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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

CANDELS Visual Classifications: Scheme, Data Release, and First Results

We have undertaken an ambitious program to visually classify all galaxies in the five CANDELS fields down to H <24.5 involving the dedicated efforts of 65 individual classifiers. Once completed, we expect to have detailed morphological classifications for over 50,000 galaxies spanning 0 < z < 4 over all the fields. Here, we present our detailed visual classification scheme, which was designed to cover a wide range of CANDELS science goals. This scheme includes the basic Hubble sequence types, but also includes a detailed look at mergers and interactions, the clumpiness of galaxies, k-corrections, and a variety of other structural properties. In this paper, we focus on the first field to be completed - GOODS-S, which has been classified at various depths. The wide area coverage spanning the full field (wide+deep+ERS) includes 7634 galaxies that have been classified by at least three different people. In the deep area of the field, 2534 galaxies have been classified by at least five different people at three different depths. With this paper, we release to the public all of the visual classifications in GOODS-S along with the Perl/Tk GUI that we developed to classify galaxies. We present our initial results here, including an analysis of our internal consistency and comparisons among multiple classifiers as well as a comparison to the Sersic index. We find that the level of agreement among classifiers is quite good and depends on both the galaxy magnitude and the galaxy type, with disks showing the highest level of agreement and irregulars the lowest. A comparison of our classifications with the Sersic index and restframe colors shows a clear separation between disk and spheroid populations. Finally, we explore morphological k-corrections between the V-band and H-band observations and find that a small fraction (84 galaxies in total) are classified as being very different between these two bands. These galaxies typically have very clumpy and extended morphology or are very faint in the V-band.

Visual↗
NASA NTRS1995

Visualization tools for the processing of airglow data from RAIDS

In anticipation of large data sets associated with a number of atmospheric imaging instruments being prepared for long term global coverage, NRL is developing graphical interfaces for all aspects of the program. For the first of these projects, RAIDS (the Remote Atmospheric and Ionospheric Detection System), a graphical approach to data handling, visualization, and analysis is envisioned and will set the stage for the satellites that follow. An overall system of hardware and a set of software 'tools,' that will allow for both the routine handling of all data and the analysis of large data sets assembled by scientists and instrument engineers, are currently being developed. The software for standard processing and visualization of instrument data is independent of computer platform and will allow for easy adaptation from one experiment to another. The processing will produce data sets that have similar characteristics, allowing for easy comparison of data obtained under similar circumstances. The visualization of both the engineering and scientific data is an important part of the system. By creating graphical environments for engineering evaluations and for scientific analysis data sets can be viewed and analyzed rapidly. This rapid analysis of data will contribute towards a greater portion of the RAIDS data being utilized.

Miller, Gordon J.↗
NASA NTRS2006

A-Train Data Depot: Integrating, Visualizing, and Extracting Cloudsat, CALIPSO, MODIS, and AIRS Atmospheric Measurements Along the A-Train Tracks

The succession of US and international Earth observing satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000). The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot (ATDD), to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The ATDD will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archiving for fast data access, access to remote data without unnecessary data transfers, and data retrieval by users finding data desirable for further study. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be foilowed by associated measurements from TVILS, =MI, HIRDLS, sad TES. Given the independent nature of instrumentlplatform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be illustrated and discussed. The project's early visualizations and analysis efforts illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗
NASA NTRS1995

Geophysical data analysis and visualization using the Grid Analysis and Display System

Several problems posed by the rapidly growing volume of geophysical data are described, and a selected set of existing solutions to these problems is outlined. A recently developed desktop software tool called the Grid Analysis and Display System (GrADS) is presented. The GrADS' user interface is a natural extension of the standard procedures scientists apply to their geophysical data analysis problems. The basic GrADS operations have defaults that naturally map to data analysis actions, and there is a programmable interface for customizing data access and manipulation. The fundamental concept of the GrADS' dimension environment, which defines both the space in which the geophysical data reside and the 'slice' of data which is being analyzed at a given time, is expressed The GrADS' data storage and access model is described. An argument is made in favor of describable data formats rather than standard data formats. The manner in which GrADS users may perform operations on their data and display the results is also described. It is argued that two-dimensional graphics provides a powerful quantitative data analysis tool whose value is underestimated in the current development environment which emphasizes three dimensional structure modeling.

