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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Langley Automated Sensor Inter-calibration System (LASICS): Open Access Tools for Satellite Imager Inter- Calibration

Satellite imager calibration teams are tasked with maintaining stable measurement records to facilitate reliable monitoring of geophysical parameters and ensure dependable input for forecast models. Satellite imagers are neither uniformly calibrated nor radiometrically scaled to a common reference standard. Consistent inter-calibration between various earth-orbiting satellite imager pairs is a critical step in the creation of seamless earth-scene reflectance data records over time for input to higher level algorithms that retrieve earth system climate-sensitive properties. Each imager inherently by virtue of its optics (and associated properties like spectral response etc.) and orbit will have a unique measurement of the same earth-scene reflected signal. A key part of this is the computationally efficient and optimal identification and prediction of science opportunities where the imager pairs from the irrespective earth-orbits near-simultaneously view the same stable terrestrial targets with nearly identical viewing and solar geometry.

Arun Gopalan↗
NASA NTRSDate not supplied

UASs in the VOG/Edge/FOG Sensor Web Environment

This paper will describe the evolution of information collection, derivation and delivery mechanisms in sensor webs utilizing Uninhabited Aerial Systems (UAS).We will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, UASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary UASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. The Author will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing UASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to other UAS development This paper will focus on applications, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

UAS↗
NASA NTRS1994

A Knowledge-Based Representation Scheme for Environmental Science Models

One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.

Keller, Richard M.↗
NASA NTRS1992

Software For Computing Selected Functions

Technical memorandum presents collection of software packages in Ada implementing mathematical functions used in science and engineering. Provides programmer with function support in Pascal and FORTRAN, plus support for extended-precision arithmetic and complex arithmetic. Valuable for testing new computers, writing computer code, or developing new computer integrated circuits.

Grant, David C.↗
NASA NTRS1986

Behind the scenes during a comet encounter

The contributions of NSSDC and SPAN to the September 11, 1985 ICE-Comet Giacobini-Zinner encounter are outlined. The NSSDC is a centralized archive and distribution center for data obtained from NASA space and earth science flight investigations while SPAN is a mission-independent computer-to-computer network used to gain electronic access to NASA facilities, coinvestigators, and data for many scientists. The ICE encounter revealed the value of SPAN and NSSDC in providing rapid access to important science data.

Green, James L.↗
NASA NTRS2003

Principles for Integrating Mars Analog Science, Operations, and Technology Research

During the Apollo program, the scientific community and NASA used terrestrial analog sites for understanding planetary features and for training astronauts to be scientists. Human factors studies (Harrison, Clearwater, & McKay 1991; Stuster 1996) have focused on the effects of isolation in extreme environments. More recently, with the advent of wireless computing, we have prototyped advanced EVA technologies for navigation, scheduling, and science data logging (Clancey 2002b; Clancey et al., in press). Combining these interests in a single expedition enables tremendous synergy and authenticity, as pioneered by Pascal Lee's Haughton-Mars Project (Lee 2001; Clancey 2000a) and the Mars Society s research stations on a crater rim on Devon Island in the High Canadian Arctic (Clancey 2000b; 2001b) and the Morrison Formation of southeast Utah (Clancey 2002a). Based on this experience, the following principles are proposed for conducting an integrated science, operations, and technology research program at analog sites: 1) Authentic work; 2) PI-based projects; 3) Unencumbered baseline studies; 4) Closed simulations; and 5) Observation and documentation. Following these principles, we have been integrating field science, operations research, and technology development at analog sites on Devon Island and in Utah over the past five years. Analytic methods include work practice simulation (Clancey 2002c; Sierhuis et a]., 2000a;b), by which the interaction of human behavior, facilities, geography, tools, and procedures are formalized in computer models. These models are then converted into the runtime EVA system we call mobile agents (Clancey 2002b; Clancey et al., in press). Furthermore, we have found that the Apollo Lunar Surface Journal (Jones, 1999) provides a vast repository or understanding astronaut and CapCom interactions, serving as a baseline for Mars operations and quickly highlighting opportunities for computer automation (Clancey, in press).

Clancey, William J.↗
NASA NTRS1999

S'COOL Provides Research Opportunities and Current Data for Today's Technological Classroom

NASA's Students' Cloud Observations On-Line (S'COOL) project, a hands-on educational project, was an innovative idea conceived by the scientists in the Radiation Sciences Branch at NASA Langley Research Center, Hampton, Virginia, in 1996. It came about after a local teacher expressed the idea that she wanted her students to be involved in real-life science. S'COOL supports NASA's Clouds and the Earth's Radiant Energy System (CERES) instrument, which was launched on the Tropical Rainforest Measuring Mission (TRMM) in November, 1997, as part of NASA's Earth Science Enterprise. With the S'COOL project students observe clouds and related weather conditions, compute data and note vital information while obtaining ground truth observations for the CERES instrument. The observations can then be used to help validate the CERES measurements, particularly detection of clear sky from space. In addition to meeting math, science and geography standards, students are engaged in using the computer to obtain, report and analyze current data, thus bringing modern technology into the realm of classroom, a paradigm that demands our attention.

