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At least 253 records · Page 14

GTOSS: Generalized Tethered Object Simulation System

GTOSS represents a tether analysis complex which is described by addressing its family of modules. TOSS is a portable software subsystem specifically designed to be introduced into the environment of any existing vehicle dynamics simulation to add the capability of simulating multiple interacting objects (via multiple tethers). These objects may interact with each other as well as with the vehicle into whose environment TOSS is introduced. GTOSS is a stand alone tethered system analysis program, representing an example of TOSS having been married to a host simulation. RTOSS is the Results Data Base (RDB) subsystem designed to archive TOSS simulation results for future display processing. DTOSS is a display post processors designed to utilize the RDB. DTOSS extracts data from the RDB for multi-page printed time history displays. CTOSS is similar to DTOSS, but is designed to create ASCII plot files. The same time history data formats provided for DTOSS (for printing) are available via CTOSS for plotting. How these and other modules interact with each other is discussed.

Lang, David D.↗

Volume server: A scalable high speed and high capacity magnetic tape archive architecture with concurrent multi-host access

A major challenge facing data processing centers today is data management. This includes the storage of large volumes of data and access to it. Current media storage for large data volumes is typically off line and frequently off site in warehouses. Access to data archived in this fashion can be subject to long delays, errors in media selection and retrieval, and even loss of data through misplacement or damage to the media. Similarly, designers responsible for architecting systems capable of continuous high-speed recording of large volumes of digital data are faced with the challenge of identifying technologies and configurations that meet their requirements. Past approaches have tended to evaluate the combination of the fastest tape recorders with the highest capacity tape media and then to compromise technology selection as a consequence of cost. This paper discusses an architecture that addresses both of these challenges and proposes a cost effective solution based on robots, high speed helical scan tape drives, and large-capacity media.

Rybczynski, Fred↗

Vehicle Health Management Communications Requirements for AeroMACS

As the development of standards for the aeronautical mobile airport communications system (AeroMACS) progresses, the process of identifying and quantifying appropriate uses for the system is progressing. In addition to defining important elements of AeroMACS standards, indentifying the systems uses impacts AeroMACS bandwidth requirements. Although an initial 59 MHz spectrum allocation for AeroMACS was established in 2007, the allocation may be inadequate; studies have indicated that 100 MHz or more of spectrum may be required to support airport surface communications. Hence additional spectrum allocations have been proposed. Vehicle health management (VHM) systems, which can produce large volumes of vehicle health data, were not considered in the original bandwidth requirements analyses, and are therefore of interest in supporting proposals for additional AeroMACS spectrum. VHM systems are an emerging development in air vehicle safety, and preliminary estimates of the amount of data that will be produced and transmitted off an aircraft, both in flight and on the ground, have been prepared based on estimates of data produced by on-board vehicle health sensors and initial concepts of data processing approaches. This allowed an initial estimate of VHM data transmission requirements for the airport surface. More recently, vehicle-level systems designed to process and analyze VHM data and draw conclusions on the current state of vehicle health have been undergoing testing and evaluation. These systems make use of vehicle system data that is mostly different from VHM data considered previously for airport surface transmission, and produce processed system outputs that will be also need to be archived, thus generating additional data load for AeroMACS. This paper provides an analysis of airport surface data transmission requirements resulting from the vehicle level reasoning systems, within the context of overall VHM data requirements.

Kerczewski, Robert J.↗

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently, new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗

Grid Technology as a Cyber Infrastructure for Earth Science Applications

This paper describes how grids and grid service technologies can be used to develop an infrastructure for the Earth Science community. This cyberinfrastructure would be populated with a hierarchy of services, including discipline specific services such those needed by the Earth Science community as well as a set of core services that are needed by most applications. This core would include data-oriented services used for accessing and moving data as well as computer-oriented services used to broker access to resources and control the execution of tasks on the grid. The availability of such an Earth Science cyberinfrastructure would ease the development of Earth Science applications. With such a cyberinfrastructure, application work flows could be created to extract data from one or more of the Earth Science archives and then process it by passing it through various persistent services that are part of the persistent cyberinfrastructure, such as services to perform subsetting, reformatting, data mining and map projections.

