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NASA NTRS2011

Land and Atmosphere Near-Real-Time Capability for Earth Observing System

The past decade has seen a rapid increase in availability and usage of near-real-time data from satellite sensors. The EOSDIS (Earth Observing System Data and Information System) was not originally designed to provide data with sufficiently low latency to satisfy the requirements for near-real-time users. The EOS (Earth Observing System) instruments aboard the Terra, Aqua and Aura satellites make global measurements daily, which are processed into higher-level 'standard' products within 8-40 hours of observation and then made available to users, primarily earth science researchers. However, applications users, operational agencies, and even researchers desire EOS products in near-real-time to support research and applications, including numerical weather and climate prediction and forecasting, monitoring of natural hazards, ecological/invasive species, agriculture, air quality, disaster relief and homeland security. These users often need data much sooner than routine science processing allows, usually within 3 hours, and are willing to trade science product quality for timely access. While Direct Broadcast provides more timely access to data, it does not provide global coverage. In 2002, a joint initiative between NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration), and the DOD (Department of Defense) was undertaken to provide data from EOS instruments in near-real-time. The NRTPE (Near Real Time Processing Effort) provided products within 3 hours of observation on a best-effort basis. As the popularity of these near-real-time products and applications grew, multiple near-real-time systems began to spring up such as the Rapid Response System. In recognizing the dependence of customers on this data and the need for highly reliable and timely data access, NASA's Earth Science Division sponsored the Earth Science Data and Information System Project (ESDIS)-led development of a new near-real-time system called LANCE (Land, Atmosphere Near-Real-Time Capability for EOS) in 2009. LANCE consists of special processing elements, co-located with selected EOSDIS data centers and processing facilities. A primary goal of LANCE is to bring multiple near-real-time systems under one umbrella, offering commonality in data access, quality control, and latency. LANCE now processes and distributes data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments within 3 hours of satellite observation. The Rapid Response System and the Fire Information for Resource Management System (FIRMS) capabilities will be incorporated into LANCE in 2011. LANCE maintains a central website to facilitate easy access to data and user services. LANCE products are extensively tested and compared with science products before being made available to users. Each element also plans to implement redundant network, power and server infrastructure to ensure high availability of data and services. Through the user registration system, users are informed of any data outages and when new products or services will be available for access. Building on a significant investment by NASA in developing science algorithms and products, LANCE creates products that have a demonstrated utility for applications requiring near-real-time data. From lower level data products such as calibrated geolocated radiances to higher-level products such as sea ice extent, snow cover, and cloud cover, users have integrated LANCE data into forecast models and decision support systems. The table above shows the current near-real-time product categories by instrument. The ESDIS Project continues to improve the LANCE system and use the experience gained through practice to seek adjustments to improve the quality and performance of the system. For example, anGC-compliant Web Map Service (WMS) will be added shortly that will allow users to download geo-referenced MODIS images for arbitrary bounding boxes. Further, an OGC-compliant Web Coverage Service (WCS) will be added later this year that will expedite user access to arbitrary data subsets or re-formatted products. AIRS images are now served through WMS and available in multiple formats (PNG, GeoTIFF, KMZ). NASA has established a LANCE User Working Group to steer the development of the system and create a forum for sharing ideas and experiences that are expected to further improve the LANCE capabilities. The LANCE system has proved a success by satisfying the growing needs of the applications and operational communities for land and atmosphere data in near-real-time. NASA's Earth Sciences Division was able to leverage existing science research capabilities to provide the near-real-time community with products and imagery that support monitoring of disasters in a timely manner.

Murphy, Kevin J.↗
NASA NTRS1989

An interactive, discipline-independent data visualization system

The data visualization techniques used by National Space Science Data Center Graphics System are discussed. The system includes a self-describing data abstraction for the storage and manipulation of multidimensional data for discipline-independent scientific applications. The system's data format and graphics display are described. Consideration is given to techniques developed for the rapid display and manipulation of large, complex data sets and for manipulating algorithms with portable implementations which can operate on any data object or geometry. The processes of operating the system are given and examples are presented from applying the system to various types of data, including TOMS data, data from the International Satellite Cloud Climatology Project, and IRAS data.

Treinish, Lloyd A.↗
NASA NTRS1993

Accessing Earth science data from the EOS data and information system

An overview of the Earth Observing System Data and Information System (EOSDIS) is presented, concentrating on the users' interactions with the system and highlighting those features that are driven by the unique requirements of the Global Change Research Program and the supported science community. However, a basic premise of the EOSDIS is that the system must evolve to meet changes in user needs and to incorporate advances in data system technology. Therefore, the development process which is being used to accommodate these changes and some of the potential areas of change are also addressed.

