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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Motion sickness and development of synergy within the spatial orientation system. A hypothetical unifying concept

Adaptation to research paradigms such as rotating rooms and optical alteration of visual feedback during movement results in development of perceptual-motor programs that provide the reflexive assistance that is necessary to skilled control of movement and balance. The discomfort and stomach awareness that occur during the adaptation process has been attributed to conflicting sensory information about the state of motion. Vestibular signals depend on the kinematics of head movements irrespective of the presence or absence of signals from other senses. We propose that sensory conflict when vestibular signals are at least one component of the conflict are innately disturbing and unpleasant. This innate reaction is part of a continuum that operates early in life to prevent development of inefficient perceptual-motor programs. This reaction operates irrespective of and in addition to reward and punishment from parental guidance or goal attainment to yield efficient control of whole body movement in the operating environment of the individual. The same mechanism is involved in adapting the spatial orientation system to strange environments. This conceptual model "explains" why motion sickness is associated with adaptation to novel environments and is in general consistent with motion sickness literature.

Review, Tutorial↗
NASA NTRSDate not supplied

Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)

The scientific community is faced with a need for greatly improved data sharing, analysis, visualization and advanced collaboration based firmly on open science principles. Recent and upcoming launches of new satellite missions with more complex and voluminous data, as well as the ever more urgent need to better understand the global carbon budget and related ecological processes, provided the immediate rational for the ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP). This highly collaborative joint project of ESA and NASA established a framework between ESA and NASA to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by ESA and NASA EO data users. Presented to the public in October 2021, the current version of MAAP provides a common cloud-based platform with computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of global above-ground biomass. Data from the Global Ecosystem Dynamics Investigation (GEDI) mission on the International Space Station and the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) have been instrumental in the first products of MAAP including the first comprehensive map of Boreal above-ground Biomass and a current Global Biomass Harmonization Activity, but the platform is also being specifically designed to support the forthcoming ESA Biomass mission and incorporate data from the upcoming NASA-ISRO SAR (NISAR) mission. While these missions and the corresponding research which includes airborne, field, and calibration/validation data collection and analyses, provide a wealth of data and information relating to global biomass estimation, they also present data storing, processing and sharing challenges. The NISAR mission alone will produce about 80TB/day. These large data volumes present a challenge that would otherwise place accessibility limits on the scientific community and impact scientific progress. Other challenges being addressed by MAAP include: 1) Enabling researchers to easily discover, process, visualize and analyze large volumes of data from both agencies; 2) Providing a wide variety of data in the same coordinate reference frame to enable comparison, analysis, data evaluation, and data generation; 3) Providing a version-controlled science algorithm development environment that supports tools, co-located data and processing resources; and 4) Addressing intellectual property and sharing challenges related to collaborative algorithm development and sharing of data and algorithms. MAAP products can be explored on the MAAP Dashboard at https://earthdata.nasa.gov/maap-biomass or the joint platform entrance at scimaap.net. MAAP also can be accessed through individual NASA (https://maap-project.org) and ESA (https://esa-maap.org/) landing pages.

cloud computing↗
NASA NTRS1982

Potential Role of Land Use and Land Cover Information in Powerplant Siting: Example of Three Mile Island

Selecting a site for a nuclear powerplant can be helped by digitizing land use and land cover data, population data, and other pertinent data sets, and then placing them in a geographic information system. Such a system begins with a set of standardized maps for location reference and then provides for retrieval and analysis of spatial data keyed to the maps. This makes possible thematic mapping by computer, or interactive visual display for decisionmaking. It also permits correlating land use area measurements with census and other data (such as fallout dosages), and the updating of all data sets. The system is thus a tool for dealing with resource management problems and for analyzing the interaction between people and their environment. An explanation of a computer-plotted map of land use and cover for Three Mile Island and vicinity is given.

Wray, J. R.↗
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 NTRS2010

SERVIR-Africa: Developing an Integrated Platform for Floods Disaster Management in Africa

SERVIR-Africa is an ambitious regional visualization and monitoring system that integrates remotely sensed data with predictive models and field-based data to monitor ecological processes and respond to natural disasters. It aims addressing societal benefits including floods and turning data into actionable information for decision-makers. Floods are exogenous disasters that affect many parts of Africa, probably second only to drought in terms of social-economic losses. This paper looks at SERVIR-Africa's approach to floods disaster management through establishment of an integrated platform, floods prediction models, post-event flood mapping and monitoring as well as flood maps dissemination in support of flood disaster management.

