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At least 847 records · Page 47

Reusing Information Management Services for Recommended Decadal Study Missions to Facilitate Aerosol and Cloud Studies

NASA Earth Sciences Division (ESD) has made great investments in the development and maintenance of data management systems and information technologies, to maximize the use of NASA generated Earth science data. With information management system infrastructure in place, mature and operational, very small delta costs are required to fully support data archival, processing, and data support services required by the recommended Decadal Study missions. This presentation describes the services and capabilities of the Goddard Space Flight Center (GSFC) Earth Sciences Data and Information Services Center (GES DISC) and the reusability for these future missions. The GES DISC has developed a series of modular, reusable data management components currently in use. They include data archive and distribution (Simple, Scalable, Script-based, Science [S4] Product Archive aka S4PA), data processing (S4 Processor for Measurements aka S4PM), data search (Mirador), data browse, visualization, and analysis (Giovanni), and data mining services. Information management system components are based on atmospheric scientist inputs. Large development and maintenance cost savings can be realized through their reuse in future missions.

Kempler, Steve↗

Preparations for Integrating Space-Based Total Lightning Observations into Forecast Operations

NASA's Short-term Prediction Research and Transition (SPoRT) Center has been a leader in collaborating with the United States National Weather Service (NWS) offices to integrate ground-based total lightning (intra-cloud and cloud-to-ground) observations into the real-time operational environment. For much of these collaborations, the emphasis has been on training, dissemination of data to the NWS AWIPS system, and focusing on the utility of these data in the warning decision support process. A shift away from this paradigm has occurred more recently for several reasons. For one, SPoRT's collaborations have expanded to new partners, including emergency managers and the aviation community. Additionally, and most importantly, is the impending launch of the GOES-R Geostationary Lightning Mapper (GLM). This has led to collaborative efforts to focus on additional forecast needs, new data displays, develop training for GLM uses based on the lessons learned from ground-based lightning mapping arrays, and ways to better relate total lightning data to other meteorological parameters. This presentation will focus on these efforts to prepare the operational end user community for GLM with an eye towards sharing lessons learned as EUMETSAT prepares for the Meteosat Third Generation Lightning Imager. This will focus on both software and training needs. In particular, SPoRT has worked closely with the Meteorological Development Laboratory to create the total lightning tracking tool. This software allows for NWS forecasters to manually track storms of interest and display a time series trend of observations. This tool also has been expanded to work on any gridded data set allowing for easy visual comparisons of multiple parameters in addition to total lightning. A new web display has been developed for the ground-based observations that can be easily extended to satellite observations. This paves the way for new collaborations outside of the NWS, both domestically and internationally, as the web display will be functional on PCs and mobile devices. Furthermore, SPoRT has helped developed the software plug-in to visualize GLM data. Examples using the official GLM proxy product will be used to provide a glimpse as to what real-time GLM and likely MTG-LI data will be in the near future.

GLM↗

NASA GIBS and Worldview: Visualizing NASA's Earth Science Data for All to Explore

For more than 20 years, the NASA Earth Observing System (EOS) has operated dozens of remote sensing satellites collecting nearly 15 Petabytes of data that span thousands of science parameters. Within these observations are keys the Earth Scientists have used to unlock many discoveries that we now understand about our planet. Also contained within these observations are a myriad of opportunities for learning and education. The challenge is making them accessible to educators and students in intuitive and simple ways so that effort can be spent on lesson enrichment and not overcoming technical hurdles. The NASA Global Imagery Browse Services (GIBS) system and NASA Worldview website provide a unique view into EOS data through daily full resolution visualizations of hundreds of earth science parameters. For many of these parameters, visualizations are available within hours of acquisition from the satellite. For others, visualizations are available for the entire mission of the satellite. Accompanying the visualizations are visual aids such as color legends, place names, and orbit tracks. By using these visualizations, educators and students can observe natural phenomena that enrich a scientific education.

