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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Spaceborne Imaging Radar Project

In June of 1985 the Project Initiation Agreement was signed by the Jet Propulsion Laboratory and the NASA Office of Space Science and Applications for the Spaceborne Imaging Radar Project (SIR). The thrust of the Spaceborne Imaging Radar Project is to continue the evolution of synthetic aperture radar (SAR) science and technology developed during SEASAT, SIR-A and SIR-B missions to meet the needs of the Earth Observing System (EOS) in the mid 1990's. As originally formulated, the Project plans were for a reflight of the SIR-B in 1987, the development of a new SAR, SIR-C, for missions in mid 1989 and early 1990, and the upgrade of SIR-C to EOS configuration with a qualification flight aboard the shuttle in the 1993 time frame (SIR-D). However, the loss of the shuttle Challenger has delayed the first manifest for SIR to early 1990. This delay prompted the decision to drop SIR-B reflight plans and move ahead with SIR-C to more effectively utilize this first mission opportunity. The planning for this project is discussed.

Herman, Neil↗
NASA NTRS1990

The Magellan Venus radar mapping mission

The NASA Magellan Venus Radar Mapper spacecraft, which will be placed into orbit around Venus on August 10, 1990, is described and its mission is discussed. The orbiter's 12-cm wavelength, multimode radar system is examined and the applications of its modes are addressed. In the SAR mode, it can image most of the Venus surface at a resolution of better than 300 m, approaching 120 m over more than half the planet. In the altimeter mode, the radar will determine topographic relief to a vertical accuracy of better than 50 m averaged over a surface resolution cell approximately 10 km in diameter. In the radiometer mode, the radar receiver can determine the surface radio emission brightness temperature with an absolute accuracy of 20 K, at a resolution of 2 K. The nature of the data products and the archiving plans are also considered.

Saunders, R. S.↗
NASA NTRS1993

Techniques and Applications of SAR interferometry for ERS-1: Topographic Mapping, Change Detection, and Slope Measurement

SAR (Synthetic Aperture Radar) interferometry allows the measurement of high resolution topography of terrain from repeat orbit SAR data sets obtained by the ERS-1 AMI (Active Microwave Instrument). The system parameters which affect the accuracy of the topographic maps are errors in determination of the interferometric baseline, non parallel orbit tracks, decorrelation caused by baseline length, thermal noise, and surface change. Surface change can be observed in the interferograms either through decorrelation of the interferometric phase, or coherent phase shifts caused by locally uniform surface displacements. Phase gradient maps can be derived directly from the complex interferograms and can be transformed into surface slopes mapped onto a geometrically corrected grid.

Charles L Werner↗
NASA NTRSDate not supplied

Mapping Inundation from Hurricane Florence (2018) with L-Band Synthetic Aperture Radar, Commercial Imagery, and Ancillary Data via Machine Learning Classification

During and after flooding events, mapping the extent of floodwaters aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. Complimentary optical and SAR images from domestic and foreign entities are brought together through activations of the International Charter: Space and Major Disasters to support response efforts, from true-color, near-infrared, and thermal remote sensing data obtained by NASA, NOAA, and international satellites to the collection of high-resolution true color aerial photography by NOAA and the National Geodetic Survey. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. In this study, true-color NOAA aerial and commercial satellite imagery are used in conjunction with four UAVSAR data swaths centered on the Lumberton and Cape Fear River basins in southeastern North Carolina to develop a Random Forest classification model focused on mapping open water and floodwater otherwise obscured by vegetation or lingering cloud cover. Ancillary building footprint, transportation route, and population data will also be incorporated into the classification scheme to estimate the societal impacts of flooding based on the proximity of features to detected inundation. Preliminary results from the Hurricane Florence case study will be discussed in addition to the limitations of available validation data for assessment of the classifier’s accuracy.

Alexander M Melancon↗
NASA NTRS2021

US Coast Guard Final Memo

A NASA Aeronautics Research Institute (NARI) intern project in Summer 2020 involved the research, design, and sourcing of a small unmanned aerial system (sUAS) for use during U.S. Coast Guard (USCG) search-and-rescue (SAR) missions. This report summarizes the results of the project.

