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At least 595 records · Page 33

A Perfect View of Vesta: Creating Pointing Observations for the Dawn Spacecraft on Asteroid 4 Vesta

The Dawn spacecraft has a timely and clever assignment in store. It will take a close look at two intact survivors from the dawn of the solar system (asteroids 4 Vesta and 1 Ceres) to understand more about solar system origin and evolution. To optimize science return, Dawn must make carefully designed observations on approach and in survey orbit, high altitude mapping orbit, and low altitude mapping orbit at each body. In this report, observations outlined in the science plan are modeled using the science opportunity analyzer program for the Vesta encounter. Specifically, I encoded Dawn's flight rules into the program, modeled pointing profiles of the optical instruments (framing camera, visible infrared spectrometer) and mapped their fields of view onto Vesta's surface. Visualization of coverage will provide the science team with information necessary to assess feasibility of alternative observation plans. Dawn launches in summer 2006 and ends its journey in 2016. Instrument observations on Vesta in 2011 will supply detailed information about Vesta's surface and internal structure. These data will be used to analyze the formation and history of the protoplanet and, therefore, complete an important step in understanding the development of our solar system.

Hay, Katrina M.↗

A model to assess the Mars Telecommunications Network relay robustness

The relatively long mission durations and compatible radio protocols of current and projected Mars orbiters have enabled the gradual development of a heterogeneous constellation providing proximity communication services for surface assets. The current and forecasted capability of this evolving network has reached the point that designers of future surface missions consider complete dependence on it. Such designers, along with those architecting network requirements, have a need to understand the robustness of projected communication service. A model has been created to identify the robustness of the Mars Network as a function of surface location and time. Due to the decade-plus time horizon considered, the network will evolve, with emerging productive nodes and nodes that cease or fail to contribute. The model is a flexible framework to holistically process node information into measures of capability robustness that can be visualized for maximum understanding. Outputs from JPL's Telecom Orbit Analysis Simulation Tool (TOAST) provide global telecom performance parameters for current and projected orbiters. Probabilistic estimates of orbiter fuel life are derived from orbit keeping burn rates, forecasted maneuver tasking, and anomaly resolution budgets. Orbiter reliability is estimated probabilistically. A flexible scheduling framework accommodates the projected mission queue as well as potential alterations.

Mars Telecommunications Orbiter (MTO)↗

Creating a NASA-Wide Museum Alliance

NASA's Museum Alliance is a nationwide network of informal educators at museums, science centers, and planetariums that present NASA information to their local audiences. Begun in 2002 as the Mars Museum Visualization Alliance with advisors from a dozen museums, the network has grown to over 300 people from 200 organizations, including a dozen or so international partners. The network has become a community of practice among these informal educators who work with students, educators, and the general public on a daily basis, presenting information and fielding questions about space exploration. Communications are primarily through an active listserve, regular telecons, and a pass word protected website. Professional development is delivered via telecons and downloadable presentations. Current content offerings include Mars exploration, Cassini, Stardust, Genesis, Deep Impact, Earth observations, STEREO, and missions to explore beyond our solar system.

planetary sciences↗

Processing Digital Imagery to Enhance Perceptions of Realism

Multi-scale retinex with color restoration (MSRCR) is a method of processing digital image data based on Edwin Land s retinex (retina + cortex) theory of human color vision. An outgrowth of basic scientific research and its application to NASA s remote-sensing mission, MSRCR is embodied in a general-purpose algorithm that greatly improves the perception of visual realism and the quantity and quality of perceived information in a digitized image. In addition, the MSRCR algorithm includes provisions for automatic corrections to accelerate and facilitate what could otherwise be a tedious image-editing process. The MSRCR algorithm has been, and is expected to continue to be, the basis for development of commercial image-enhancement software designed to extend and refine its capabilities for diverse applications.