Doty, Brian E.↗
NASA NTRS1997

Visualization of IACG data

The common data format (CDF), adopted by the international solar terrestrial physics (ISTP) program and the Interagency Consultative Group (IACG), is considered. Extensive data sharing and data analysis are needed to ensure the success of the ISTP/IACG program. The CDF user guidelines and tools for creation, visualization and manipulation are underlined. Computer software applications based on CDF data sets and designed using ISTP/IACG guidelines are shown.

Kessel, Ramona L.↗
NASA NTRS2007

A-Train Data Search and Visualization to Facilitate Multi-Instrument Cloud Studies

Now that the A-Train suite of datasets have become more mature, new and innovative science utilizing the various products has become more reliable and challenging. To perform multi-satellite research with A-Train data originating from heterogenous missions, scientists must access, subset visualize and analyze user specified datasets in ways unique to the dataset. Then hte datasets need to be co-registered and maybe merged. The A-Train Data Depot (ATDD) has been developed to save each scientist the effort and expense of developing these functions individually.

Kempler, Steven↗
NASA NTRS1989

Volumetric visualization of 3D data

In recent years, there has been a rapid growth in the ability to obtain detailed data on large complex structures in three dimensions. This development occurred first in the medical field, with CAT (computer aided tomography) scans and now magnetic resonance imaging, and in seismological exploration. With the advances in supercomputing and computational fluid dynamics, and in experimental techniques in fluid dynamics, there is now the ability to produce similar large data fields representing 3D structures and phenomena in these disciplines. These developments have produced a situation in which currently there is access to data which is too complex to be understood using the tools available for data reduction and presentation. Researchers in these areas are becoming limited by their ability to visualize and comprehend the 3D systems they are measuring and simulating.

Russell, Gregory↗
NASA NTRS2018

Improving NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA: The Research Access initiative is part of the agency's framework for increasing public access to scientific publications and digital scientific data. The initiative follows the release of White House Office of Science and Technology Policy's (OSTP) memorandum "Increasing Access to the Results of Federally Funded Research," to ensure federally funded research is available to the public within one year of publication. NASA answered the mandate by creating an agency plan entitled "NASA Plan for Increasing Access to the Results of Scientific Research" and associated policy, NPD 2230.1, Research Data and Publication Access. Principles in NASA SMD Strategic Plan for Scientific Data and Computing: Continued free and open access to scientific data for any use. Improved ease of use and discoverability. Enhanced science applications and new use cases. Incorporates best practices and "state of the art" through partnerships. Earth Data and Systems are Evolving: Increasing archive and file sizes. More complicated data structures. More user-friendly and data services. What is the future direction?

Liu, Zhong↗
NASA NTRS1996

ICASE/LaRC Symposium on Visualizing Time-Varying Data

Time-varying datasets present difficult problems for both analysis and visualization. For example, the data may be terabytes in size, distributed across mass storage systems at several sites, with time scales ranging from femtoseconds to eons. In response to these challenges, ICASE and NASA Langley Research Center, in cooperation with ACM SIGGRAPH, organized the first symposium on visualizing time-varying data. The purpose was to bring the producers of time-varying data together with visualization specialists to assess open issues in the field, present new solutions, and encourage collaborative problem-solving. These proceedings contain the peer-reviewed papers which were presented at the symposium. They cover a broad range of topics, from methods for modeling and compressing data to systems for visualizing CFD simulations and World Wide Web traffic. Because the subject matter is inherently dynamic, a paper proceedings cannot adequately convey all aspects of the work. The accompanying video proceedings provide additional context for several of the papers.

Banks, D. C.↗
NASA NTRS2004

Software and Algorithms for Biomedical Image Data Processing and Visualization

A new software equipped with novel image processing algorithms and graphical-user-interface (GUI) tools has been designed for automated analysis and processing of large amounts of biomedical image data. The software, called PlaqTrak, has been specifically used for analysis of plaque on teeth of patients. New algorithms have been developed and implemented to segment teeth of interest from surrounding gum, and a real-time image-based morphing procedure is used to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The PlaqTrak system integrates these components into a single software suite with an easy-to-use GUI (see Figure 1) that allows users to do an end-to-end run of a patient s record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image. The automated and accurate processing of the captured images to segment each tooth [see Figure 2(a)] and then detect plaque on a tooth-by-tooth basis is a critical component of the PlaqTrak system to do clinical trials and analysis with minimal human intervention. These features offer distinct advantages over other competing systems that analyze groups of teeth or synthetic teeth. PlaqTrak divides each segmented tooth into eight regions using an advanced graphics morphing procedure [see results on a chipped tooth in Figure 2(b)], and a pattern recognition classifier is then used to locate plaque [red regions in Figure 2(d)] and enamel regions. The morphing allows analysis within regions of teeth, thereby facilitating detailed statistical analysis such as the amount of plaque present on the biting surfaces on teeth. This software system is applicable to a host of biomedical applications, such as cell analysis and life detection, or robotic applications, such as product inspection or assembly of parts in space and industry.