Search and Rescue↗
NASA NTRSDate not supplied

Mapping Inundation from Hurricane Florence (2018) with L-Band Synthetic Aperture Radar, Commercial Imagery, and Ancillary Data via Random Forest Classification

Mapping the extent of floodwaters following extreme rainfall aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. This study seeks to determine how accurately maps of inundation can be generated from L-band SAR imagery through Random Forest classification. Once the extent of water and inundated vegetation is classified, cleanup operations are performed using fuzzy logic to reduce false detections. Estimates of water extent are then combined with datasets describing the distribution of population, buildings, and roads throughout the domain to evaluate societal impacts. Results from the Hurricane Florence case study will be discussed along with the limitations of available validation data for assessment of the classifier’s accuracy.

Alexander Melancon↗
DOE OSTI2020

Antibody dynamics to SARS‐CoV‐2 in asymptomatic COVID‐19 infections

Abstract Background The missing asymptomatic COVID‐19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. Measure Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty‐three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS‐CoV‐2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. Results A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS‐CoV‐2. Different from strong and persistent N‐specific antibodies, S1‐specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. Conclusion Our findings might have important implications for the definition of asymptomatic COVID‐19 infections, diagnosis, serological survey, public health, and immunization strategies.

Lei, Qing↗
NASA NTRS1988

The Earth Observing System

NASA's Earth Observing System (EOS) is a prospective program for earth observation from space using various unmanned, sun-synchronous polar orbit sensor platforms in conjunction with the Space Station to conduct measurements over a period of 15 years. The most important instruments will be the Moderate-Resolution Imaging Spectrometer, the High-Resolution Imaging Spectrometer, a large-area coverage SAR, the Laser Atmospheric Wind Sounder, the Atmospheric IR Sounder, and a Geodynamics and Laser-Ranging System.

Soffen, Gerald A.↗
DOE OSTI2024

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don’t yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures

Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Hypergraph Models of Biological Networks to Identify Genes Critical to Pathogenic Viral Response

Motivation: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems such as protein complexes, metabolic reactions, and signal transduction pathways. Hypergraphs are generalizations of graphs that naturally model multi-way interactions in data, and we therefore seek to understand how they can more faithfully identify, and potentially predict, complex relationships in genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges are differentially expressed genes and vertices represent conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Our results demonstrate the utility of using hypergraphs to represent complex biological systems, and highlight potentially interesting biological results about host response to highly pathogenic viruses.

systems biology, hypergraph, viral infection, biol↗
NASA NTRS1994

Remote sensing of ocean waves: The Surface Wave Process Program experiment

An airborne synthetic aperture radar (SAR) has been used as an interferometer to obtain direct, calibrated measurements of the ocean wind wave directional spectrum. Flights over the same area from three different directions produced reasonably consistent results. The SAR-derived wave data agree well with simultaneous observations by a conventional wave measuring system and with a novel in situ acoustic Doppler system.

Goldstein, R. M.↗
NASA NTRS1992

Identification of sea ice types in spaceborne synthetic aperture radar data

This study presents an approach for identification of sea ice types in spaceborne SAR image data. The unsupervised classification approach involves cluster analysis for segmentation of the image data followed by cluster labeling based on previously defined look-up tables containing the expected backscatter signatures of different ice types measured by a land-based scatterometer. Extensive scatterometer observations and experience accumulated in field campaigns during the last 10 yr were used to construct these look-up tables. The classification approach, its expected performance, the dependence of this performance on radar system performance, and expected ice scattering characteristics are discussed. Results using both aircraft and simulated ERS-1 SAR data are presented and compared to limited field ice property measurements and coincident passive microwave imagery. The importance of an integrated postlaunch program for the validation and improvement of this approach is discussed.