Hinke, Thomas H.↗

Interpreting forest and grassland biome productivity utilizing nested scales of image resolution and biogeographical analysis

Data acquisition, initial site characterization, image and geographic information methods available, and brief evaluations of first-year for NASA's Thematic Mapper (TM) working group are presented. The TM and other spectral data are examined in order to relate local, intensive ecosystem research findings to estimates of carbon cycling rates over wide geographic regions. The effort is to span environments ranging from dry to moist climates and from good to poor site quality using the TM capability, with and without the inclusion of geographic information system (GIS) data, and thus to interpret the local spatial pattern of factors conditioning biomass or productivity. Twenty-eight TM data sets were acquired, archived, and evaluated. The ERDAS image processing and GIS system were installed on the microcomputer (PC-AT) and its capabilities are being investigated. The TM coverage of seven study areas were exported via ELAS software on the Prime to the ERDAS system. Statistical analysis procedures to be used on the spectral data are being identified.

Iverson, L. R.↗

Long-Lasting Science Returns from the Apollo Heat Flow Experiments

The Apollo astronauts deployed geothermal heat flow instruments at landing sites 15 and 17 as part of the Apollo Lunar Surface Experiments Packages (ALSEP) in July 1971 and December 1972, respectively. These instruments continuously transmitted data to the Earth until September 1977. Four decades later, the data from the two Apollo sites remain the only set of in-situ heat flow measurements obtained on an extra-terrestrial body. Researchers continue to extract additional knowledge from this dataset by utilizing new analytical techniques and by synthesizing it with data from more recent lunar orbital missions such as the Lunar Reconnaissance Orbiter. In addition, lessons learned from the Apollo experiments help contemporary researchers in designing heat flow instruments for future missions to the Moon and other planetary bodies. For example, the data from both Apollo sites showed gradual warming trends in the subsurface from 1971 to 1977. The cause of this warming has been debated in recent years. It may have resulted from fluctuation in insolation associated with the 18.6-year-cycle precession of the Moon, or sudden changes in surface thermal environment/properties resulting from the installation of the instruments and the astronauts' activities. These types of reanalyses of the Apollo data have lead a panel of scientists to recommend that a heat flow probe carried on a future lunar mission reach 3 m into the subsurface, approx 0.6 m deeper than the depths reached by the Apollo 17 experiment. This presentation describes the authors current efforts for (1) restoring a part of the Apollo heat flow data that were left unprocessed by the original investigators and (2) designing a compact heat flow instrument for future robotic missions to the Moon. First, at the conclusion of the ALSEP program in 1977, heat flow data obtained at the two Apollo sites after December 1974 were left unprocessed and not properly archived through NASA. In the following decades, heat flow data from January 1975 through February 1976, as well as the metadata necessary for processing the data (the data reduction algorithm, instrument calibration data, etc.), were somehow lost. In 2010, we located 450 original master archival tapes of unprocessed data from all the ALSEP instruments for a period of April through June 1975 at the Washington National Records Center. We are currently extracting the heat flow data packets from these tapes and processing them. Second, on future lunar missions, heat flow probes will likely be deployed by a network of small robotic landers, as recommended by the latest Decadal Survey of the National Academy of Science. In such a scenario, the heat flow probe must be a compact system, and that precludes use of heavy excavation equipment such as a rotary drill for reaching the 3-m target depth. The new heat flow system under development uses a pneumatically driven penetrator. It utilizes a stem that winds out of a reel and pushes its conical tip into the regolith. Simultaneously, gas jets, emitted from the cone tip, loosen and blow away the soil. Lab experiments have demonstrated its effectiveness in lunar vacuum.

Nagihara, S.↗

Using Selection Pressure as an Asset to Develop Reusable, Adaptable Software Systems

The Goddard Earth Sciences Data and Information Services Center (GES DISC) at NASA has over the years developed and honed several reusable architectural components for supporting large-scale data centers with a large customer base. These include a processing system (S4PM) and an archive system (S4PA) based upon a workflow engine called the Simple Scalable Script based Science Processor (S4P) and an online data visualization and analysis system (Giovanni). These subsystems are currently reused internally in a variety of combinations to implement customized data management on behalf of instrument science teams and other science investigators. Some of these subsystems (S4P and S4PM) have also been reused by other data centers for operational science processing. Our experience has been that development and utilization of robust interoperable and reusable software systems can actually flourish in environments defined by heterogeneous commodity hardware systems the emphasis on value-added customer service and the continual goal for achieving higher cost efficiencies. The repeated internal reuse that is fostered by such an environment encourages and even forces changes to the software that make it more reusable and adaptable. Allowing and even encouraging such selective pressures to software development has been a key factor In the success of S4P and S4PM which are now available to the open source community under the NASA Open source Agreement