Cechini, Matthew↗

Satellite and Reanalysis Air Quality Data and Services at NASA GES DISC for Public Health Study

Outbreaks of infectious diseases and health can be influenced by airborne and water-borne pollutants. Furthermore, air and water quality are associated with climate variability, industrialization, land use and land cover change, and water resource management. It is therefore crucial to understand environment-disease connections with existing long-term observed and modeled data, particularly for development of early warning systems for infectious disease outbreaks. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) (https://disc.gsfc.nasa.gov) archives large volumes of global environment data that are useful for research and applications regarding environmental factors and public health. Examples of air quality measurements are: Daily satellite remotely sensed data, including Aerosol Index (AI), O3, SO2, CO, and NO2 from Aura/OMI (October 2014 to present), and OMPS-NPP (January 2012 to present, currently research data products only) Hourly and monthly reanalysis modeled data, including PM2.5, O3, CO, SO2, BC, dust, AOD, and aerosol types from MERRA-2 (January 1980 to present) Examples of surface meteorology and land surface measurements are: hourly, daily, and monthly satellite precipitation from TRMM (December 1997 to March 2015) 30-minute and monthly satellite precipitation from GPM (March 2014 to present); Hourly and monthly modeled surface meteorology and land surface condition from MERRA-2 (January 1980 to present) and land surface assimilation models (January 1948 to present), including precipitation, surface temperature, relative humidity, wind, and soil moisture.This presentation will give an overview of relevant environmental data at the NASA GES DISC. Through a number of use cases, such as dust events and active fires, we will introduce data services that assist in finding the right data, enable visualization and analysis of the data online, and allow downloading of data in user-preferred format.

remote sensing data↗

NASA GIBS and Worldview: Visualizing NASA's Earth Science Data for All to Explore

For more than 20 years, the NASA Earth Observing System (EOS) has operated dozens of remote sensing satellites collecting nearly 15 Petabytes of data that span thousands of science parameters. Within these observations are keys the Earth Scientists have used to unlock many discoveries that we now understand about our planet. Also contained within these observations are a myriad of opportunities for learning and education. The challenge is making them accessible to educators and students in intuitive and simple ways so that effort can be spent on lesson enrichment and not overcoming technical hurdles.The NASA Global Imagery Browse Services (GIBS) system and NASA Worldview interactive mapping site provide a unique view into EOS data through daily full resolution visualizations of hundreds of Earth science parameters. For many of these parameters, visualizations are available within hours of acquisition from the satellite. For others, visualizations are available for the entire mission of the satellite. Accompanying the visualizations are visual aids such as color legends, place names, and orbit tracks. By using these visualizations, educators and students can observe natural phenomena that enrich a scientific education.This presentation will provide an overview of the visualizations available in NASA GIBS and Worldview and how they are accessed. Specific attention will be given to the newer capabilities and accomplishments, including: Support for geostationary sub-daily visualizations, Enhanced support for vector-based visualizations, Improved Worldview tour and snapshot capabilities, New imagery products across a growing set of scientific areas.

Cechini, Matthew↗

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists.

Brugel, Edward W.↗

Visualization and Analysis of Data from Small-Body Missions with NASA's Solar System Treks Portals

The portals of NASA's Solar System Trek Project (SSTP) provide web-based suites of interactive visualization and analysis tools enabling mission planners, planetary scientists, students, and the general public to explore planetary surfaces as seen through the eyes of many different instruments aboard a wide range of spacecraft. The portals present a vast collection of mapped data products from past and current missions for a growing number of planetary bodies. As web-based toolsets, the portals do not require users to purchase or install any software beyond current web browsers. They feature a common user interface and are available through a single integrated website at https://trek.nasa.gov. This presentation will highlight 4 portals focusing on small bodies. We will provide an overview of established portals for (1) Ceres and (4) Vesta, and present the early capabilities for new portals being introduced for (162173) Ryugu and (101955) Bennu.