Talukder, Ashit↗
NASA NTRS2001

D3: A Collaborative Infrastructure for Aerospace Design

DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid dynamics) model executions. DARWIN captures, stores and indexes data, manages derived knowledge (such as visualizations across multiple data sets) and provides an environment for designers to collaborate in the analysis of the results of testing. DARWIN is an interesting application because it supports high volumes of data, integrates multiple modalities of data display (e.g. images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and view of data.

Walton, Joan↗
NASA NTRS2011

User Centered, Application Independent Visualization of National Airspace Data

This paper describes an application independent software tool, IV4D, built to visualize animated and still 3D National Airspace System (NAS) data specifically for aeronautics engineers who research aggregate, as well as single, flight efficiencies and behavior. IV4D was origin ally developed in a joint effort between the National Aeronautics and Space Administration (NASA) and the Air Force Research Laboratory (A FRL) to support the visualization of air traffic data from the Airspa ce Concept Evaluation System (ACES) simulation program. The three mai n challenges tackled by IV4D developers were: 1) determining how to d istill multiple NASA data formats into a few minimal dataset types; 2 ) creating an environment, consisting of a user interface, heuristic algorithms, and retained metadata, that facilitates easy setup and fa st visualization; and 3) maximizing the user?s ability to utilize the extended range of visualization available with AFRL?s existing 3D te chnologies. IV4D is currently being used by air traffic management re searchers at NASA?s Ames and Langley Research Centers to support data visualizations.

Murphy, James R.↗
NASA NTRS1994

Cpt 2.0: A 2-D Fluid Visualization Program for Unsteady Data

Cpt is an interactive two dimensional fluid visualization program for unsteady data sets. Cpt is capable of showing the velocity and scalar fields, calculating streaml@nes and contours, advecting particles, bubblers and more. The user interface is simple point and click and most of its operations are deducible from a few minutes of experimentation.

Levit, Creon↗
NASA NTRS2000

An Architecture for Real-Time Interpretation and Visualization of Structural Sensor Data in a Laboratory Environment

A visualization system is being developed out of the need to monitor, interpret, and make decisions based on the information from several thousand sensors during experimental testing to facilitate development and validation of structural health monitoring algorithms. As an added benefit the system will enable complete real-time sensor assessment of complex test specimens. Complex structural specimens are routinely tested that have hundreds or thousands of sensors. During a test, it is impossible for a single researcher to effectively monitor all the sensors and subsequently interesting phenomena occur that are not recognized until post-test analysis. The ability to detect and alert the researcher to these unexpected phenomena as the test progresses will significantly enhance the understanding and utilization of complex test articles. Utilization is increased by the ability to halt a test when the health monitoring algorithm response is not satisfactory or when an unexpected phenomenon occurs, enabling focused investigation potentially through the installation of additional sensors. Often if the test continues, structural changes make it impossible to reproduce the conditions that exhibited the phenomena. The prohibitive time and costs associated with fabrication, sensoring, and subsequent testing of additional test articles generally makes it impossible to further investigate the phenomena. A scalable architecture is described to address the complex computational demands of structural health monitoring algorithm development and laboratory experimental test monitoring. The researcher monitors the test using a photographic quality 3D graphical model with actual sensor locations identified. In addition, researchers can quickly activate plots displaying time or load versus selected sensor response along with the expected values and predefined limits. The architecture has several key features. First, distributed dissimilar computers may be seamlessly integrated into the information flow. Second, virtual sensors may be defined that are complex functions of existing sensors or other virtual sensors. Virtual sensors represent a calculated value not directly measured by particular physical instrument. They can be used, for example, to represent the maximum difference in a range of sensors or the calculated buckling load based on the current strains. Third, the architecture enables autonomous response to preconceived events, where by the system can be configured to suspend or abort a test if a failure is detected in the load introduction system. Fourth, the architecture is designed to allow cooperative monitoring and control of the test progression from multiple stations both remote and local to the test system. To illustrate the architecture, a preliminary implementation is described monitoring the Stitched Composite Wing recently tested at LaRC.