Berrick, Stephen↗

The Role of Advanced Information System Technology in Remote Sensing for NASA's Earth Science Enterprise in the 21st Century

Future NASA Earth observing satellites will carry high-precision instruments capable of producing large amounts of scientific data. The strategy will be to network these instrument-laden satellites into a web-like array of sensors to facilitate the collection, processing, transmission, storage, and distribution of data and data products - the essential elements of what we refer to as "Information Technology." Many of these Information Technologies will enable the satellite and ground information systems to function effectively in real-time, providing scientists with the capability of customizing data collection activities on a satellite or group of satellites directly from the ground. In future systems, extremely large quantities of data collected by scientific instruments will require the fastest processors, the highest communication channel transfer rates, and the largest data storage capacity to insure that data flows smoothly from the satellite-based instrument to the ground-based archive. Autonomous systems will control all essential processes and play a key role in coordinating the data flow through space-based communication networks. In this paper, we will discuss those critical information technologies for Earth observing satellites that will support the next generation of space-based scientific measurements of planet Earth, and insure that data and data products provided by these systems will be accessible to scientists and the user community in general.

Prescott, Glenn↗

TRMM .25 deg x .25 deg Gridded Precipitation Text Product

Since the launch of the Tropical Rainfall Measuring Mission (TRMM), the Precipitation Measurement Missions science team has endeavored to provide TRMM precipitation retrievals in a variety of formats that are more easily usable by the broad science community than the standard Hierarchical Data Format (HDF) in which TRMM data is produced and archived. At the request of users, the Precipitation Processing System (PPS) has developed a .25 x .25 gridded product in an easily used ASCII text format. The entire TRMM mission data has been made available in this format. The paper provides the details of this new precipitation product that is designated with the TRMM designator 3G68.25. The format is packaged into daily files. It provides hourly precipitation information from the TRMM microwave imager (TMI), precipitation radar (PR), and TMI/PR combined rain retrievals. A major advantage of this approach is the inclusion only of rain data, compression when a particular grid has no rain from the PR or combined, and its direct ASCII text format. For those interested only in rain retrievals and whether rain is convection or stratiform, these products provide a huge reduction in the data volume inherent in the standard TRMM products. This paper provides examples of the 3G68 data products and their uses. It also provides information about C tools that can be used to aggregate daily files into larger time samples. In addition, it describes the possibilities inherent in the spatial sampling which allows resampling into coarser spatial sampling. The paper concludes with information about downloading the gridded text data products.

Stocker, Erich↗

UIT support observations archive

We are in the process of archiving the approximately 1.2Tbytes of imaging data acquired in support of UIT observations. The UIT is one of three telescopes comprising the ASTRO spacecraft and is a 38-cm f/9 Ritchey-Chretien telescope with wavelength coverage 1200 A to 3000 A and a 40 arcminute diameter field-of-view at 4 min FWHM resolution. During the ASTRO shuttle mission, there were 65 different pointings (some with multiple targets) of the UIT and hence 65 fields. Our support data of these fields were obtained with the KPNO and CTIO 0.9m telescopes and several of the 2048x2048 CCD's. Our images are typically about 20 acrminutes on a side and contain the entire UV target except for nearby galaxies, for which mosaiced images were created. All good quality images in the broadband and narrow band filters for every target are being archived. Though all of the UIT targets were well studied astronomical objects, these frames are many of the first large field format images of them and, when combined with the soon to be released UV frames, provide a unique dataset. These data were already used to address a wide variety of astronomical questions. Vacuum ultraviolet (VUV) observations were used to study star formation in a sample of nearby galaxies, since integrated VUV - optical colors provide the most sensitive available measure of the formation rate of massive stars. The blue stages later in stellar evolution are also being studied. These data allow more accurate determination of the helium and metallicities of hothorzontal branch stars. These data are being prepared to release to the public in CD-ROM format through the National Space Science Data Center.