Day, Brian↗

Improving Data Discovery, Analysis, and Visualizations With Cloud-Based User Services

The Global Hydrometeorology Resource Center (GHRC) Distributed Active Archive Center (DAAC) is one of 12 DAACs managed by the United States National Aeronautics and Space Administration (NASA) Earth Science Data and Information System (ESDIS) project [1]. GHRC and the other DAACs are designed to process, archive, document, and distribute NASA Earth-observing data, ranging from satellite missions to field campaigns [2]. A major goal of the DAACs is to enable science with these data. Science enabling can be difficult as datasets can be very large, use multiple formats, come from numerous platforms, and require three-dimensional visualization. GHRC is using its expertise with cloud-based technologies to develop open source and open science tools to empower users to explore, coincidentally visualize, and analyze multiple datasets. Being open source, the user community can develop visualizations for their own datasets. This presentation will expand on this objective and highlight the capabilities available to the international community now.

GHRC↗

Visualization of three dimensional data

The objective of research is to characterize patterns of errors observers make when relating the judged exocentric direction of a target presented on a perspective display to their egocentric sense of visual direction. This type of spatial task is commonly faced by operators of telerobotic systems when using a map-like display of their workspace to determine the visual location and orientation of objects seen by direct view. It is also essentially the same task as faced by an aircraft pilot using a cockpit perspective traffic display of his surrounding airspace to locate traffic out his windows. The results of the current study clearly show that the visual direction is a significantly biased metric of virtual space presented by flat panel perspective displays. Modeling and explanation of the causes of the observed biases will allow design of compensated perspective displays.

Ellis, Stephen R.↗

Visualizing characteristics of ocean data collected during the Shuttle Imaging Radar-B experiment

Topographic measurements of sea surface elevation collected by the Surface Contour Radar (SCR) during NASA's Shuttle Imaging Radar (SIR-B) experiment are plotted as three dimensional surface plots to observe wave height variance along the track of a P-3 aircraft. Ocean wave spectra were computed from rotating altimeter measurements acquired by the Radar Ocean Wave Spectrometer (ROWS). Fourier power spectra computed from SIR-B synthetic aperture radar (SAR) images of the ocean are compared to ROWS surface wave spectra. Fourier inversion of SAR spectra, after subtraction of spectral noise and modeling of wave height modulation, yields topography similar to direct measurements made by SCR. Visual perspectives on the SCR and SAR ocean data are compared. Threshold distinctions between surface elevation and texture modulations of SAR data are considered within the context of a dynamic statistical model of rough surface scattering. The result of these endeavors is insight as to the physical mechanism governing the imaging of ocean waves with SAR.

Tilley, David G.↗

Integrating Ideas for International Data Collaborations Through The Committee on Earth Observation Satellites (CEOS) International Directory Network (IDN)

The capabilities of the International Directory Network's (IDN) version MD9.5, along with a new version of the metadata authoring tool, "docBUILDER", will be presented during the Technology and Services Subgroup session of the Working Group on Information Systems and Services (WGISS). Feedback provided through the international community has proven instrumental in positively influencing the direction of the IDN s development. The international community was instrumental in encouraging support for using the IS0 international character set that is now available through the directory. Supporting metadata descriptions in additional languages encourages extended use of the IDN. Temporal and spatial attributes often prove pivotal in the search for data. Prior to the new software release, the IDN s geospatial and temporal searches suffered from browser incompatibilities and often resulted in unreliable performance for users attempting to initiate a spatial search using a map based on aging Java applet technology. The IDN now offers an integrated Google map and date search that replaces that technology. In addition, one of the most defining characteristics in the search for data relates to the temporal and spatial resolution of the data. The ability to refine the search for data sets meeting defined resolution requirements is now possible. Data set authors are encouraged to indicate the precise resolution values for their data sets and subsequently bin these into one of the pre-selected resolution ranges. New metadata authoring tools have been well received. In response to requests for a standalone metadata authoring tool, a new shareable software package called "docBUILDER solo" will soon be released to the public. This tool permits researchers to document their data during experiments and observational periods in the field. interoperability has been enhanced through the use of the Open Archives Initiative s (OAI) Protocol for Metadata Harvesting (PMH). Harvesting of XML content through OAI-MPH has been successfully tested with several organizations. The protocol appears to be a prime candidate for sharing metadata throughout the international community. Data services for visualizing and analyzing data have become valuable assets in facilitating the use of data. Data providers are offering many of their data-related services through the directory. The IDN plans to develop a service-based architecture to further promote the use of web services. During the IDN Task Team session, ideas for further enhancements will be discussed.

