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At least 469 records · Page 26

NASA Earth Sciences Data Support System and Services for the Northern Eurasia Earth Science Partnership Initiative

The presentation describes the recently awarded ACCESS project to provide data management of NASA remote sensing data for the Northern Eurasia Earth Science Partnership Initiative (NEESPI). The project targets integration of remote sensing data from MODIS, and other NASA instruments on board US-satellites (with potential expansion to data from non-US satellites), customized data products from climatology data sets (e.g., ISCCP, ISLSCP) and model data (e.g., NCEP/NCAR) into a single, well-architected data management system. It will utilize two existing components developed by the Goddard Earth Sciences Data & Information Services Center (GES DISC) at the NASA Goddard Space Flight Center: (1) online archiving and distribution system, that allows collection, processing and ingest of data from various sources into the online archive, and (2) user-friendly intelligent web-based online visualization and analysis system, also known as Giovanni. The former includes various kinds of data preparation for seamless interoperability between measurements by different instruments. The latter provides convenient access to various geophysical parameters measured in the Northern Eurasia region without any need to learn complicated remote sensing data formats, or retrieve and process large volumes of NASA data. Initial implementation of this data management system will concentrate on atmospheric data and surface data aggregated to coarse resolution to support collaborative environment and climate change studies and modeling, while at later stages, data from NASA and non-NASA satellites at higher resolution will be integrated into the system.

Leptoukh, Gregory↗

Earth Science Informatics Comes of Age

The volume and complexity of Earth science data have steadily increased, placing ever-greater demands on researchers, software developers and data managers tasked with handling such data. Additional demands arise from requirements being levied by funding agencies and governments to better manage, preserve and provide open access to data. Fortunately, over the past 10-15 years significant advances in information technology, such as increased processing power, advanced programming languages, more sophisticated and practical standards, and near-ubiquitous internet access have made the jobs of those acquiring, processing, distributing and archiving data easier. These advances have also led to an increasing number of individuals entering the field of informatics as it applies to Geoscience and Remote Sensing. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of data, information, and knowledge. Informatics also encompasses the use of computers and computational methods to support decisionmaking and other applications for societal benefits.

Jodha, Siri↗

Discrepancy Reporting Management System

Discrepancy Reporting Management System (DRMS) is a computer program designed for use in the stations of NASA's Deep Space Network (DSN) to help establish the operational history of equipment items; acquire data on the quality of service provided to DSN customers; enable measurement of service performance; provide early insight into the need to improve processes, procedures, and interfaces; and enable the tracing of a data outage to a change in software or hardware. DRMS is a Web-based software system designed to include a distributed database and replication feature to achieve location-specific autonomy while maintaining a consistent high quality of data. DRMS incorporates commercial Web and database software. DRMS collects, processes, replicates, communicates, and manages information on spacecraft data discrepancies, equipment resets, and physical equipment status, and maintains an internal station log. All discrepancy reports (DRs), Master discrepancy reports (MDRs), and Reset data are replicated to a master server at NASA's Jet Propulsion Laboratory; Master DR data are replicated to all the DSN sites; and Station Logs are internal to each of the DSN sites and are not replicated. Data are validated according to several logical mathematical criteria. Queries can be performed on any combination of data.

Cooper, Tonja M.↗

Avionics test bed development plan

The plan is for a facility for the early investigation and evaluation of new concepts for the control of large space structures, orbiter attached flex body experiments, and orbiter enhancements. This plan outlines a distributed data processing facility that will utilize the current JSC laboratory resources for the test bed development. The future studies required for implementation, the management system for project control, and the baseline system configuration are described.

Harris, L. H.↗

NEP power subsystem modeling

The Nuclear Electric Propulsion (NEP) system optimization code consists of a master module and various submodules. Each of the submodules represents a subsystem within the total NEP power system. The master module sends commands and input data to each of the submodules and receives output data back. Rocketdyne was responsible for preparing submodules for the power conversion (both K-Rankine and Brayton), heat rejection, and power management and distribution.

Harty, Richard B.↗

Performance evaluation of the NASA/KSC CAD/CAE and office automation LAN's

This study's objective is the performance evaluation of the existing CAD/CAE (Computer Aided Design/Computer Aided Engineering) network at NASA/KSC. This evaluation also includes a similar study of the Office Automation network, since it is being planned to integrate this network into the CAD/CAE network. The Microsoft mail facility which is presently on the CAD/CAE network was monitored to determine its present usage. This performance evaluation of the various networks will aid the NASA/KSC network managers in planning for the integration of future workload requirements into the CAD/CAE network and determining the effectiveness of the planned FDDI (Fiber Distributed Data Interface) migration.