Mcdonald, Kenneth R.↗
NASA NTRSDate not supplied

A User-Focused Renovation of CERES Metadata

Production software and public data products for Clouds and the Earth’s Radiant Energy System (CERES) continue to evolve as the project extends its climate data record. The data management team for CERES is currently undertaking major renovations of both code and data products, the latter of which is, of course, in service of improving user experience. A major mode of CERES’ data product improvement is in renovating products’ metadata. Metadata standards have evolved since CERES began producing its data products in 2000. In its twentieth year, CERES essentially asked the question: how would the project design its data products if it could start all over again? With forthcoming editions, this rebirth will be realized. CERES has redesigned its metadata standards to best position itself for data discoverability. The project has used the latest standards being developed in NASA’s Earth Science Data and Information Systems (ESDIS) Project’s Unified Metadata Model (UMM) documentation; collaborated with the Atmospheric Science Data Center (ASDC) to ensure compliance with Common Metadata Repository compatibility, and continued compliance with Climate and Forecast (CF) Conventions. In doing so, the team created its own, internal document for proper metadata creation and metadata verification software that is deployed prior to all code deliveries. This presentation will discuss this redesign process, as well as needs met and those that are still outstanding in the search for an improved user experience with CERES data products.

Kathleen Dejwakh↗
NASA NTRS1975

General purpose simulation system of the data management system for space shuttle mission 18

The simulation program of the science and engineering data management system for the space shuttle is presented. The programming language used was General Purpose Simulation System V (OS). The data flow was modeled from its origin at the experiments or subsystems to transmission from the space shuttle. Mission 18 was the particular flight chosen for simulation. First, the general structure of the program is presented and the trade studies which were performed are identified. Inputs required to make runs are discussed followed by identification of the output statistics. Some areas for model modifications are pointed out. A detailed model configuration, program listing and results are included.

Bengtson, N. M.↗
NASA NTRS2019

Improving Earth Science Data Literacy

The improvement of scientific literacy across the public can take on a myriad of forms and activities. The vast archives of NASA’s Earth science data, as one example, reflect the agency’s ongoing commitment to producing the highest quality data, services and tools intended for enabling the public to understand the complexity of Earth systems. The focus of this presentation is to explore and reveal the specific strategies the NASA Earth Science Data and Information System (ESDIS) Project uses to support our very large and diverse user communities access to and understanding of these science data and services. The diversity of our subject matter, spanning the whole Earth science domain, is mirrored by our user communities which are equally as broad in their needs and abilities. ESDIS and the supporting Communication Team leverages an array of internet-based tools and communication strategies to both understand actual user needs and develop optimum pathways for improving our users’ knowledge and understanding of the data. We will focus our limited time on a few of the high-impact activities including Webinars, or video-based, on-line, interactive discussions and presentations that since their introduction in 2013 have become a staple for user-instructor interaction via the internet. Here we discuss the types of content we produce and many lessons learned on how best to use this medium for improving user literacy on the subject at hand. In addition, we include discussion of our approach to using various social media platforms and tools to bolster the awareness of our users for data and services that are likely of interest. The ESDIS project remains active in various social media campaigns where our particular blend of science, data and tools engages new users curious of how to get their science or application started using NASA-available data. We anticipate that these examples may prove to be novel in their application to improving science literacy and skill development among the public.

Lindsay, Francis↗
NASA NTRS2008

Evolution of the Earth Observing System (EOS) Data and Information System (EOSDIS)

One of the strategic goals of the U.S. National Aeronautics and Space Administration (NASA) is to "Develop a balanced overall program of science, exploration, and aeronautics consistent with the redirection of the human spaceflight program to focus on exploration". An important sub-goal of this goal is to "Study Earth from space to advance scientific understanding and meet societal needs." NASA meets this subgoal in partnership with other U.S. agencies and international organizations through its Earth science program. A major component of NASA s Earth science program is the Earth Observing System (EOS). The EOS program was started in 1990 with the primary purpose of modeling global climate change. This program consists of a set of space-borne instruments, science teams, and a data system. The instruments are designed to obtain highly accurate, frequent and global measurements of geophysical properties of land, oceans and atmosphere. The science teams are responsible for designing the instruments as well as scientific algorithms to derive information from the instrument measurements. The data system, called the EOS Data and Information System (EOSDIS), produces data products using those algorithms as well as archives and distributes such products. The first of the EOS instruments were launched in November 1997 on the Japanese satellite called the Tropical Rainfall Measuring Mission (TRMM) and the last, on the U.S. satellite Aura, were launched in July 2004. The instrument science teams have been active since the inception of the program in 1990 and have participation from Brazil, Canada, France, Japan, Netherlands, United Kingdom and U.S. The development of EOSDIS was initiated in 1990, and this data system has been serving the user community since 1994. The purpose of this chapter is to discuss the history and evolution of EOSDIS since its beginnings to the present and indicate how it continues to evolve into the future. this chapter is organized as follows. Sect. 7.2 provides a discussion of EOSDIS, its elements and their functions. Sect. 7.3 provides details regarding the move towards more distributed systems for supporting both the core and community needs to be served by NASA Earth science data systems. Sect. 7.4 discusses the use of standards and interfaces and their importance in EOSDIS. Sect. 7.5 provides details about the EOSDIS Evolution Study. Sect. 7.6 presents the implementation of the EOSDIS Evolution plan. Sect. 7.7 briefly outlines the progress that the implementation has made towards the 2015 Vision, followed by a summary in Sect. 7.8.