Woodell, Glenn A.↗

Characterize Aerosols from MODIS MISR OMI MERRA-2: Dynamic Image Browse Perspective

Among the known atmospheric constituents, aerosols still represent the greatest uncertainty in climate research. To understand the uncertainty is to bring altogether of observational (in-situ and remote sensing) and modeling datasets and inter-compare them synergistically for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if these earth science data (satellite and modeling) are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite-borne sensors routinely measure aerosols. There is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) have developed a new visualization service (NASA Level 2 Data Quality Visualization, DQViz)supporting various visualization and data accessing capabilities from satellite Level 2(MODISMISROMI) and long term assimilated aerosols from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2 displaying at their own native physical-retrieved spatial resolution. Functionality will include selecting data sources (e.g., multiple parameters under the same measurement), defining area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting and reformatting.

data quality↗

Giovanni in the Cloud: Earth Science Data Exploration in Amazon Web Services

Giovanni is an exploration tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), providing 22 analysis and visualization services for over 1600 Earth Science data variables. Owing to its popularity, Giovanni has experienced a consistent growth in overall demand, with periodic usage spikes attributed to trainings by education organizations, extensive data analysis in response to natural disasters, preparations for science meetings, etc. Furthermore, the new generation of spaceborne sensors and high resolution models have resulted in an exponential growth in data volume with data distributed across the traditional boundaries of data centers. Seamless exploration of data (without users having to worry about data center boundaries) has been a key recommendation of the GES DISC User Working Group. These factors have required new strategies for delivering acceptable performance. The cloud-based Giovanni, built on Amazon Web Services (AWS), evaluates (1) AWS native solutions to provide a scalable, serverless architecture; (2) open standards for data storage in the Cloud; (3) a cost model for operations; and (4) end-user performance. Our preliminary findings indicate that the use of serverless architecture has a potential to significantly reduce development and operational cost of Giovanni. The combination of using AWS managed services, storage of data in open standards, and schema-on-read data access strategy simplifies data access and analytics, in addition to making data more accessible to the end users of Giovanni through popular programming languages.

Giovanni↗

The Best Educational Tool for Interdisciplinary Earth Science Giovanni

Accessing and using NASA Earth science data has commonly presented a challenge to many educators and students, due to issues such as heterogeneous data formats, complex data structures, large volumes of data storage, special programming requirements, and diverse analytical software options that often require a significant investment in time and resources, especially for novices. By facilitating data access and evaluation, as well as promoting open access to create a more level playing field for non-funded scientists, NASA Earth observation data can be more readily used for scientific discovery and societal benefits. To advance this goal, the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) developed the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni). To date, Giovanni has assisted researchers around the world publish over 1300 peer-reviewed papers in a wide range of Earth science disciplines. In this presentation, we will demonstrate how easy it is to use Giovanni for the rapid creation of many different analyses of both weather and climate events.

interdisciplinary↗

Natural Language Processing Analysis of Notices to Airmen for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized.

Natural Language Processing↗

Natural Language Processing (NLP) Analysis of NOTAMs for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized. Video is an mp4 download, with a play time of 9 min 35 secs.

Natural Language Processing↗

Assessment of a head-mounted miniature monitor

Two experiments were conducted to assess the capabilities and limitations of the Private Eye, a miniature, head-mounted monitor. The first experiment compared the Private Eye with a cathode ray tube (CRT) and hard copy in both a constrained and unconstrained work envelope. The task was a simulated maintenance and assembly task that required frequent reference to the displayed information. A main effect of presentation media indicated faster placement times using the CRT as compared with hard copy. There were no significant differences between the Private Eye and either the CRT or hard copy for identification, placement, or total task times. The goal of the second experiment was to determine the effects of various local visual parameters on the ability of the user to accurately perceive the information of the Private Eye. The task was an interactive video game. No significant performance differences were found under either bright or dark ambient illumination environments nor with either visually simple or complex task backgrounds. Glare reflected off of the bezel surrounding the monitor did degrade performance. It was concluded that this head-mounted, miniature monitor could serve a useful role for in situ operations, especially in microgravity environments.

Hale, J. P., II↗

Challenges in Development of Online Visualization and Analysis Tools for Satellite Data