Green, Carolyn J.↗
NASA NTRS2001

Adaptive Instrument Module: Space Instrument Controller "Brain" through Programmable Logic Devices

The Adaptive Instrument Module (AIM) will be the first true demonstration of reconfigurable computing with field-programmable gate arrays (FPGAs) in space, enabling the 'brain' of the system to evolve or adapt to changing requirements. In partnership with NASA Goddard Space Flight Center and the Australian Cooperative Research Centre for Satellite Systems (CRC-SS), APL has built the flight version to be flown on the Australian university-class satellite FEDSAT. The AIM provides satellites the flexibility to adapt to changing mission requirements by reconfiguring standardized processing hardware rather than incurring the large costs associated with new builds. This ability to reconfigure the processing in response to changing mission needs leads to true evolveable computing, wherein the instrument 'brain' can learn from new science data in order to perform state-of-the-art data processing. The development of the AIM is significant in its enormous potential to reduce total life-cycle costs for future space exploration missions. The advent of RAM-based FPGAs whose configuration can be changed at any time has enabled the development of the AIM for processing tasks that could not be performed in software. The use of the AIM enables reconfiguration of the FPGA circuitry while the spacecraft is in flight, with many accompanying advantages. The AIM demonstrates the practicalities of using reconfigurable computing hardware devices by conducting a series of designed experiments. These include the demonstration of implementing data compression, data filtering, and communication message processing and inter-experiment data computation. The second generation is the Adaptive Processing Template (ADAPT) which is further described in this paper. The next step forward is to make the hardware itself adaptable and the ADAPT pursues this challenge by developing a reconfigurable module that will be capable of functioning efficiently in various applications. ADAPT will take advantage of radiation tolerant RAM-based field programmable gate array (FPGA) technology to develop a reconfigurable processor that combines the flexibility of a general purpose processor running software with the performance of application specific processing hardware for a variety of high performance computing applications.

Darrin, Ann Garrison↗
NASA NTRS2002

Grids for Dummies: Featuring Earth Science Data Mining Application

This viewgraph presentation discusses the concept and advantages of linking computers together into data grids, an emerging technology for managing information across institutions, and potential users of data grids. The logistics of access to a grid, including the use of the World Wide Web to access grids, and security concerns are also discussed. The potential usefulness of data grids to the earth science community is also discussed, as well as the Global Grid Forum, and other efforts to establish standards for data grids.

Hinke, Thomas H.↗
NASA NTRS2010

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) Science Processing Pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

photocenter↗
NASA NTRS2012

MSL-RAD Cruise Operations Concept

The Mars Science Laboratory (MSL) payload includes the Radiation Assessment Detector (RAD) instrument, intended to fully characterize the radiation environment for the MSL mission. The RAD instrument operations concept is intended to reduce impact to spacecraft resources and effort for the MSL operations team. By design, RAD autonomously performs regular science observations without the need for frequent commanding from the Rover Compute Element (RCE). RAD operates with pre-defined "sleep" and "observe" periods, with an adjustable duty cycle for meeting power and data volume constraints during the mission. At the start of a new science observation, RAD performs a pre-observation activity to assess count rates for selected RAD detector elements. Based on this assessment, RAD can enter "solar event" mode, in which instrument parameters (including observation duration) are selected to more effectively characterize the environment. At the end of each observation period, RAD stores a time-tagged, fixed length science data packet in its non-volatile mass memory storage. The operating cadence is defined by adjustable parameters, also stored in non-volatile memory within the instrument. Periodically, the RCE executes an on-board sequence to transfer RAD science data packets from the instrument mass storage to the MSL downlink buffer. Infrequently, the RAD instrument operating configuration is modified by updating internal parameter tables and configuration entries.

Mars Science Laboratory (MSL)↗
NASA NTRS2004

Safe Agents in Space: Lessons from the Autonomous Sciencecraft Experiment

An Autonomous Science Agent is currently flying onboard the Earth Observing One Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and run-time robust execution. Because of the deployment to a remote spacecraft, this Autonomous Science Agent has stringent constraints of autonomy, reliability, and limited computing resources. We describe these constraints and how they are reflected in our agent architecture.

