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At least 1,063 records · Page 59

Use of NASA Satellite Data in Aiding Mississippi Barrier Island Restoration Projects

This presentation discusses a NASA Stennis Space Center project in which NASA-supported satellite and aerial data is being used to aid state and federal agencies in restoring the Mississippi barrier islands. Led by the Applied Science and Technology Project Office (ASTPO), this project will produce geospatial information products from multiple NASA-supported data sources, including Landsat, ASTER, and MODIS satellite data as well as ATLAS multispectral, CAMS multispectral, AVIRIS hyperspectral, EAARL, and other aerial data. Project objectives include the development and testing of a regional sediment transport model and the monitoring of barrier island restoration efforts through remote sensing. Barrier islands provide invaluable benefits to the State of Mississippi, including buffering the mainland from storm surge impacts, providing habitats for valuable wildlife and fisheries habitat, offering accessible recreational opportunities, and preserving natural environments for educating the public about coastal ecosystems and cultural resources. Unfortunately, these highly valued natural areas are prone to damage from hurricanes. For example, Hurricane Camille in 1969 split Ship Island into East and West Ship Island. Hurricane Georges in 1998 caused additional land loss for the two Ship Islands. More recently, Hurricanes Ivan, Katrina, Rita, Gustav, and Ike impacted the Mississippi barrier islands. In particular, Hurricane Katrina caused major damage to island vegetation and landforms, killing island forest overstories, overwashing entire islands, and causing widespread erosion. In response, multiple state and federal agencies are working to restore damaged components of these barrier islands. Much of this work is being implemented through federally funded Coastal Impact Assessment and Mississippi Coastal Improvement programs. One restoration component involves the reestablishment of the island footprints to that in 1969. Our project will employ NASA remote sensing data and products to support these federally funded efforts on multiple fronts. Landsat and ASTER data is being analyzed to assess changes in barrier island land cover over the last 35 years. ASTER, SRTM, and EAARL terrain products and other NASA airborne imagery are being applied in assessing changes in barrier island geomorphology and geospatial extent. MODIS data is being examined as a tool for sediment transport modeling by supplying geospatial data that quantifies in-water sediment concentrations. MODIS satellite data is being assessed for monitoring changes in the spatial extent of individual barrier islands. Results thus far indicate that NASA data products are useful in assessing barrier island conditions and changes. This value is enhanced with additional historical geospatial data, commercial high resolution satellite data, other non-NASA aerial imagery, and field survey data. The project s products are relevant to the Gulf of Mexico Alliance priority issues, including coastal habitat conservation, restoration and coastal community resilience. Such products will be available to state and federal agencies involved with coastal restoration. Potential end-users of these products include the National Park Service, U.S. Geological Survey, U.S. Army Corps of Engineers, Environmental Protection Agency, Mississippi Department of Environmental Quality, and Mississippi Department of Marine Resources.

Giardino, Marco↗

Effect of subjectively enhancing the initial vorticity field in a short-range numerical forecast

The paper tests a simple method to incorporate subsynoptic-scale information into the initial conditions of a forecast model. The amplitude, orientation and vertical structure of the vorticity field associated with the subsynoptic-scale disturbance are estimated subjectively; this is done using a combination of climatological and physical models together with all available data. The initial values of geopotential are then obtained in the vicinity of the subsynoptic-scale disturbance, as over the rest of the domain, through the balance equation. Two sets of initial conditions are tested in 12-hr forecasts using a six-layer version of a primitive equation forecast model (Anthes and Warner, 1978). The analysis schemes consisted of (1) a careful subjective analysis of radiosonde data with a high-resolution objective interpolation, and (2) the same preceding analysis but including data derived from the enhanced vorticity fields in the vicinity of the subsynoptic-scale disturbance. The results are discussed in some detail.

