1984-1986, operate in the L- and C-bands, and have a look angle which can be varied through 15-75 deg. Polarizations of HH on the L-band and HH, VV, HV, and VH on the C-band are possible. The SIR will provide 10 and 30 m resolutions in the high and low resolution modes, respectively, with a swatch width between 35-125 km. Real-time to ground and on-board optical recording will be available, together with digital and optical processing. The antennas will be rotated in the Shuttle bay in 5 deg increments, permitting the formation of stereo pictures during several overpasses. Viewing at 1275 MHz is intended for imaging, while the 5300 MHz band can sense soil moisture
Elachi, C.↗
Geologic Interpretation of Remote Sensing Data for the Martian Volcano, Ascraeus Mons
Results of an investigation to relate remotely determined physical properties on Ascraeus Mons to the geologic history of the volcano are summarized. Products include a 1:2,000,000-scale photogeologic map of Ascraeus Mons and its environs; a 1:250,000-scale corrected thermal-inertia map of the summit caldera complex; four corrected thermal-inertia profiles across the volcano from high-resolution thermal data; fourteen low-resolution thermal sequences providing corrected thermal inertias for the volcano throughout half a Martian year; and a calibrated three-color photograph of the volcano. These data were combined with published spectral-reflectance, radar, and atmospheric water-vapor data relating to Acraeus Mons. Photogeologic mapping indicates that the sequence of events at Acraeus Mons is more complex than previously described. The plains surrounding the volcano include numerous flows, some of which can be traced to the flank of the volcano and some to different locations along the Tharsis Ridge. Surface morphology in the summit area is very distinct for features 100 m in scale, but the surface relief and tonal contrast steadily decrease toward the base of the shield, indicating modification by deposition or erosion.
Zimbelman, J.↗
Infrared spectroscopy of Seyfert 2 galaxies: A look through the obscuring Torus?
We present both high-resolution (R = 1260) and low-resolution (R = 345 and 425) J-band spectra of a sample of 15 Seyfert 2 galaxies. Our goal is to look for broad Pa beta lines, indicating broad-line regions which are hidden by dust from our view at optical wavelengths. Of the 15 objects studied here, three have broad Pa beta lines: MCG-05.23.16, Mrk 463E, and NGC 2992. Mrk 176 and NGC 5728 may also have weak broad lines. In NGC 5506, previously reported to have broad Pa beta and hydrogen alpha lines, we find that the Pa beta line profile is continuous and has the same shape as the nearby line (Fe II) lambda 1.2567, which should not have a broad component. We interpret these observations as gas from the narrow-line region (NLR) with no broad component. In NGC 5506, however, the NLR profiles become broader with increasing wavelength, indicating that highly reddened wings are becoming more readily visible at the longer wavelengths. We confirm the correlation of (O I) lambda 6300/hydrogen alpha and (Fe II) lambda 1.644/Br gamma (the latter transformed to (Fe II) lambda 1.2567/Pa beta to compare with our data) found by previous authors when comparing active galactic nuclei (AGNs), supernova remnants, starbursts, and H II regions. The correlation confirms that in all of these objects both (O I) lambda 6300 and the (Fe II) lines come from partially ionized regions in which hydrogen is mostly neutral. Comparison of the infrared optical depths with column depths determined from X-ray data show a general tendency for the objects with detected broad Pa beta to have lower X-ray columns.
Goodrich, Robert W.↗
Estimation of Sea Ice Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data
Combinations of sea ice freeboard and snow depth measurements from satellite data have the potential to provide a means to derive global sea ice thickness values. However, large differences in spatial coverage and resolution between the measurements lead to uncertainties when combining the data. High resolution airborne laser altimeter retrievals of snow-ice freeboard and passive microwave retrievals of snow depth taken in March 2006 provide insight into the spatial variability of these quantities as well as optimal methods for combining high resolution satellite altimeter measurements with low resolution snow depth data. The aircraft measurements show a relationship between freeboard and snow depth for thin ice allowing the development of a method for estimating sea ice thickness from satellite laser altimetry data at their full spatial resolution. This method is used to estimate snow and ice thicknesses for the Arctic basin through the combination of freeboard data from ICESat, snow depth data over first-year ice from AMSR-E, and snow depth over multiyear ice from climatological data. Due to the non-linear dependence of heat flux on ice thickness, the impact on heat flux calculations when maintaining the full resolution of the ICESat data for ice thickness estimates is explored for typical winter conditions. Calculations of the basin-wide mean heat flux and ice growth rate using snow and ice thickness values at the 70 m spatial resolution of ICESat are found to be approximately one-third higher than those calculated from 25 km mean ice thickness values.