Eatth Observing One Spacecraft↗
NASA NTRSDate not supplied

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

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

Alexey N Shiklomanov↗
NASA NTRS2013

Science Opportunity Analyzer (SOA) Version 8

SOA allows scientists to plan spacecraft observations. It facilitates the identification of geometrically interesting times in a spacecraft s orbit that a user can use to plan observations or instrument-driven spacecraft maneuvers. These observations can then be visualized multiple ways in both two- and three-dimensional views. When observations have been optimized within a spacecraft's flight rules, the resulting plans can be output for use by other JPL uplink tools. Now in its eighth major version, SOA improves on these capabilities in a modern and integrated fashion. SOA consists of five major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, and Data Output. Opportunity Search is a GUI-driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last-minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily assess the cost to science if flight rule changes occur. Data Output allows the user to compute ancillary data related to an observation or to a given position of the spacecraft along its trajectory. The data can be saved as a tab-delimited text file or viewed as a graph. SOA combines science planning functionality unique to both JPL and the sponsoring spacecraft. SOA is able to ingest JPL SPICE Kernels that are used to drive the tool and its computations. A Percy search engine is then included that identifies interesting time periods for the user to build observations. When observations are then built, flight-like orientation algorithms replicate spacecraft dynamics to closely simulate the flight spacecraft s dynamics. SOA v8 represents large steps forward from SOA v7 in terms of quality, reliability, maintainability, efficiency, and user experience. A tailored agile development environment has been built around SOA that provides automated unit testing, continuous build and integration, a consolidated Web-based code and documentation storage environment, modern Java enhancements, and a focus on usability

Witoff, Robert J.↗
NASA NTRSDate not supplied

Visioning a Global Carbon Monitoring System That Can Quantify and Attribute Ocean Carbon Dioxide Removal: Where Are We Now and How Might We Get There?

As atmospheric greenhouse gas concentrations and the resulting social costs rise, it is increasingly important to conduct research on technical approaches to remove carbon dioxide from the atmosphere at the gigaton scale. One highly uncertain but perhaps plausible solution is ocean carbon dioxide (CO2) removal (CDR), which encompasses a suite of proposed techniques for increasing the net flux of CO2 from the atmosphere to the ocean. As reflected in a 2022 National Academy of Sciences report, interest in ocean CDR is rapidly growing, and new stakeholders from a wide range of fields want access to air-sea CO2 flux and ocean carbon information to understand the potential risks and benefits of ocean CDR. Moreover, there is an urgent need for research to develop a scientific basis to support these societal needs. At the same time, there is a growing need to vision a global carbon monitoring system that can quantify natural and anthropogenic perturbations in the air-sea CO2 flux to quantify and attribute the impacts of ocean CDR efforts on the ocean carbon sink. Here, we propose to present nascent efforts at the Ames Research Center to leverage NASA's unique remote sensing and computational capabilities and expertise in basic and applied Earth science to meet the needs of the ocean CDR stakeholder community as represented by the OceanVisions network. Specifically we aim to develop a global ocean CDR scenario explorer with two objectives: 1) to make quantitative estimates of the air-sea CO2 flux and its uncertainty more accessible to a wide range of users, and 2) to enable these diverse users to interactively explore the uncertain impacts on air-sea CO2 fluxes in a wide range of ocean CDR scenarios. The information would be provided to users via a public graphical user interface, and the results would be based on a new synthesis of scientific observations and knowledge in a global ocean mixed layer inverse model run on supercomputers. The proposed tool aims to fill a unique and valuable niche for users and the scientific community by balancing tradeoffs between user interests, scientific knowledge, and technical capabilities. We will conclude by visioning the potential implications for a global carbon monitoring system in a world with gigaton scale ocean CDR.

Global↗
NASA NTRS1994

The assessment of virtual reality for human anatomy instruction

This research project seeks to meet the objective of science training by developing, assessing, and validating virtual reality as a human anatomy training medium. In ideal situations, anatomic models, computer-based instruction, and cadaver dissection are utilized to augment the traditional methods of instruction. At many institutions, lack of financial resources limits anatomy instruction to textbooks and lectures. However, human anatomy is three dimensional, unlike the one dimensional depiction found in textbooks and the two dimensional depiction found on the computer. Virtual reality is a breakthrough technology that allows one to step through the computer screen into a three dimensional world. This technology offers many opportunities to enhance science education. Therefore, a virtual testing environment of the abdominopelvic region of a human cadaver was created to study the placement of body parts within the nine anatomical divisions of the abdominopelvic region and the four abdominal quadrants.

Benn, Karen P.↗
NASA NTRS2002

The Torque of the Planet: NASA Researcher Uses NCCS Computers to Probe Atmosphere-Land-Ocean Coupling

The study of Earth science is like a giant puzzle, says Braulio Sanchez. "The more you know about the individual pieces, the easier it is to fit them together." A researcher with Goddard's Space Geodesy Branch, Sanchez has been using NCCS supercomputer and mass storage resources to show how the angular momenta of the atmosphere, the oceans, and the solid Earth are dynamically coupled. Sanchez has calculated the magnitude of atmospheric torque on the planet and has determined some of the possible effects that torque has on Earth's rotation.

Source record↗