Fried, G. D.↗

The S-PLUS Fifth Data Release: Over 4500 Square Degrees of the Southern Sky and a Multicolor View of the Hydra and Antlia Galaxy Clusters

Abstract We present the fifth data release (DR5) of the Southern Photometric Local Universe Survey (S-PLUS), covering 4592 deg 2 across 2491 fields. Observations were conducted with the T80-South, a Brazilian robotic telescope equipped with the Javalambre 12-filter system, containing five broadband and seven narrowband filters. Data products feature FITS images and extensive catalogs containing fluxes, magnitudes, and shape parameters for over 113 million detections. In addition, several value-added catalogs are provided, offering photometric redshifts (photo- zs ), object classifications, masks, and extinction coefficients. For the first time, this release includes coverage of 110 deg 2 along the Galactic disk, facilitating new research into Galactic structure and stellar populations. The release also provides full coverage of the Hydra Supercluster and numerous other nearby clusters with improved data reduction and calibration, enhancing photo- z accuracy, which is vital for large-scale structure studies. A preliminary analysis of the Hydra and Antlia galaxy clusters up to 5 × R 200 yields an updated catalog of 1706 cluster members based on both spectroscopic and high-quality photo- zs . Our photometric data shows that both clusters have a similar proportion of galaxies with an H α excess relative to their clustercentric distance, though Hydra has a higher fraction near its center. Additionally, the spatial distribution of all objects in our sample highlights a bridge connecting both clusters. We verify that S-PLUS DR5 provides a solid foundation for future scientific investigations, ranging from solar system studies to cosmology.

Vinicius Rodrigues de Lima, Erik [Universidade de ↗

An application of the Multi-Purpose System Simulation /MPSS/ model to the Monitor and Control Display System /MACDS/ at the National Aeronautics and Space Administration /NASA/ Goddard Space Flight Center /GSFC/

The Multi-Purpose System Simulator (MPSS) model was used to investigate the current and projected performance of the Monitor and Control Display System (MACDS) at the Goddard Space Flight Center in processing and displaying launch data adequately. MACDS consists of two interconnected mini-computers with associated terminal input and display output equipment and a disk-stored data base. Three configurations of MACDS were evaluated via MPSS and their performances ascertained. First, the current version of MACDS was found inadequate to handle projected launch data loads because of unacceptable data backlogging. Second, the current MACDS hardware with enhanced software was capable of handling two times the anticipated data loads. Third, an up-graded hardware ensemble combined with the enhanced software was capable of handling four times the anticipated data loads.

Mill, F. W.↗

NASA B-57B severe storms flight program

The B-57B Severe Storms Flight Program gathers data to characterize atmosphere anomalies such as wind shear, turbulence, and microbursts at altitudes up to 1000 feet (300 meters). These data are used to enhance the knowledge of atmospheric processes, to improve aviation safety, to develop systems technology and piloting technique for avoiding hazards and to increase the understanding of the causes of related aircraft accidents. The NASA Dryden Flight Research Facility B-57B aircraft has participated in several severe storms data collection programs such as the Joint Airport Weather Studies (JAWS) located in Denver, Colorado area, Operation Rough Rider located in the Norman, Oklahoma area with the National Severe Storms Laboratory, and Mountain and desert turbulence in the Edwards Air Force Base, California area. Flight data are presented from flights which encountered the wind shear, turbulence and microburst anomalies. These flight results are discussed and some conclusions are made relating to these atmospheric anomalies.

Painter, W. D.↗

SP mountain data analysis

An analysis of synthetic aperture radar data of SP Mountain was undertaken to demonstrate the use of digital image processing techniques to aid in geologic interpretation of SAR data. These data were collected with the ERIM X- and L-band airborne SAR using like- and cross-polarizations. The resulting signal films were used to produce computer compatible tapes, from which four-channel imagery was generated. Slant range-to-ground range and range-azimuth-scale corrections were made in order to facilitate image registration; intensity corrections were also made. Manual interpretation of the imagery showed that L-band represented the geology of the area better than X-band. Several differences between the various images were also noted. Further digital analysis of the corrected data was done for enhancement purposes. This analysis included application of an MSS differencing routine and development of a routine for removal of relief displacement. It was found that accurate registration of the SAR channels is critical to the effectiveness of the differencing routine. Use of the relief displacement algorithm on the SP Mountain data demonstrated the feasibility of the technique.

Rawson, R. F.↗

Current Status, Performance and Plans for the NASA Airborne Visible and Infrared Imaging Spectrometer (AVIRIS)

The status of the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) is reported at the beginning of the current flight season. Sensor performance based on laboratory measurements and trend data as well as a review of end of 1995 season performance is given as a measure of expected performance during the 1996 season which began in March of 1996. Recent improvements to the sensor's internal calibration source and measurements of instrument parameters are described. The effects of these enhancements on the reported data are also discussed along with and update onflight schedules and plans for 1996 flight operations.