Macharia, Daniel↗
NASA NTRS2016

New Global Precipitation Products and Data Service Updates at the NASA GES DISC

This poster describes recent updates of the ongoing GPM data service activities at the NASA Goddard Earth Sciences (GES) Data and Information Services Center(DISC) to facilitate access and exploration of GPM, TRMM and other NASA precipitation datasets for the global community. The poster contains -Updates on GPM products and data services -New features in Giovanni for precipitation data visualization -Precipitation data and service outreach activities.

GPM↗
NASA NTRS2017

Exploratory Analysis of Carbon Dioxide Levels, Ultrasound and Optical Coherence Tomography Measures of the Eye During ISS Missions

Carbon dioxide (CO2) levels on board the International Space Station (ISS) have typically averaged 2.3 to 5.3 mmHg, with large fluctuations occurring over periods of hours and days. CO2 has effects on cerebral vascular tone, resulting in vasodilation and alteration of cerebral blood flow (CBF). Increased CBF leads to elevated intracranial pressure (ICP), a factor leading to visual disturbances, headaches, and other central nervous system symptoms. Ultrasound of the optic nerve and optical coherence tomography (OCT) provide surrogate measurements of ICP; in-flight measurements of both were implemented as enhanced screening tools for the Visual Impairment/Intracranial Pressure (VIIP) syndrome. This analysis examines the relationships between ambient CO2 levels on ISS, ultrasound and OCT measures of the eye in an effort to understand how CO2 may possibly be associated with VIIP and to inform future analysis of in-flight VIIP data.

Schaefer, C.↗
NASA NTRS2018

TCL2 National Campaign Human Factors Brief

The Technology Capability Level-2 National Campaign (TCL2nc) was conducted at six different test-sites located across the USA, during May and June of 2017. The campaign resulted in over 240 data collection flights using 24 different aircraft and involving 23 flight crews. Flights not only varied in duration, but also in the environments and terrains over which they flew. The TCL2nc highlighted beyond visual line of sight (BVLOS) and altitude-stratified operations, and saw five partners bring their own, independently built, UAS Service Supplier (USS) for use during the flight tests. This document presents data collected during the TCL2nc that informs the 'Operator' section of the 'Requirements/Best Practices' from the UTM Technical Capability Matrix and Guidelines to Operate (Rios, version as of March 2017). A review of the data collected indicated that although teams were well qualified on paper (in terms of both completing training and having experience with flying UAS vehicles), greater consideration should be given to the unique perspectives and backgrounds of future UAS operators. Overall, teams looked at a variety of sources for information, including USS client-displays, and participants became more mindful of the need to be aware of other vehicles, highlighting the value of reporting information. Observations found that flight crews' time to respond to a UTM issue depended heavily on the team structure, communication efficiency, and crew procedures. These points are discussed in more detail below.

unmanned vehicles↗
NASA NTRS2018

Serving NASA GES DISC Multi-Spatiotemporal Earth Science Data to the GIS community

NASA Earth Science (ES) data is essential to a wide range of GIS research and applications. However, for many GIS users, searching, accessing, using and analyzing NASA ES data can be of a great challenge- ranging from the sheer data volumes, types of science parameters, and to the complexity of data encoding formats. As one of the twelve NASA Science Mission Directorate (SMD) Data Centers, Goddard Earth Sciences (GES) Data and Information Services Center (DISC) archives and distributes petabytes of ES parameters covering atmosphere, land, and ocean fields. Most data are multidimensional and multi-spatiotemporal in nature and are encoded in different science data formats (e.g, HDF, HDF-EOS, netCDF, GRIB, binary), which usually contain multiple variables and different metadata information. By far, GES DISC has been developing a number of services and online tools to help GIS users to easily explore our data products. In this presentation, we will describe our ArcGIS-based data accessing and visualization services and portals, which allow users directly exploring the multi-spatiotemporal ES data in ArcGIS clients without having to pre-download/import the data. The ArcGIS services are also compliant with the Open Geospatial Consortium (OGC) Web Coverage Service (WCS) and Web Map Service (WMS) protocols and can be accessed by any other WCS/WMS clients to get customized GES DISC EO data on-the-fly from such services.