Over the years, various online visualization and analysis tools have been developed to facilitate satellite data access and help scientific users around the world to conduct research and develop applications (e.g., data product evaluation, what-if questions, etc.). For those who are new to satellite data products, using them can be a daunting task due to many obstacles in data processing such as data formats, complex data structures, special software packages, unfamiliar terminology, etc., especially when one is not sure whether a dataset is suitable for his/er research project. Even for experienced users, developing software for data processing and analysis can be a costly and time-consuming task. Online visualization tools can overcome many of these difficulties and allow users to focus on scientific questions. For example, Giovanni (the Geospatial Interactive Online Visualization and Analysis Infrastructure, https://giovanni.gsfc.nasa.gov), developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), allows access over 1900 satellite and model variables in 82 measurement groups of 8 disciplines without downloading data and software. Main features include basic functions for data analysis and visualization, data provenance, output data in different formats (ASCII, NetCDF, GeoTIFF), and more. Over the years, ~1700 peer-reviewed publications in different disciplines have been benefited from Giovanni in research activities (e.g. initial investigation, what-if questions, product evaluation). Despite the success of online visualization and analysis tools, challenges and new opportunities still exist and more can be done with new requirements and technology. Examples are: a) how to increase the efficiency of dataset search by enhancing intuitive aspects; b) how to facilitate interdisciplinary research; c) how to provide data quality information; d) how to engage users to participate in data quality assessment; and more. NASA Earth Observing System Data and Information System (EOSDIS) satellite-based data products are processed at various levels ranging from Level 0 to Level 4. While most users use data products at higher levels (Level-3 and 4), products at lower levels are still important for case studies, algorithm development, ground validation, etc. In this presentation, we will use Giovanni as an example to present and discuss challenges and near-future opportunities for satellite data online visualization and analysis tools.

Liu, Zhong↗

Cockpit displayed traffic information and distributed management in air traffic control

A graphical display of information (such as surrounding aircraft and navigation routes) in the cockpit on a cathode ray tube has been proposed for improving the safety, orderliness, and expeditiousness of the air traffic control system. An investigation of this method at NASA-Ames indicated a large reduction in controller verbal work load without increasing pilot verbal load; the visual work may be increased. The cockpit displayed traffic and navigation information system reduced response delays permitting pilots to maintain their spacing more closely and precisely than when depending entirely on controller-issued radar vectors and speed command.

Kreifeldt, J. G.↗

A method for automatically abstracting visual documents

Visual documents - motion sequences on film, video-tape, and digital recordings - constitute a major source of information for the Space Agency, as well as all other government and private sector entities. This article describes a method for automatically selecting key frames from visual documents. These frames may in turn be used to represent the total image sequence of visual documents in visual libraries, hypermedia systems, and training guides. The performance of the abstracting algorithm reduces 51 minutes of video sequences to 134 frames; a reduction of information in the range of 700:1.

Rorvig, Mark E.↗

Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

CWAM↗

Topography from shading and stereo

Methods exploiting photometric information in images that have been developed in machine vision can be applied to planetary imagery. Present techniques, however, focus on one visual cue, such as shading or binocular stereo, and produce results that are either not very accurate in an absolute sense or provide information only at few points on the surface. We plan to integrate shape from shading, binocular stereo and photometric stereo to yield a robust system for recovering detailed surface shape and surface reflectance information. Such a system will be useful in producing quantitative information from the vast volume of imagery being received, as well as in helping visualize the underlying surface. The work will be carried out on a popular computing platform so that it will be easily accessible to other workers.

Horn, Berthold P.↗

Topography from shading and stereo

Methods exploiting photometric information in images that have been developed in machine vision can be applied to planetary imagery. Present techniques, however, focus on one visual cue, such as shading or binocular stereo, and produce results that are either not very accurate in an absolute sense or provide information only at few points on the surface. We plan to integrate shape from shading, binocular stereo and photometric stereo to yield a robust system for recovering detailed surface shape and surface reflectance information. Such a system will be useful in producing quantitative information from the vast volume of imagery being received, as well as in helping visualize the underlying surface. The work will be carried out on a popular computing platform so that it will be easily accessible to other workers.

Horn, Berthold P.↗

Virtual Environments in Scientific Visualization

Virtual environment technology is a new way of approaching the interface between computers and humans. Emphasizing display and user control that conforms to the user's natural ways of perceiving and thinking about space, virtual environment technologies enhance the ability to perceive and interact with computer generated graphic information. This enhancement potentially has a major effect on the field of scientific visualization. Current examples of this technology include the Virtual Windtunnel being developed at NASA Ames Research Center. Other major institutions such as the National Center for Supercomputing Applications and SRI International are also exploring this technology. This talk will be describe several implementations of virtual environments for use in scientific visualization. Examples include the visualization of unsteady fluid flows (the virtual windtunnel), the visualization of geodesics in curved spacetime, surface manipulation, and examples developed at various laboratories.

Bryson, Steve↗