Airborne↗

EOSDIS Archive & Data Stewardship

NASA’s Earth Observing System Data and Information System’s (EOSDIS) was built to archive and distribute earth science data from flight and research programs. At the close of FY2020, the data collection had grown to over 42 petabytes distributed across the US. This presentation describes fundamentals associated with managing a free and open archive of this size for a worldwide, multi-discipline user community. The presentation is prepared for the Committee on Earth Observation Satellites (CEOS), which strives to enhance international coordination and data exchange and to optimize societal benefit. The Working Group on Information System and Services (WGISS) is a forum within CEOS for the collaboration with other international and domestic agencies io the development of Earth observation data archives, systems and services. This presentation reviews the construct of the EOSDIS archives, formats for long term archive, preservation of appropriate data and documents, and challenges facing the community.

earth science↗

Solvent-Induced Swelling Behaviors of Microphase-Separated Polystyrene- block -Poly(ethylene oxide) Thin Films Investigated Using In Situ Spectroscopic Ellipsometry and Single-Molecule Fluorescence Microscopy

Block copolymers have attracted considerable interest in the fields of nanoscience and nanotechnology, because these polymers afford well-defined nanostructures via self-assembly. An in-depth understanding of solvent effects on the physicochemical properties of these microdomains is crucial for their preparation and utilization. Herein, we employed in situ spectroscopic ellipsometry and single-molecule fluorescence techniques to gain detailed insights into microdomain properties in polystyrene-block-poly(ethylene oxide) (PS-b-PEO) films exposed to ethanol- and water-saturated N 2 . We observed a quick increase and a subsequent gradual decrease in the ellipsometric thickness of PS-b-PEO films upon exposure to ethanol-saturated N 2 . This observation was unexpected because ethanol-saturated N 2 induced negligible thickness change for PS and PEO homopolymer films. The similarity in maximum thickness gain observed under ethanol- and water-saturated N 2 implied the swelling of PEO microdomains. Ethanol vapor permeation through the PEO microdomains was supported by the red-shift of the ensemble and single-molecule fluorescence emission of Nile red in PS-b-PEO films. Single-molecule tracking data showed the initial enhancement and subsequent reduction of the diffusion of hydrophilic sulforhodamine B molecules in PS-b-PEO films upon exposure to ethanol-saturated N 2 , consistent with the spectroscopic ellipsometry results. Furthermore, the higher ethanol susceptibility of the PEO microdomains was attributable to their amorphous nature, as shown by FTIR data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Semisupervised Learning for Seismic Monitoring Applications

The impressive performance that deep neural networks demonstrate on a range of seismic monitoring tasks depends largely on the availability of event catalogs that have been manually curated over many years or decades. However, the quality, duration, and availability of seismic event catalogs vary significantly across the range of monitoring operations, regions, and objectives. Semisupervised learning (SSL) enables learning from both labeled and unlabeled data and provides a framework to leverage the abundance of unreviewed seismic data for training deep neural networks on a variety of target tasks. We apply two SSL algorithms (mean-teacher and virtual adversarial training) as well as a novel hybrid technique (exponential average adversarial training) to seismic event classification to examine how unlabeled data with SSL can enhance model performance. In general, we find that SSL can perform as well as supervised learning with fewer labels. We also observe in some scenarios that almost half of the benefits of SSL are the result of the meaningful regularization enforced through SSL techniques and may not be attributable to unlabeled data directly. Lastly, the benefits from unlabeled data scale with the difficulty of the predictive task when we evaluate the use of unlabeled data to characterize sources in new geographic regions. Finally, in geographic areas where supervised model performance is low, SSL significantly increases the accuracy of source-type classification using unlabeled data.

58 GEOSCIENCES↗

Mathematical analysis study for radar data processing and enchancement. Part 2: Modeling of propagation path errors

A study is performed under NASA contract to evaluate data from an AN/FPS-16 radar installed for support of flight programs at Dryden Flight Research Facility of NASA Ames Research Center. The purpose of this study is to provide information necessary for improving post-flight data reduction and knowledge of accuracy of derived radar quantities. Tracking data from six flights are analyzed. Noise and bias errors in raw tracking data are determined for each of the flights. A discussion of an altitude bias error during all of the tracking missions is included. This bias error is defined by utilizing pressure altitude measurements made during survey flights. Four separate filtering methods, representative of the most widely used optimal estimation techniques for enhancement of radar tracking data, are analyzed for suitability in processing both real-time and post-mission data. Additional information regarding the radar and its measurements, including typical noise and bias errors in the range and angle measurements, is also presented. This report is in two parts. This is part 2, a discussion of the modeling of propagation path errors.

