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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Optimal Reorganization of NASA Earth Science Data for Enhanced Accessibility and Usability for the Hydrology Community

A long-standing "Digital Divide" in data representation exists between the preferred way of data access by the hydrology community and the common way of data archival by earth science data centers. Typically, in hydrology, earth surface features are expressed as discrete spatial objects (e.g., watersheds), and time-varying data are contained in associated time series. Data in earth science archives, although stored as discrete values (of satellite swath pixels or geographical grids), represent continuous spatial fields, one file per time step. This Divide has been an obstacle, specifically, between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. and NASA earth science data systems. In essence, the way data are archived is conceptually orthogonal to the desired method of access. Our recent work has shown an optimal method of bridging the Divide, by enabling operational access to long-time series (e.g., 36 years of hourly data) of selected NASA datasets. These time series, which we have termed "data rods," are pre-generated or generated on-the-fly. This optimal solution was arrived at after extensive investigations of various approaches, including one based on "data curtains." The on-the-fly generation of data rods uses "data cubes," NASA Giovanni, and parallel processing. The optimal reorganization of NASA earth science data has significantly enhanced the access to and use of the data for the hydrology user community.

data rods↗
NASA NTRS2010

Data Access Services that Make Remote Sensing Data Easier to Use

This slide presentation reviews some of the processes that NASA uses to make the remote sensing data easy to use over the World Wide Web. This work involves much research into data formats, geolocation structures and quality indicators, often to be followed by coding a preprocessing program. Only then are the data usable within the analysis tool of choice. The Goddard Earth Sciences Data and Information Services Center is deploying a variety of data access services that are designed to dramatically shorten the time consumed in the data preparation step. On-the-fly conversion to the standard network Common Data Form (netCDF) format with Climate-Forecast (CF) conventions imposes a standard coordinate system framework that makes data instantly readable through several tools, such as the Integrated Data Viewer, Gridded Analysis and Display System, Panoply and Ferret. A similar benefit is achieved by serving data through the Open Source Project for a Network Data Access Protocol (OPeNDAP), which also provides subsetting. The Data Quality Screening Service goes a step further in filtering out data points based on quality control flags, based on science team recommendations or user-specified criteria. Further still is the Giovanni online analysis system which goes beyond handling formatting and quality to provide visualization and basic statistics of the data. This general approach of automating the preparation steps has the important added benefit of enabling use of the data by non-human users (i.e., computer programs), which often make sub-optimal use of the available data due to the need to hard-code data preparation on the client side.

Lynnes, Christopher↗
NASA NTRS2016

Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations

Cloud computing has the potential to bring high performance computing capabilities to the average science researcher. However, in order to take full advantage of cloud capabilities, the science data used in the analysis must often be reorganized. This typically involves sharding the data across multiple nodes to enable relatively fine-grained parallelism. This can be either via cloud-based file systems or cloud-enabled databases such as Cassandra, Rasdaman or SciDB. Since storing an extra copy of data leads to increased cost and data management complexity, NASA is interested in determining the benefits and costs of various cloud analytics methods for real Earth Observation cases. Accordingly, NASA's Earth Science Technology Office and Earth Science Data and Information Systems project have teamed with cloud analytics practitioners to run a benchmark comparison on cloud analytics methods using the same input data and analysis algorithms. We have particularly looked at analysis algorithms that work over long time series, because these are particularly intractable for many Earth Observation datasets which typically store data with one or just a few time steps per file. This post will present side-by-side cost and performance results for several common Earth observation analysis operations.

science data management↗
NASA NTRS2004

Swift Gamma-Ray Burst Explorer: Mission Design for Rapid, Accurate Location of Gamma-ray Bursts

The Swift Gamma-ray Burst Explorer is a NASA Mid-sized Explorer (MIDEX) with the primary mission of determining the origins of Gamma-Ray Bursts (GRBs). It will be the first mission to autonomously respond to newly-discovered GRBs and provide immediate follow-up narrow field instruments capable of multi-wavelength (UV, Optical, X-ray) observations. The characteristics of GRBs that are the key mission design drivers, are their non-repeating and brief duration bursts of multi-wavelength photons. In addition, rapid notification of the location and characteristics of the GRBs to ground-and-space- based observatories drive the end-to-end data analysis and distribution requirements. The Swift mission is managed by the GSFC, and includes an international team of contributors that each bring their unique perspective that have proven invaluable to the mission. The spacecraft bus, provided by Spectrum Astro, Inc. was procured through a Rapid Spacecraft Development Office (RSDO) contract by the GSFC. There are three instruments: the Burst Alert Telescope (BAT) provided by the GSFC; the X-Ray Telescope (XRT) provided by a team led by the Pennsylvania State University (PSU); and the Ultra-Violet Optical Telescope (UVOT), again managed by PSU. The Mission Operations Center (MOC) was developed by and is located at PSU. Science archiving and data analysis centers are located at the GSFC, in the UK and in Italy.