Kurtz, Nathan T.↗
Towards Construction of a Novel Nanometer-Resolution MeV-STEM for Imaging Thick Frozen Biological Samples
Driven by life-science applications, a mega-electron-volt Scanning Transmission Electron Microscope (MeV-STEM) has been proposed here to image thick frozen biological samples as a conventional Transmission Electron Microscope (TEM) may not be suitable to image samples thicker than 300–500 nm and various volume electron microscopy (EM) techniques either suffering from low resolution, or low speed. The high penetration of inelastic scattering signals of MeV electrons could make the MeV-STEM an appropriate microscope for biological samples as thick as 10 μm or more with a nanoscale resolution, considering the effect of electron energy, beam broadening, and low-dose limit on resolution. The best resolution is inversely related to the sample thickness and changes from 6 nm to 24 nm when the sample thickness increases from 1 μm to 10 μm. To achieve such a resolution in STEM, the imaging electrons must be focused on the specimen with a nm size and an mrad semi-convergence angle. This requires an electron beam emittance of a few picometers, which is ~1000 times smaller than the presently achieved nm emittance, in conjunction with less than 10 -4 energy spread and 1 nA current. We numerically simulated two different approaches that are potentially applicable to build a compact MeV-STEM instrument: (1) DC (Direct Current) gun, aperture, superconducting radio-frequency (SRF) cavities, and STEM column; (2) SRF gun, aperture, SRF cavities, and STEM column. Beam dynamic simulations show promising results, which meet the needs of an MeV-STEM, a few-picometer emittance, less than 10 -4 energy spread, and 0.1–1 nA current from both options. Also, we designed a compact STEM column based on permanent quadrupole quintuplet, not only to demagnify the beam size from 1 μm at the source point to 2 nm at the specimen but also to provide the freedom of changing the magnifications at the specimen and a scanning system to raster the electron beam across the sample with a step size of 2 nm and the repetition rate of 1 MHz. This makes it possible to build a compact MeV-STEM and use it to study thick, large-volume samples in cell biology.
36 MATERIALS SCIENCE↗
Deep-learning-guided high-resolution subsurface reflectivity imaging with application to ground-penetrating radar data
Subsurface reflectivity imaging is one of the most important geophysical characterization methods for revealing subsurface structures. In many cases, accurate subsurface reflectivity imaging is challenging because of, for example, random or coherent noise in the data and sparse source-receiver observation geometry. Here, we develop a deep-learning-guided iterative imaging method to improve subsurface structure imaging. Specifically, we train a supervised neural network to infer a noise-free, high-resolution image from a noisy, low-resolution image and use this estimated image as guidance to regularize least-squares imaging. We develop a systematic method to generate high-quality synthetic training data (data-label pairs) to train the guidance neural network. The trained neural network can provide high-fidelity predictions even for field-data images that are not in the training data. We validate our new imaging method using one synthetic and two field ground-penetrating radar data examples, and find that our method can produce clean, high-resolution subsurface reflectivity images where existing single-pass and least-squares imaging methods fail due to noise and insufficient data coverage.
58 GEOSCIENCES↗
Diverse Super-Resolution (diversity_SR) [SWR-21-60]
Deep learning tools for enhancing the spatial resolution of wind data. The software is developed in Python using the TensorFlow deep learning package. Models for diversity super-resolution is provided. Included in the package are pretrained models with example code/data to perform the super-resolution as well as tools of training models for different enhancement- or data-types. The super-resolution is an inherently ill-conditioned problem, with multiple high-resolution fields plausibly mapping to the same coarse field. Considitional GANs provide a framework for generating a distribution of high-resolution realizations from a given low-resolution input. Stochastic estimation is used to inform the network of the expected degree and location of sub-grid diversity. The package includes a pretrained network to generate distributions of 10x-enhanced fields of wind data.
Glaws, Andrew↗
3D Multiresolution Velocity Model Fusion with Probability Graphical Models
ABSTRACT The variability in spatial resolution of seismic velocity models obtained via tomographic methodologies is attributed to many factors, including inversion strategies, ray-path coverage, and data integrity. Integration of such models, with distinct resolutions, is crucial during the refinement of community models, thereby enhancing the precision of ground-motion simulations. Toward this goal, we introduce the probability graphical model (PGM), combining velocity models with heterogeneous resolutions and nonuniform data point distributions. The PGM integrates data relations across varying resolution subdomains, enhancing detail within low-resolution (LR) domains by utilizing information and prior knowledge from high-resolution (HR) subdomains through a maximum posterior problem. Assessment of efficacy, utilizing both 2D and 3D velocity models—consisting of synthetic checkerboard models and a fault-zone model from Ridgecrest, California—demonstrates noteworthy improvements in accuracy, compared to state-of-the-art fusion techniques. Specifically, we find reductions of 30% and 44% in computed travel-time residuals for 2D and 3D models, respectively, as compared to conventional smoothing techniques. Unlike conventional methods, the PGM’s adaptive weight selection facilitates preserving and learning details from complex, nonuniform HR models and applies the enhancements to the LR background domain.