James, R.↗

Monitoring and Modeling Astronaut Occupational Radiation Exposures in Space: Recent Advances

In 1982 astronauts were declared to be radiation workers by OSHA, and as such were subject to the rules and regulations applied to that group. NASA was already aware that space radiation was a hazard to crewmembers and had been studying and monitoring astronaut doses since 1962 at the Johnson Space Center. It was quickly realized NASA would not be able to accomplish all of its goals if the astronauts were subject to the ground based radiation worker limits, and thus received a waiver from OSHA to establish independent limits. As part of the stipulation attached to setting new limits, OSHA included a requirement to perform preflight dose projections for each crew and inform them of the associated risks. Additional requirements included measuring doses from various sources during the flight, making every effort to prevent a crewmember from exceeding the new limits, and keeping all exposures As Low As Reasonably Achievable (a.k.a. ALARA - a common health physics principle). The assembly of the International Space Station (ISS) and its initial manned operations will coincide with the 4-5 year period of high space weather activity at the next maximum in the solar cycle. For the first time in NASA's manned program, US astronauts will be in orbit continuously throughout a solar maximum period. During this period, crews are at risk of significantly increased radiation exposures due to solar particle events and trapped electron belt enhancements following geomagnetic storms. The problem of protecting crews is compounded by the difficulty of providing continuous real-time monitoring over a period of a decade in an era of tightly constrained budgets. In order to prepare for ISS radiological support needs, the NASA Space Radiation Analysis Group and the NOAA Space Environment Center have undertaken a multiyear effort to improve and automate ground-based space weather monitoring systems and real-time radiation analysis tools. These improvements include a coupled, automated space weather monitoring and alarm system--SPE exposure analysis system, an advanced space weather data distribution and display system, and a high-fidelity space weather simulation system. In addition, significant new real-time space weather data sets, which will enhance the forecasting and now-casting of near-Earth space environment conditions, are being made available through unique NASA-NOAA-USAF collaborations. These new data sets include coronal mass ejection monitoring by the Solar and Heliospheric Observatory (SOHO) and in-situ plasma and particle monitoring at the L1 libration point by the Solar Wind Monitor (SWIM) and Advanced Composition Explorer (ACE) spacecraft. Advanced real-time radiation monitoring data from charged particle telescopes and tissue equivalent proportional counters will also be available to assist crew and flight controllers in monitoring the external and intravehicular radiation environment.

Weyland, Mark↗

Validation and parameterization of a novel physics-constrained neural dynamics model applied to turbulent fluid flow

We report, in fluid physics, data-driven models to enhance or accelerate time to solution are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In the context of reduced order models of high-dimensional time-dependent fluid systems, machine learning methods grant the benefit of automated learning from data, but the burden of a model lies on its reduced-order representation of both the fluid state and physical dynamics. In this work, we build a physics-constrained, data-driven reduced order model for Navier–Stokes equations to approximate spatiotemporal fluid dynamics in the canonical case of isotropic turbulence in a triply periodic box. The model design choices mimic numerical and physical constraints by, for example, implicitly enforcing the incompressibility constraint and utilizing continuous neural ordinary differential equations for tracking the evolution of the governing differential equation. We demonstrate this technique on a three-dimensional, moderate Reynolds number turbulent fluid flow. In assessing the statistical quality and characteristics of the machine-learned model through rigorous diagnostic tests, we find that our model is capable of reconstructing the dynamics of the flow over large integral timescales, favoring accuracy at the larger length scales. More significantly, comprehensive diagnostics suggest that physically interpretable model parameters, corresponding to the representations of the fluid state and dynamics, have attributable and quantifiable impact on the quality of the model predictions and computational complexity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Conference on Applications of Digital Image Processing to Astronomy, Pasadena, Calif., August 20-22, 1980, Proceedings

The astronomic applications of non-military digital image processing are covered in this conference volume. Systems like CCD's, interactive data analysis facilities, stellar speckle interferometry, sky flux subsystems, guide star systems and various image processing systems are described. Techniques in photometry including filtering, automatic photometry, and image restoration are examined. Digital spectral analyses of galaxies, supernova remnants, stars and other celestial bodies are discussed together with algorithms developed to calibrate, clean up, enhance, and quantitatively analyze data. The techniques of image processing permit astronomers to make much more efficient use of their data for both subjective and quantitative analyses. Future missions, such as the Space Telescope, representing a vast data base are briefly covered.