Doggett, William↗
NASA NTRS2019

Creating Data-Driven Vector Visualizations of Satellite Orbit Tracks Using NASA GIBS and Worldview

NASA Earth Observing System (EOS) currently operates dozens of remote sensing satellites, many of which can be viewed directly in NASA’s open-source Worldview application. Much of this satellite imagery can be viewed in near-real time as it is processed and served by NASA’s Global Imagery Browse Service (GIBS). To better educate users on the time and location of imagery, GIBS serves orbit track specific layers for each satellite. Worldview has historically served these layers as raster images but recent updates have enabled the application to now serve these layers using vector tiles. With the release of Worldview v3.0, orbit track layers can be displayed using mapbox vector tiles (MVT). This visualization format allows users to not only view and change the color of orbit track layers, as they could do previously with rasters, but also inspect individual vector points and filter layers by specific parameters such as time. The data contained within a MVT is further enhanced in Worldview with the combination of a JSON description file served from GIBS used to describe the MVT data. This presentation will provide an overview of the process of consuming orbit track vector tiles and data files from GIBS using a pipeline to configure, build and ultimately display the orbit tracks in Worldview. Furthermore, the presentation aims to describe how others can leverage our open-source code to display and enhance vector layers in their own applications.

Rice, Zachary↗
NASA NTRS1995

Data handling and visualization for NASA's science programs

Advanced information systems capabilities are essential to conducting NASA's scientific research mission. Access to these capabilities is no longer a luxury for a select few within the science community, but rather an absolute necessity for carrying out scientific investigations. The dependence on high performance computing and networking, as well as ready and expedient access to science data, metadata, and analysis tools is the fundamental underpinning for the entire research endeavor. At the same time, advances in the whole range of information technologies continues on an almost explosive growth path, reaching beyond the research community to affect the population as a whole. Capitalizing on and exploiting these advances are critical to the continued success of space science investigations. NASA must remain abreast of developments in the field and strike an appropriate balance between being a smart buyer and a direct investor in the technology which serves its unique requirements. Another key theme deals with the need for the space and computer science communities to collaborate as partners to more fully realize the potential of information technology in the space science research environment.

Bredekamp, Joseph H.↗
NASA NTRS2014

Challenges in Evaluating Relationships Between Quantitative Data (Carbon Dioxide) and Qualitative Data (Self-Reported Visual Changes)

Understanding the nuances in clinical data is critical in developing a successful data analysis plan. Carbon dioxide (CO2) data are collected on board the International Space Station (ISS) in a continuous stream. Clinical data on ISS are primarily collected via conversations between individual crewmembers and NASA Flight Surgeons during weekly Private Medical Conferences (PMC). Law, et.al, 20141 demonstrated a statistically significant association between weekly average CO2 levels on ISS and self-reported headaches over the reporting period from March 14, 2001 to May 31, 2012. The purpose of this analysis is to describe the evaluation of a possible association between visual changes and CO2 levels on ISS and to discuss challenges in developing an appropriate analysis plan. METHODS & PRELIMINARY RESULTS: A first analysis was conducted following the same study design as the published work on CO2 and self-reported headaches1; substituting self-reported changes in visual acuity in place of self-reported headaches. The analysis demonstrated no statistically significant association between visual impairment characterized by vision symptoms self-reported during PMCs and ISS average CO2 levels over ISS missions. Closer review of the PMC records showed that vision outcomes are not well-documented in terms of clinical severity, timing of onset, or timing of resolution, perhaps due to the incipient nature of vision changes. Vision has been monitored in ISS crewmembers, pre- and post-flight, using standard optometry evaluations. In-flight visual assessments were limited early in the ISS program, primarily consisting of self-perceived changes reported by crewmembers. Recently, on-orbit capabilities have greatly improved. Vision data ranges from self-reported post-flight changes in visual acuity, pre- to postflight changes identified during fundoscopic examination, and in-flight progression measured by advanced on-orbit clinical imaging capabilities at predetermined testing intervals. In contrast, CO2 data are recorded in a continuous stream over time; however, for the initial analysis this data was categorized into weekly averages.

Mendez, C. M.↗