Kwok, Ronald↗
NASA NTRSDate not supplied

NASA GSFC Flood Mapping System (In beta testing)

The authors are developing the NASA GSFC Flood Mapping System, designed to provide near real time, on-demand satellite-based products to disaster management practitioners for requests provided through a website interface. The initial version of the system, which only provides products based on Planetscope data provided by Planet Labs to NASA through the NASA CSDA Program, is currently being beta tested in partnership with the disaster management community and interested research partners. Products include images, NDWI maps, NDVI maps, and water extent maps for flood scenes of interest, the same four products for a specified reference scene, and water extent change maps based on the flood scenes and reference scenes. The team’s vision for the system includes adding products based on all appropriate sources of data that are available at no cost to the project (Landsat, Sentinel-1, Sentinel-2), and obtaining funding for commercial SAR data to provide products in the case where none of the “no-cost” data meets end-user needs. We provide an overview of the system, and discuss the products offered, lessons learned from initial testing, and plans to evolve the system in accordance with our overall vision and the lessons learned.

F. Policelli↗
NASA NTRS2000

IFSAR Simulation Using the Shooting and Bouncing Ray Technique

Interferometric Synthetic Aperture Radar (IFSAR) is a technique that allows an automated way to carry out terrain mapping. IFSAR is carried out by first generating a SAR image pair from two antennas that are spatially separated. The phase difference between the SAR image pair is proportional to the topography. After registering the SAR images, the difference in phase in each pixel is extracted to generate an interferogram. Since the phase can only be measured within 2pi radians, phase unwrapping is carried out to extract the absolute phase for each pixel that will be proportional to the local height. While IFSAR algorithm is typically applied to measurement data, it is useful to develop an IFSAR simulator to develop a better understanding of the IFSAR technique. The IFSAR simulator can be used in choosing system parameters, experimenting with processing procedures and mission planning. In this paper we will present an IFSAR simulation methodology to simulate the interferogram based on the shooting and bouncing ray (SBR) technique. SBR is a standard ray-tracing technique used to simulate scattering from large, complex targets. SBR is carried out by shooting rays at the target or scene. At the exit point of each ray, a ray-tube integration is done to find its contribution to the total field. A fast algorithm has been developed for the SBR for simulating SAR images of complex targets. In the IFSAR simulation, we build upon the fast SAR simulation technique. Given the antenna pair configuration, radar system parameters and the geometrical description of the scene, we first simulate two SAR images from each antenna. After post processing the two SAR images, we generate an interferogram. Phase unwrapping is then performed on the interferogram to arrive at the desired terrain map. We will present results from the SBR-based IFSAR simulator. The results will include terrain map reconstruction of urban environments. The reconstruction will be compared to the ground truth to examine the fidelity of the simulation. We will also investigate the effect of multi-bounce scattering in urban environments on phase unwrapping and reconstruction.

Houshmand, Bijan↗
DOE OSTI2023

Sequence similarity between SARS-CoV-2 nucleocapsid and multiple sclerosis-associated proteins provides insight into viral neuropathogenesis following infection

Abstract The novel coronavirus SARS-CoV-2 continues to cause death and disease throughout the world, underscoring the necessity of understanding the virus and host immune response. From the start of the pandemic, a prominent pattern of central nervous system (CNS) pathologies, including demyelination, has emerged, suggesting an underlying mechanism of viral mimicry to CNS proteins. We hypothesized that immunodominant epitopes of SARS-CoV-2 share homology with proteins associated with multiple sclerosis (MS). Using PEPMatch, a newly developed bioinformatics package which predicts peptide similarity within specific amino acid mismatching parameters consistent with published MHC binding capacity, we discovered that nucleocapsid protein shares significant overlap with 22 MS-associated proteins, including myelin proteolipid protein (PLP). Further computational evaluation demonstrated that this overlap may have critical implications for T cell responses in MS patients and is likely unique to SARS-CoV-2 among the major human coronaviruses. Our findings substantiate the hypothesis of viral molecular mimicry in the pathogenesis of MS and warrant further experimental exploration.

60 APPLIED LIFE SCIENCES↗