Zobrist, George W.↗

Recent Project Experience Mars Reconnaissance Orbiter (MRO)

This viewgraph presentation reviews the experiences of the Mars Reconnaissance Orbiter (MRO). It includes an overview of the MRO mission; the challenges of data Management and Transport; a representation of the end-to-end flow for the telemetry data; a review of the data issues, and Coherent File Distribution Protocol (CFDP) uses and issues.

Mars Exploration Rover (MER)↗

Land Processes Distributed Active Archive Center (LP DAAC) 25th Anniversary Recognition "A Model for Government Partnerships". LP DAAC "History and a Look Forward"

This presentation discusses 25 years of interactions between NASA and the USGS to manage a Land Processes Distributed Active Archive Center (LPDAAC) for the purpose of providing users access to NASA's rich collection of Earth Science data. The presentation addresses challenges, efforts and metrics on the performance.

Land Remote Sensing↗

A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

big data↗

Application of LANDSAT to the management of Delaware's marine and wetland resources

The author has identified the following significant results. LANDSAT data were found to be the best source of synoptic information on the distribution of horizontal water mass discontinuities (fronts) at different portions of the tidal cycle. Distributions observed were used to improve an oil slick movement prediction model for the Delaware Bay. LANDSAT data were used to monitor the movement and dispersion of industrial acid waste material dumped over the continental shelf. A technique for assessing aqueous sediment concentration with limited ground truth was proposed.

Klemas, V.↗

NASA's Earth Science Flight Program Meets the Challenges of Today and Tomorrow

NASA's Earth science flight program is a dynamic undertaking that consists of a large fleet of operating satellites, an array of satellite and instrument projects in various stages of development, a robust airborne science program, and a massive data archiving and distribution system. Each element of the flight program is complex and present unique challenges. NASA builds upon its successes and learns from its setbacks to manage this evolving portfolio to meet NASA's Earth science objectives. NASA fleet of 16 operating missions provide a wide range of scientific measurements made from dedicated Earth science satellites and from instruments mounted to the International Space Station. For operational missions, the program must address issues such as an aging satellites operating well beyond their prime mission, constellation flying, and collision avoidance with other spacecraft and orbital debris. Projects in development are divided into two broad categories: systematic missions and pathfinders. The Earth Systematic Missions (ESM) include a broad range of multi-disciplinary Earth-observing research satellite missions aimed at understanding the Earth system and its response to natural and human-induced forces and changes. Understanding these forces will help determine how to predict future changes, and how to mitigate or adapt to these changes. The Earth System Science Pathfinder (ESSP) program provides frequent, regular, competitively selected Earth science research opportunities that accommodate new and emerging scientific priorities and measurement capabilities. This results in a series of relatively low-cost, small-sized investigations and missions. Principal investigators whose scientific objectives support a variety of studies lead these missions, including studies of the atmosphere, oceans, land surface, polar ice regions, or solid Earth. This portfolio of missions and investigations provides opportunity for investment in innovative Earth science that enhances NASA's capability for better understanding the current state of the Earth system. ESM and ESSP projects often involve partnerships with other US agencies and/or international organizations. This adds to the complexity of mission development, but allows for a greater scientific return on NASA's investments. The Earth Science Airborne Science Program provides manned and unmanned aircraft systems that further science and advance the use of satellite data. NASA uses these assets worldwide in campaigns to investigate extreme weather events, observe Earth system processes, obtain data for Earth science modeling activities, and calibrate instruments flying aboard Earth science spacecraft. The Airborne Science Program has six dedicated aircraft and access to many other platforms. The Earth Science Multi-Mission Operations program acquires, preserves, and distributes observational data from operating spacecraft to support Earth Science research focus areas. The Earth Observing System Data and Information System (EOSDIS), which has been in operations since 1994, primarily accomplishes this. EOSDIS acquires, processes, archives, and distributes Earth Science data and information products. The archiving of NASA Earth Science information happens at eight Distributed Active Archive Centers (DAACs) and four disciplinary data centers located across the United States. The DAACs specialize by topic area, and make their data available to researchers around the world. The DAACs currently house over 9 petabytes of data, growing at a rate of 6.4 terabytes per day. NASA's current Earth Science portfolio is responsive to the National Research Council (NRC) 2007 Earth Science Decadal Survey and well as the 2010 NASA Response to President Obama's Climate Plan. As the program evolves into the future it will leverage the lessons learned from the current missions in operations and development, and plan for adjustments to future objectives in response to the anticipated 2017 NRC Decadal Survey.