Ramapriyan, Hampapuram K.↗
NASA NTRS1992

Knowledge-based assistance for science visualization and analysis using large distributed databases

Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scaleable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on the concept called the Data Hub. With the Data Hub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (access, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

Handley, Thomas H., Jr.↗
NASA NTRS1993

DataHub--Knowledge-Based Science Data Management for Exploratory Data Analysis

It is our belief that new modes of research and new tools will be required to handle the massive amount of diverse data that is to be stored, organized, accessed, distributed, visualized, and analyzed. The fundamental innovation required is the integration of three automation technologies, videlicet knowledge-based expert systems, science visualization and science data management. This integration is based on a concept caled the DataHub, which we describe here.

DataHub↗
NASA NTRS2012

NASA Tech Briefs, June 2012

Topics covered include: iGlobe Interactive Visualization and Analysis of Spatial Data; Broad-Bandwidth FPGA-Based Digital Polyphase Spectrometer; Small Aircraft Data Distribution System; Earth Science Datacasting v2.0; Algorithm for Compressing Time-Series Data; Onboard Science and Applications Algorithm for Hyperspectral Data Reduction; Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data; Security Data Warehouse Application; Integrated Laser Characterization, Data Acquisition, and Command and Control Test System; Radiation-Hard SpaceWire/Gigabit Ethernet-Compatible Transponder; Hardware Implementation of Lossless Adaptive Compression of Data From a Hyperspectral Imager; High-Voltage, Low-Power BNC Feedthrough Terminator; SpaceCube Mini; Dichroic Filter for Separating W-Band and Ka-Band; Active Mirror Predictive and Requirement Verification Software (AMP-ReVS); Navigation/Prop Software Suite; Personal Computer Transport Analysis Program; Pressure Ratio to Thermal Environments; Probabilistic Fatigue Damage Program (FATIG); ASCENT Program; JPL Genesis and Rapid Intensification Processes (GRIP) Portal; Data::Downloader; Fault Tolerance Middleware for a Multi-Core System; DspaceOgreTerrain 3D Terrain Visualization Tool; Trick Simulation Environment 07; Geometric Reasoning for Automated Planning; Water Detection Based on Color Variation; Single-Layer, All-Metal Patch Antenna Element with Wide Bandwidth; Scanning Laser Infrared Molecular Spectrometer (SLIMS); Next-Generation Microshutter Arrays for Large-Format Imaging and Spectroscopy; Detection of Carbon Monoxide Using Polymer-Composite Films with a Porphyrin-Functionalized Polypyrrole; Enhanced-Adhesion Multiwalled Carbon Nanotubes on Titanium Substrates for Stray Light Control; Three-Dimensional Porous Particles Composed of Curved, Two-Dimensional, Nano-Sized Layers for Li-Ion Batteries 23 Ultra-Lightweight; and Ultra-Lightweight Nanocomposite Foams and Sandwich Structures for Space Structure Applications.

Source record↗
NASA NTRS1981

Science and Applications Space Platform (SASP) End-to-End Data System Study

The capability of present technology and the Tracking and Data Relay Satellite System (TDRSS) to accommodate Science and Applications Space Platforms (SASP) payload user's requirements, maximum service to the user through optimization of the SASP Onboard Command and Data Management System, and the ability and availability of new technology to accommodate the evolution of SASP payloads were assessed. Key technology items identified to accommodate payloads on a SASP were onboard storage devices, multiplexers, and onboard data processors. The primary driver is the limited access to TDRSS for single access channels due to sharing with all the low Earth orbit spacecraft plus shuttle. Advantages of onboard data processing include long term storage of processed data until TRDSS is accessible, thus reducing the loss of data, eliminating large data processing tasks at the ground stations, and providing a more timely access to the data.