Bundas, David J.↗
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 NTRS2018

Hyperspectral Data Processing: an Opportunity for End-To-End Processing

The evolution and improvements in hyperspectral instrumentation are being matched by information technology improvements in science data processing and analysis. Research has improved techniques in both onboard and ground-based processing to support other high data volume instruments. Algorithms and hardware have evolved, permitting faster access to the observations. Cloud computing is taking the algorithms to the data. Technologies are being specifically designed to address high volume data sets and are an investment in the improvement of hyperspectral data processing.

science data processing↗
NASA NTRS2015

Unified User Interface to Support Effective and Intuitive Data Discovery, Dissemination, and Analysis at NASA GES DISC

Goddard Earth Sciences Data and Information Services Center (GES DISC) has been providing access to scientific data sets since 1990s. Beginning as one of the first Earth Observing System Data and Information System (EOSDIS) archive centers, GES DISC has evolved to offer a wide range of science-enabling services. With a growing understanding of needs and goals of its science users, GES DISC continues to improve and expand on its broad set of data discovery and access tools, sub-setting services, and visualization tools. Nonetheless, the multitude of the available tools, a partial overlap of functionality, and independent and uncoupled interfaces employed by these tools often leave the end users confused as of what tools or services are the most appropriate for a task at hand. As a result, some the services remain underutilized or largely unknown to the users, significantly reducing the availability of the data and leading to a great loss of scientific productivity. In order to improve the accessibility of GES DISC tools and services, we have designed and implemented UUI, the Unified User Interface. UUI seeks to provide a simple, unified, and intuitive one-stop shop experience for the key services available at GES DISC, including sub-setting (Simple Subset Wizard), granule file search (Mirador), plotting (Giovanni), and other services. In this poster, we will discuss the main lessons, obstacles, and insights encountered while designing the UUI experience. We will also present the architecture and technology behind UUI, including NodeJS, Angular, and Mongo DB, as well as speculate on the future of the tool at GES DISC as well as in a broader context of the Space Science Informatics.

web portal↗
NASA NTRS2019

Bringing Analysis Closer to Data: Developing a Visualization Tool for L2 Earth Science Satellite Data

Earth Science satellite missions provide a unique opportunity for scientists to visualize complex and multifaceted observations projected geospatially across maps of the Earth. While visualization tools can help scientists comprehend, analyze, and share data, visualizing Level-2 Earth Sciences data poses its own specific set of challenges. Since the geospatial information in Level-2 data files is stored as independent variables, the plotting process involves matching dimensional information from latitude and longitude with a desired variable. Variables are stored in different ways across various Earth Science data file formats, which complicates the process of extracting data and plotting variables from a given file without requiring extensive user input and prerequisite familiarity with the file type variable structure. In coordination with NASA’s Goddard Earth Sciences Data Information Services Center (GES DISC), the team developed a Level-2 Earth Science data visualization tool that aims to address some of the complexities associated with plotting Level-2 data. This tool offers command-line and user interface support for file and variable selection to accommodate varying use cases and degrees of user familiarity with the structure of a given file. The visualization tool is written in Python 3 and utilizes a modular approach to facilitate continued expansion and reuse. In addressing some common complications involved in plotting Level-2 Earth Sciences data, the tool aims to help to link the process of analysis more directly with data acquisition and visualization, bringing analysis closer to data across levels of processing.

Li, Angela W.↗
NASA NTRS2014

Data Albums: An Event Driven Search, Aggregation and Curation Tool for Earth Science

Approaches used in Earth science research such as case study analysis and climatology studies involve discovering and gathering diverse data sets and information to support the research goals. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. In cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. This paper presents a specialized search, aggregation and curation tool for Earth science to address these challenges. The search rool automatically creates curated 'Data Albums', aggregated collections of information related to a specific event, containing links to relevant data files [granules] from different instruments, tools and services for visualization and analysis, and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non relevant information and data.