Geochemistry & Geophysics↗
A seamless approach for evaluating climate models across spatial scales
In regions of the world where topography varies significantly with distance, most global climate models (GCMs) have spatial resolutions that are too coarse to accurately simulate key meteorological variables that are influenced by topography, such as clouds, precipitation, and surface temperatures. One approach to tackle this challenge is to run climate models of sufficiently high resolution in those topographically complex regions such as the North American Regionally Refined Model (NARRM) subset of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 (E3SM v2). Although high-resolution simulations are expected to provide unprecedented details of atmospheric processes, running models at such high resolutions remains computationally expensive compared to lower-resolution models such as the E3SM Low Resolution (LR). Moreover, because regionally refined and high-resolution GCMs are relatively new, there are a limited number of observational datasets and frameworks available for evaluating climate models with regionally varying spatial resolutions. As such, we developed a new framework to quantify the added value of high spatial resolution in simulating precipitation over the contiguous United States (CONUS). To determine its viability, we applied the framework to two model simulations and an observational dataset. We first remapped all the data into Hierarchical Equal-Area Iso-Latitude Pixelization (HEALPix) pixels. HEALPix offers several mathematical properties that enable seamless evaluation of climate models across different spatial resolutions including its equal-area and partitioning properties. The remapped HEALPix-based data are used to show how the spatial variability of both observed and simulated precipitation changes with resolution increases. This study provides valuable insights into the requirements for achieving accurate simulations of precipitation patterns over the CONUS. It highlights the importance of allocating sufficient computational resources to run climate models at higher temporal and spatial resolutions to capture spatial patterns effectively. Furthermore, the study demonstrates the effectiveness of the HEALPix framework in evaluating precipitation simulations across different spatial resolutions. This framework offers a viable approach for comparing observed and simulated data when dealing with datasets of varying spatial resolutions. By employing this framework, researchers can extend its usage to other climate variables, datasets, and disciplines that require comparing datasets with different spatial resolutions.
54 ENVIRONMENTAL SCIENCES↗
Variable features on Mars V - Evidence for crater streaks produced by wind erosion
High-resolution television pictures obtained by Mariner 9 are presented as evidence to show that the ragged dark streaks which appeared behind many dark craters several months after the end of the 1971 global dust storm resulted from wind erosion of a thin surface veneer consisting of dust-storm fallout. The pictures were taken over an area near the border between Mare Serpentis and Pandorae Fretum (approximately 30 deg S, 335 deg W). The high-resolution pictures are compared with low-resolution views of the same area, and it is shown that one very long dark streak is interrupted by a rille. It is concluded that this interruption proves that the dark streaks were produced by the present erosional mechanism.
Veverka, J.↗
Estimating Elevation Angles From SAR Crosstalk
Scheme for processing polarimetric synthetic-aperture-radar (SAR) image data yields estimates of elevation angles along radar beam to target resolution cells. By use of estimated elevation angles, measured distances along radar beam to targets (slant ranges), and measured altitude of aircraft carrying SAR equipment, one can estimate height of target terrain in each resolution cell. Monopulselike scheme yields low-resolution topographical data.
Freeman, Anthony↗
Calibration of the SHERLOC Deep Ultraviolet Fluorescence–Raman Spectrometer on the Perseverance Rover
We describe the wavelength calibration of the spectrometer for the scanning of habitable environments with Raman and luminescence for organics and chemicals (SHERLOC) instrument onboard NASA’s Perseverance Rover. SHERLOC utilizes deep ultraviolet Raman and fluorescence (DUV R/F) spectroscopy to enable analysis of samples from the Martian surface. SHERLOC employs a 248.6 nm deep ultraviolet laser to generate Raman-scattered photons and native fluorescence emission photons from near-surface material to detect and classify chemical and mineralogical compositions. The collected photons are focused on a charge-coupled device and the data are returned to Earth for analysis. The compact DUV R/F spectrometer has a spectral range from 249.9 nm to 353.6 nm (200 cm1 to 12, 000 cm1) (with a spectral resolution of 0.296 nm (40 cm1)). The compact spectrometer uses a custom design to project a high-resolution Raman spectrum and a low-resolution fluorescence spectrum on a single charge-coupled device. The natural spectral separation enabled by deep ultraviolet excitation enables wavelength separation of the Raman/fluorescence spectra. The SHERLOC spectrometer was designed to optimize the resolution of the Raman spectral region and the wavelength range of the fluorescence region. The resulting illumination on the charge-coupled device is curved, requiring a segmented, nonlinear wavelength calibration in order to understand the mineralogy and chemistry of Martian materials.
Kyle Uckert↗
The Galactic halo and local intergalactic medium toward PKS 2155-304
Low-resolution UV observations of the bright, low-redshift BL Lac object PKS 2155-304 have been obtained by the HST's high-resolution spectrograph. Attention is here given to results on the number of intergalactic H I Ly-alpha components in the line-of-sight toward this object. The highest-redshift of the observed Ly-alpha systems furnishes a lower limit on the distance of the BL Lac object; this distance is consistent with the approximate redshift deduced from CCD imagery of the probable host galaxy for PKS 2155-304.
Bruhweiler, Frederick C.↗