Olsen, Lola M.↗

The Future of NASA Earth Science in the Commercial Cloud: Challenges and Opportunities

NASA produces a large volume and variety of data products that are used every day to support research, decision making, and education. The widespread use of NASA’s Earth Science data is enabled by NASA’s Earth Science Data System (ESDS) program, which oversees the archiving and distribution of these data and invests in the development of new data systems and tools. However, NASA’s current approach to Earth Science data distribution — based on distributed institutional archives with individual on-premises high-performance computing capabilities — faces some significant challenges, including massive increases in data volume from upcoming missions, a greater need for transdisciplinary science that synthesizes many different kinds of observations, and a push to make science more open, inclusive, and accessible. To address these challenges, NASA is aggressively migrating its Earth Science data and related tools and services into the commercial cloud. Migration of data into the commercial cloud can significantly improve NASA’s existing data system capabilities by (1) providing more flexible options for storage and compute (including rapid, as-needed access to state-of-the-art capabilities); (2) by centralizing and standardizing data access, which gives all of NASA’s institutional data centers access to all of each other’s datasets; and (3) by facilitating “analysis-in-place”, whereby users can bring their own computational workflows and tools to the data rather than having to maintain their own copies of NASA datasets. However, migration to the commercial cloud also poses some significant challenges, including (1) managing costs under a “pay-as-you-go” model; (2) incompatibility with existing tools and data formats with object-based storage and network access; (3) vendor lock-in; (4) challenges with data access for workflows that mix on-premise and cloud computing; and (5) standardization for highly diverse data as is present in NASA’s data archive. I conclude with two examples of recent NASA activities showcasing capabilities enabled by the commercial cloud: An interactive analysis and development platform for analyzing airborne imaging spectroscopy data, and a new collection of tools and services for data discovery, analysis, publication, and data-driven storytelling (Visualization, Exploration, and Data Analysis, VEDA).

Alexey N Shiklomanov↗

Visualization of Atmospheric Water Vapor Data for SAGE

The goal of this project was to develop visualization tools to study the water vapor dynamics using the Stratospheric Aerosol and Gas Experiment 11 (SAGE 11) water vapor data. During the past years, we completed the development of a visualization tool called EZSAGE, and various Gridded Water Vapor plots, tools deployed on the web to provide users with new insight into the water vapor dynamics. Results and experiences from this project, including papers, tutorials and reviews were published on the main Web page. Additional publishing effort has been initiated to package EZSAGE software for CD production and distribution. There have been some major personnel changes since Fall, 1998. Dr. Mou-Liang Kung, a Professor of Computer Science assumed the PI position vacated by Dr. Waldo Rodriguez who was on leave. However, former PI, Dr. Rodriguez continued to serve as a research adviser to this project to assure smooth transition and project completion. Typically in each semester, five student research assistants were hired and trained. Weekly group meetings were held to discuss problems, progress, new research direction, and activity planning. Other small group meetings were also held regularly for different objectives of this project. All student research assistants were required to submit reports for conference submission.

Kung, Mou-Liang↗

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

This report describes our project activities for the period Sep. 1991 - Oct. 1992. Our activities included stabilizing the software system STAR, porting STAR to IDL/widgets (improved user interface), targeting new visualization techniques for multi-dimensional data visualization (emphasizing 3D visualization), and exploring leading-edge 3D interface devices. During the past project year we emphasized high-end visualization techniques, by exploring new tools offered by state-of-the-art visualization software (such as AVS3 and IDL4/widgets), by experimenting with tools still under research at the Department of Computer Science (e.g., use of glyphs for multidimensional data visualization), and by researching current 3D input/output devices as they could be used to explore 3D astrophysical data. As always, any project activity is driven by the need to interpret astrophysical data more effectively.