Elliott, D. A.↗

Innovation in Radiological Security, Part 2 of 2 – Insights into Developing a Cloud-hosted Security Technology

A Sentry Remote Monitoring System (Sentry-RMS) is a stand-alone security system that provides detection, assessment, and communication of priority alarms as an additional means of thwarting internal and external threats to sites that maintain radiological material. The SEntry-RMS CommUnications and REsponse (Sentry-SECURE) platform is an optional feature of the Sentry-RMS that relays priority alarm information to the identified response stakeholders. Sentry-SECURE is hosted in a cloud environment that abstracts the data owner’s and data consumer’s platforms to allow for greater information sharing. This promotes situational awareness amongst authorized users and enables future innovation among modern response platforms. When securely architecting a cloud solution such as this, the use of design paradigms can be an effective tool to increase the accuracy and reliability of cyber- and information-security-related decisions made throughout the development process. This approach also supports the categorization of design considerations into three levels: industry concepts, project approaches, and data protections for digital processes. Industry concepts consist of the notional underpinnings that guide or motivate a security process, system, or design but often lack any tangible attributes. Project approaches represent decisions made during the design and development process to prioritize a solution, method, or practice above another that may provide a comparable functional output but lacks a desired security benefit. Data protections for digital processes represent the selection, integration, and implementation of specific controls for a given asset. This paper will explore specific examples of how Sentry-SECURE has been designed to account for considerations at each of these three levels, while balancing the operational intent of the platform with the security enhancements necessary to maintain data integrity, availability, and confidentiality.

assessment, RMS, security, physical, cloud, Cyber ↗

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Brown, Richard B.↗

Revisiting Five Years of CASMI Contests with EPA Identification Tools

Software applications for high resolution mass spectrometry (HRMS)-based non-targeted analysis (NTA) continue to enhance chemical identification capabilities. Given the variety of available applications, determining the most fit-for-purpose tools and workflows can be difficult. The Critical Assessment of Small Molecule Identification (CASMI) contests were initiated in 2012 to provide a means to evaluate compound identification tools on a standardized set of blinded tandem mass spectrometry (MS/MS) data. Five CASMI contests have resulted in recommendations, publications, and invaluable datasets for practitioners of HRMS-based screening studies. The US Environmental Protection Agency’s (EPA) CompTox Chemicals Dashboard is now recognized as a valuable resource for compound identification in NTA studies. However, this application was too new and immature in functionality to participate in the five previous CASMI contests. In this work, we performed compound identification on all five CASMI contest datasets using Dashboard tools and data in order to critically evaluate Dashboard performance relative to that of other applications. CASMI data was accessed via the CASMI webpage and processed for use in our spectral matching and identification workflow. Relative to applications used by former contest participants, our tools, data, and workflow performed well, placing more challenge compounds in the top five of ranked candidates than did the winners of three contest years and tying in a fourth. In addition, we conducted an in-depth review of the CASMI structure sets and made these reviewed sets available via the Dashboard. Our results suggest that Dashboard data and tools would enhance chemical identification capabilities for practitioners of HRMS-based NTA.

97 MATHEMATICS AND COMPUTING↗

NASA GeneLab: Open Science for Life in Space

NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. The open-access GeneLab repository currently consists of over 300 omics datasets generated by biological experiments, involving various model organisms, that are relevant to spaceflight. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. To aide GeneLab’s efforts to harmonize and democratize space-relevant omics data, over 130 scientists have joined one of four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG) and together helped develop and adopted standard data analysis workflows for all data types available in GeneLab. Currently, the GeneLab Data System includes a data repository with federated search capability, an online controlled-access toolshed powered by "Galaxy" for users to process data with vetted standard workflows, a workspace for data sharing, a data submission portal, and the ability to browse and visualize transcriptomics processed data. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. The visualization portal enhances GeneLab’s ability to democratize omics data by removing the need for bioinformatics expertise to interpret transcriptomics data hosted on GeneLab. This presentation will provide an over-view of NASA’s GeneLab including how to navigate the GeneLab Data System and will conclude by providing resources for opportunities to work with GeneLab and NASA at large.

Amanda M Saravia-Butler↗