Crawford, P. R.↗
NASA NTRS2003

Space Communications and Data Systems Technologies for Next Generation Earth Science Measurements

The next generation of Earth observing satellites and sensor networks will face challenges in supporting robust high rate communications links from the increasingly sophisticated onboard instruments. Emerging applications will need data rates forecast to be in the 100's to 1000's of Mbps. As mission designers seek smaller spacecraft, challenges exist in reducing the size and power requirements while increasing the capacity of the spacecraft's communications technologies. To meet these challenges, this work looks at three areas of selected space communications and data services technologies, specifically in the development of reflectarray antennas, demonstration of space Internet concepts, and measurement of atmospheric propagation effects on Ka-band signal transmitted from LEO.

Bauer, Robert A.↗
NASA NTRS2001

Simple, Scalable, Script-Based Science Processor (S4P)

The development and deployment of data processing systems to process Earth Observing System (EOS) data has proven to be costly and prone to technical and schedule risk. Integration of science algorithms into a robust operational system has been difficult. The core processing system, based on commercial tools, has demonstrated limitations at the rates needed to produce the several terabytes per day for EOS, primarily due to job management overhead. This has motivated an evolution in the EOS Data Information System toward a more distributed one incorporating Science Investigator-led Processing Systems (SIPS). As part of this evolution, the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has developed a simplified processing system to accommodate the increased load expected with the advent of reprocessing and launch of a second satellite. This system, the Simple, Scalable, Script-based Science Processor (S42) may also serve as a resource for future SIPS. The current EOSDIS Core System was designed to be general, resulting in a large, complex mix of commercial and custom software. In contrast, many simpler systems, such as the EROS Data Center AVHRR IKM system, rely on a simple directory structure to drive processing, with directories representing different stages of production. The system passes input data to a directory, and the output data is placed in a "downstream" directory. The GES DAAC's Simple Scalable Script-based Science Processing System is based on the latter concept, but with modifications to allow varied science algorithms and improve portability. It uses a factory assembly-line paradigm: when work orders arrive at a station, an executable is run, and output work orders are sent to downstream stations. The stations are implemented as UNIX directories, while work orders are simple ASCII files. The core S4P infrastructure consists of a Perl program called stationmaster, which detects newly arrived work orders and forks a job to run the appropriate executable (registered in a configuration file for that station). Although S4P is written in Perl, the executables associated with a station can be any program that can be run from the command line, i.e., non-interactively. An S4P instance is typically monitored using a simple Graphical User Interface. However, the reliance of S4P on UNIX files and directories also allows visibility into the state of stations and jobs using standard operating system commands, permitting remote monitor/control over low-bandwidth connections. S4P is being used as the foundation for several small- to medium-size systems for data mining, on-demand subsetting, processing of direct broadcast Moderate Resolution Imaging Spectroradiometer (MODIS) data, and Quick-Response MODIS processing. It has also been used to implement a large-scale system to process MODIS Level 1 and Level 2 Standard Products, which will ultimately process close to 2 TB/day.

Lynnes, Christopher↗
NASA NTRS1984

Planetary Science Analysis Support System: Hardware Report

The computeer hardware requirements for a planetary science data analysis support system are described. Present practice, state-of-the-art, and predictable developments are considered. Specific recommendations are presented for those who plan to acquire new computational tools, those who must install and use them, and those who pay for them.

Source record↗
NASA NTRS2001

Lessons from Adaptive Level One Accelerator (ALOA) System Implementation

The Adaptive Level One Accelerator (ALOA) system was developed as part of the Earth Science Data and Information System (ESDIS) project. The reconfigurable computing technologies were investigated for Level 1 satellite telemetry data processing to achieve computing acceleration and cost reduction for the next-generation Level 1 data processing systems. The MODIS instrument calibration algorithm was implemented using reconfigurable a computer. The system development process and the lessons learned throughout the design cycle are summarized in this paper.

Patel, Umesh D.↗
NASA NTRS2016

Evolving a NASA Digital Object Identifiers System with Community Engagement

To demonstrate how the ESDIS (Earth Science Data and Information System) DOI (Digital Object Identifier) system and its processes have evolved over these years based on the recommendations provided by the user community (whether the community members create and manage DOI information or use DOIs in the data citations). The user community is comprised of people with common interests and needs for data identifiers who are actively involved in the creation and usage process. Engagement describes the interactive context wherein the community provides information, evaluates the proposed processes, and provides guidance in the area of identifiers.

Identifiers↗