Ramachandran, Rahul↗
NASA NTRS2007

2004 Space Report: Environment and Strategy for Space Research at NATO's Research and Technology Organisation (RTO)

This report describes the motivation for and a strategy to enhance the NATO Research and Technology Organisation's (RTO) current space research effort to reflect NATO's growing military dependence on space systems. Such systems and services provided by these systems are critical elements of military operations. NATO uses space systems for operational planning and support, communication, radio navigation, multi-sensor and multi-domain demonstrations. Such systems are also used to promote regional stability. A quantitative analysis of work related to space in the NATO RTO showed that during the period of 1998 - 2004, 5% of the research pursued in the NATO RTO has been clearly focused on space applications. Challenging environmental and organizational barriers for increasing RTO space research were identified. In part, these include lack of sufficient space expertise representation on panels, the military sensitivity of space, current panel work loads and the need for specific technical recommendations from peers. A strategy for enhancing space research in the RTO is to create a limited-life Space Advisory Group (SAG) composed of Space Expert Consultants who are panel members with appropriate expertise and additional expertise from the nations. The SAG will recommend and find support in the nations for specific technical activities related to space in the areas of Space Science, Remote Sensing Data Analysis, Spacecraft Systems, Surveillance and Early Warning, Training and Simulation and Policy. An RTO Space Advisory Group will provide an organizational mechanism to gain recognition of RTO as a forum for trans-Atlantic defence space research and to enhance space research activities.

Woods-Vedeler, Jessica A.↗
NASA NTRSDate not supplied

Preservation of Provenance and Context to Ensure Future Understandability of Airborne Earth Observations and Derived Data Products

Open-source science goes beyond making data from scientific projects (e.g., on-orbit/satellite missions, airborne and field investigations, and other data producing activities) openly available after they are generated, but involves and open sharing of information throughout the project lifecycle. Preservation of the data and associated information required for understanding and reusing the data well after the scientific projects is a contributor to open-source science as well. Considering the high investment in the on-orbit/satellite missions, we had developed a document titled “NASA Earth Science Data Preservation Content Specification (PCS)” in 2011. This document has been used as a requirement for recent on-orbit/satellite missions by NASA. Recently it became clear that the specifications should be applied to other scientific projects as well. Therefore, the document was revised to cover other types of projects, and a Preservation Content Implementation Guidance (PCIG) document was also developed. The revised PCS, and the PCIG, were published in 2022. The purpose of this presentation is to highlight the contents of these documents as they apply to suborbital/airborne investigations. The PCS calls for content preservation in eight general categories - Measuring Instrument/Platform Description, Instrument and Science Data Products and Metadata, Science Raw Data, Product and Algorithm Documentation, Instrument Calibration, Science Algorithm Software, Science Data Product Algorithm Inputs, Science Data Product Validation, and Science Data Access and Analysis Tools. While all these categories apply to various types of projects, a few clarifying sentences have been added to the descriptions of contents in each of the categories to show which categories are especially important to airborne and field investigations and where some contents are not applicable (or difficult to obtain). The PCIG document provides some general guidance applicable to all types of projects and specific guidance in a separate section for airborne and field investigations. This section calls out typical artifacts produced during such investigations that can meet the spirit of the various PCS categories.

remote sensing↗
NASA NTRS1982

Interpretation of HCMM images: A regional study

Potential users of HCMM data, especially those with only a cursory background in thermal remote sensing are familiarized with the kinds of information contained in the images that can be extracted with some reliability solely from inspection of such standard products as those generated at NASA/GSFC and now achieved in the National Space Science Data Center. Visual analysis of photoimagery is prone to various misimpressions and outright errors brought on by unawareness of the influence of physical factors as well as by sometimes misleading tonal patterns introduced during photoprocessing. The quantitative approach, which relies on computer processing of digital HCMM data, field measurements, and integration of rigorous mathematical models, can usually be used to identify, compensate for, or correct the contributions from at least some of the natural factors and those associated with photoprocessing. Color composite, day-IR, night-IR and visible images of California and Nevada are examined.

Source record↗
NASA NTRS1984

User's Guide for ERB 7 Matrix. Volume 1: Experiment Description and Quality Control Report for Year 1

The Nimbus 7 ERB MATRIX Tape is a computer program in which radiances and irradiances are converted into fluxes which are used to compute the basic scientific output parameters, emitted flux, albedo, and net radiation. They are spatially averaged and presented as time averages over one-day, six-day, and monthly periods. MATRIX data for the period November 16, 1978 through October 31, 1979 are presented. Described are the Earth Radiation Budget experiment, the Science Quality Control Report, Items checked by the MATRIX Science Quality Control Program, and Science Quality Control Data Analysis Report. Additional material from the detailed scientific quality control of the tapes which may be very useful to a user of the MATRIX tapes is included. Known errors and data problems and some suggestions on how to use the data for further climatologic and atmospheric physics studies are also discussed.

Tighe, R. J.↗