Flight Program↗

An optical disk archive for a data base management system

An overview is given of a data base management system that can catalog and archive data at rates up to 50M bits/sec. Emphasis is on the laser disk system that is used for the archive. All key components in the system (3 Vax 11/780s, a SEL 32/2750, a high speed communication interface, and the optical disk) are interfaced to a 100M bits/sec 16-port fiber optic bus to achieve the high data rates. The basic data unit is an autonomous data packet. Each packet contains a primary and secondary header and can be up to a million bits in length. The data packets are recorded on the optical disk at the same time the packet headers are being used by the relational data base management software ORACLE to create a directory independent of the packet recording process. The user then interfaces to the VAX that contains the directory for a quick-look scan or retrieval of the packet(s). The total system functions are distributed between the VAX and the SEL. The optical disk unit records the data with an argon laser at 100M bits/sec from its buffer, which is interfaced to the fiber optic bus. The same laser is used in the read cycle by reducing the laser power. Additional information is given in the form of outlines, charts, and diagrams.

Thomas, Douglas T.↗

UTM Data Working Group Demonstration 1: Final Report

This document summarizes activities defining and executing the first demonstration of the NASA-FAA Research Transition Team (RTT) Data Exchange and Information Architecture (DEIA) working group (DWG). The demonstration focused on testing the interactions between two key components in the future UAS Traffic Management (UTM) System through a collaborative and distributed simulation of key scenarios. The summary incorporates written feedback from each of the participants in the demonstration. In addition to reporting the activities, this report also provides some insight into future steps of this working group.

UAS Traffic Management↗

Intelligent Sensors: An Integrated Systems Approach

The need for intelligent sensors as a critical component for Integrated System Health Management (ISHM) is fairly well recognized by now. Even the definition of what constitutes an intelligent sensor (or smart sensor) is well documented and stems from an intuitive desire to get the best quality measurement data that forms the basis of any complex health monitoring and/or management system. If the sensors, i.e. the elements closest to the measurand, are unreliable then the whole system works with a tremendous handicap. Hence, there has always been a desire to distribute intelligence down to the sensor level, and give it the ability to assess its own health thereby improving the confidence in the quality of the data at all times. This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines some fundamental issues in the development of intelligent sensors under the following two categories: Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS).

Mahajan, Ajay↗

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

Figueroa, Fernando↗

Utilization of ERTS-1 for appraising changes in continental migratory bird habitat

The author has identified the following significant results. Information on numbers, distribution, and quality of wetlands in the breeding range of migratory waterfowl is important for the management of this wildlife resource. Using computer processing of data gathered by the ERTS-1 multispectral scanner, techniques for obtaining indices of annual waterfowl recruitment, and habitat quality are examined. As a primary task, thematic maps and statistics relating to open surface water were produced. Discrimination of water was based upon water's low apparent radiance in a single, near-infrared waveband. An advanced technique using multispectral information for discerning open water at a level of detail finer than the virtual resolution of the data was also successfully tested. In another related task, vegetation indicators were used for detecting conditions of latent or occluded water and upland habitat characteristics.

Gilmer, D. S.↗

Application Of Artificial Intelligence To Wind Tunnels

Report discusses potential use of artificial-intelligence systems to manage wind-tunnel test facilities at Ames Research Center. One of goals of program to obtain experimental data of better quality and otherwise generally increase productivity of facilities. Another goal to increase efficiency and expertise of current personnel and to retain expertise of former personnel. Third goal to increase effectiveness of management through more efficient use of accumulated data. System used to improve schedules of operation and maintenance of tunnels and other equipment, assignment of personnel, distribution of electrical power, and analysis of costs and productivity. Several commercial artificial-intelligence computer programs discussed as possible candidates for use.

Lo, Ching F.↗

Technologies for Networked Enabled Operations

Current point-to-point data links will not scale to support future integration of surveillance, security, and globally-distributed air traffic data, and already hinders efficiency and capacity. While the FAA and industry focus on a transition to initial system-wide information management (SWIM) capabilities, this paper describes a set of initial studies of NAS network-enabled operations technology gaps targeted for maturity in later SWIM spirals (201 5-2020 timeframe).

Glass, B.↗