Domik, Gitta↗

Multidisciplinary Analytics, Visualization, and Reporting Interface for Integrated Countermeasures

Exploration class missions will have communication latency requiring crew members to make decisions more autonomously, with less support from ground personnel. Therefore, new software is needed to provide crew the ability to not only visualize their countermeasures data, but to also derive comprehensive, nuanced, and multidisciplinary insights regarding the health and performance informatics throughout a mission. The Multidisciplinary Analytics, Visualization, and Reporting Interface for Integrated Countermeasures (MAVRIIC) software seeks to establish a centralized approach to countermeasure data visualization that will facilitate a more holistic understanding of crew members' well-being and performance and enable the development of informed and autonomous decision-making support systems aligned with the evolving requirements of Exploration missions. The culmination of MAVRIIC phase 1 (end of FY23) marked the release of a full-stack, cloud-based ground tool displaying visualizations of in-flight exercise data, exercise ground testing, and exercise MEDB reports. Phase 2 of MAVRIIC (FY24) focuses on beginning the expansion of data contents to domains outside of exercise, including functional fitness, sensorimotor, food/nutrition, radiation, bone, and cardio/vision. Phase 3 and phase 4 will comprise enhanced analytics integration and initiation of flight tool development for infusion into the Artemis Program and eventually the Mars Transit Habitat.

Kent Lawrence Kalogera↗

Visions of visualization aids - Design philosophy and observations

Aids for the visualization of high-dimensional scientific or other data must be designed. Simply casting multidimensional data into a two-dimensional or three-dimensional spatial metaphor does not guarantee that the presentation will provide insight or a parsimonious description of phenomena implicit in the data. Useful visualization, in contrast to glitzy, high-tech, computer-graphics imagery, is generally based on preexisting theoretical beliefs concerning the underlying phenomena. These beliefs guide selection and formatting of the plotted variables. Visualization tools are useful for understanding naturally three-dimensional data bases such as those used by pilots or astronauts. Two examples of such aids for spatial maneuvering illustrate that informative geometric distortion may be introduced to assist visualization and that visualization of complex dynamics alone may not be adequate to provide the necessary insight into the underlying processes.

Ellis, Stephen R.↗

Exploring and Visualizing A-Train Instrument Data

The succession of US and international satellites that follow each other in close succession, known as the A-Train, affords an opportunity to atmospheric researchers that no single platform could provide: Increasing the number of observations at any given geographic location.. . a more complete "virtual science platform". However, vertically and horizontally, co-registering and regridding datasets from independently developed missions, Aqua, Calipso, Cloudsat, Parasol, and Aura, so that they can be inter-compared can be daunting to some, and may be repeated by many. Scientists will individually spend much of their time and resources acquiring A-Train datasets of interest residing at various locations, developing algorithms to match up and graph datasets along the A-Train track, and search through large amounts of data for areas and/or phenomena of interest. The aggregate amount of effort that can be expended on repeating pre-science tasks could climb into the tens of millions of dollars. The goal of the A-Train Data Depot (ATDD) is to enable 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. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) is accomplished by through the ATDDs Giovanni data analysis and visualization tool. Giovanni brings together data from Aqua (MODIS, AIRS, AMSR-E), Cloudsat (cloud profiling radar) and Calipso (CALIOP, IIR), as well as the Aura (OMI, MLS, HIRDLS, TES) to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. This easy to learn and use exploration tool will allow users to create vertical profiles of any desired A-Train dataset, for any given time of choice. This presentation shows the power of Giovanni by describing and illustrating how this tool facilitates and aids A-Train science and research. A web based display system Giovanni provides users with the capability of creating co-located profile images of temperature and humidity data from the MODIS, MLS and AIRS instruments for a user specified time and spatial area. In addition, Cloud and Aerosol profiles may also be displayed for the Cloudsat and Caliop instruments. The ability to modify horizontal and vertical axis range, data range and dynamic color range is also provided. Two dimensional strip plots of MODIS, AIRS, OM1 and POLDER parameters, co-located along the Cloudsat reference track, can also be plotted along with the Cloudsat cloud profiling data. Center swath pixels for the same parameters can also be shown as line plots overlaying the Cloudsat or Calipso profile images. Images and subsetted data produced in each analysis run may be downloaded. Users truly can explore and discover data specific to their needs prior to ever transferring data to their analysis tools.

Kempler, S.↗