Smith, Eric P.↗

Ozone determinations with the NOAA SBUV/2 system

The NOAA satellite ozone monitoring program was initiated by the National Environmental Satellite Data and Information Service (NESDIS) in December 1984, with the launch of the NOAA-9 spacecraft carrying the first operational Solar Backscatter Ultraviolet Spectrometer (SBUV/2). This instrument and its successor on NOAA-11, launched in 1988, are similar to the SBUV instrument launched by the NASA in 1978 on the Nimbus-7 research spacecraft. Measurements by the SBUV and SBUV/2 instruments overlap beginning in 1985. These instruments use measurements of the reflected ultraviolet solar radiation from the atmosphere to derive total ozone amounts and ozone vertical profiles. Since launch, the NOAA instruments and the derived products have been undergoing extensive evaluation by scientists of NOAA and NASA. Measurements obtained with these instruments are processed in real time by the NESDIS. These are reprocessed as the SBUV/2 instrument characterization is refined and as the retrieval algorithm for processing the data is improved. The NOAA-9 ozone data archive begins in March 1985 and continues through October 1990. The archive of NOAA-11 data begins in January 1989 and the data continues to be acquired in 1992.

Planet, Walter G.↗

Development and analysis of SCR requirements tables for system scenarios

We describe the use of scenarios to develop and refine requirement tables for parts of the Earth Observing System Data and Information System (EOSDIS). The National Aeronautics and Space Administration (NASA) is developing EOSDIS as part of its Mission-To-Planet-Earth (MTPE) project to accept instrument/platform observation requests from end-user scientists, schedule and perform requested observations of the Earth from space, collect and process the observed data, and distribute data to scientists and archives. Current requirements for the system are managed with tools that allow developers to trace the relationships between requirements and other development artifacts, including other requirements. In addition, the user community (e.g., earth and atmospheric scientists), in conjunction with NASA, has generated scenarios describing the actions of EOSDIS subsystems in response to user requests and other system activities. As part of a research effort in verification and validation techniques, this paper describes our efforts to develop requirements tables from these scenarios for the EOSDIS Core System (ECS). The tables specify event-driven mode transitions based on techniques developed by the Naval Research Lab's (NRL) Software Cost Reduction (SCR) project. The SCR approach has proven effective in specifying requirements for large systems in an unambiguous, terse format that enhance identification of incomplete and inconsistent requirements. We describe development of SCR tables from user scenarios and identify the strengths and weaknesses of our approach in contrast to the requirements tracing approach. We also evaluate the capabilities of both approach to respond to the volatility of requirements in large, complex systems.

Callahan, John R.↗

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Goodman, M.↗

The Sensor Management for Applied Research Technologies (SMART) Project

NASA seeks on-demand data processing and analysis of Earth science observations to facilitate timely decision-making that can lead to the realization of the practical benefits of satellite instruments, airborne and surface remote sensing systems. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep "learning curve" associated with each sensor, data type, and associated products. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output.

Goodman, Michael↗

Transforming Science Data for GIS: How to Find and Use NASA Earth Observation Data Without Being a Rocket Scientist

NASAs Earth Observing System Data Information System (EOSDIS) manages Earth Observation satellites and the Distributed Active Archive Centers (DAACs), where the data is stored and processed. The challenge is that Earth Observation data is complicated. There is plenty of data available, however, the science teams have had a top-down approach: define what it is you are trying to study -select a set of satellite(s) and sensor(s), and drill down for the data.Our alternative is to take a bottom-up approach using eight environmental fields of interest as defined by the Group on Earth Observations (GEO) called Societal Benefit Areas (SBAs): Disaster Resilience (DR) Public Health Surveillance (PHS) Energy and Mineral Resource Management (EMRM) Water Resources Management (WRM) Infrastructure and Transport Management (ITM) Sustainable Urban Development (SUD) Food Security and Sustainable Agriculture (FSSA) Biodiversity and Ecosystems Sustainability (BES).

DAAC↗

Flood Analysis of the Thomas Flood in California Using NASA Data in a GIS

In December 2017, the Thomas Fire burned areas in Ventura and Santa Barbara Counties in California, consuming 281,893 acres (440 square miles), and becoming the largest wildfire in California history. On January 8, 2018, a winter storm made landfall in Santa Barbara County, releasing more than 5 inches of rain onto the same scarred area, causing San Ysidro and Montecito Creeks to overflow and leading to devastating flash flooding and debris flows by January 9, 2018. Several areas that were not typically prone to flooding were at risk due to the higher than usual flows in the nearby streams and creeks. The unprecedented flooding killed at least 20 people and left several others missing. NASA's Earth Observing System Data Information System (EOSDIS) manages Earth Observation satellites and the Distributed Active Archive Centers (DAACs), where the data is stored and processed. This poster presents the use of satellite data from NASA's inventory that have the potential for use in identification and analysis of forest fire risk and subsequent after-effects within a geographic information system (GIS).

science↗