Wei, Jennifer↗
NASA NTRS2017

NASA's UTM Research

The Technology Capability Level-2 National Campaign (TCL2nc) was conducted at six different test sites located across the USA, during May and June of 2017. The campaign resulted in over 250 data collection flights using 26 different aircraft and involving 23 flight crews. Flights not only varied in duration, but also in the environments and terrains over which they flew. The TCL2nc highlighted beyond visual line of sight (BVLOS) and altitude-stratified operations, and saw five partners bring their own, independently built, UTM Service Supplier (USS) for use during the flight tests. This document presents data collected during the TCL2nc that informs the 'Operator' section of the 'Requirements/Best Practices' from the UTM Technical Capability Matrix and Guidelines to Operate (Rios, version as of March 2017). A review of the data collected indicated that although teams were well qualified on paper (in terms of both completing training and having experience with flying UAS vehicles), greater consideration should be given to the unique perspectives and backgrounds of future UAS operators. Overall, teams looked at a variety of sources for information, including USS client-displays, and participants became more aware of the need to be aware of other vehicles, highlighting the value of reporting information. Observations found that flight crews' time to respond to a UTM issue depended heavily on the team structure, communication efficiency, and crew procedures.

Mercer, Joey↗
NASA NTRS2019

Using GES DISC Data to Study Kilauea Volcano of 2018

Kilauea volcano in Hawaii which erupted in early May 2018 injected massive amount of SO2 and ash into the atmosphere. The lava flow during the eruption destroyed many home and neighborhoods. The SO2 plume during the eruption of Kilauea volcano is analyzed from May to August 2018 using multiple satellite products such as Level 2 TROPspheric Monitoring Instrument (TROPOMI) and Level 3 Ozone Monitoring Instrument (OMI) from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). GES DISC hosts multi-disciplinary Earth science data sets that can be used to analyze natural disasters, such as the Kilauea volcano. Additionally, GES DISC's Giovanni tool can be used to visualize these data. We acquired OMI through the subsetting function, which is processed by the GES DISC in-house developed backend software Level3/4 Regrider and Subsetter (L34RS) and TROPOMI using OPeNDAP.Data from the OMI OMSO2e product showed elevated levels of SO2 amounts during the eruption between May to August 2018. Similarly, ground-based stations at Hawaii Volcanoes National Park recorded higher SO2 concentrations during the same time period. This study uses wind direction from Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) to analyze the transport and dispersion of SO2 plume and map lava flows from the volcano using thermal images from Visible Infrared Imaging Radiometer Suite (VIIRS). Furthermore, satellite observations combined with socioeconomic and public health data are used to analyze its impact in public health.

KC, Binita↗
NASA NTRSDate not supplied

Data Assimilation and Reanalysis

This presentation introduces the Data Assimilation and Reanalysis principle, then details the NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2). The MERRA-2 is atmospheric reanalysis data spanning 1980 to the present. It has been produced by the NASA Global Modeling and Assimilation Office (GMAO) and is distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). In this presentation, I will introduce the MERRA-2 datasets associated with aerosol and air quality studies and use case studies to demonstrate the data tools developed at GES DISC to analyze and visualize MERRA-2 data, such as Giovanni and Jupyter Python notebook.

Xiaohua Pan↗
NASA NTRS2004

Perceptual learning through optimization of attentional weighting: human versus optimal Bayesian learner

Human performance in visual detection, discrimination, identification, and search tasks typically improves with practice. Psychophysical studies suggest that perceptual learning is mediated by an enhancement in the coding of the signal, and physiological studies suggest that it might be related to the plasticity in the weighting or selection of sensory units coding task relevant information (learning through attention optimization). We propose an experimental paradigm (optimal perceptual learning paradigm) to systematically study the dynamics of perceptual learning in humans by allowing comparisons to that of an optimal Bayesian algorithm and a number of suboptimal learning models. We measured improvement in human localization (eight-alternative forced-choice with feedback) performance of a target randomly sampled from four elongated Gaussian targets with different orientations and polarities and kept as a target for a block of four trials. The results suggest that the human perceptual learning can occur within a lapse of four trials (<1 min) but that human learning is slower and incomplete with respect to the optimal algorithm (23.3% reduction in human efficiency from the 1st-to-4th learning trials). The greatest improvement in human performance, occurring from the 1st-to-2nd learning trial, was also present in the optimal observer, and, thus reflects a property inherent to the visual task and not a property particular to the human perceptual learning mechanism. One notable source of human inefficiency is that, unlike the ideal observer, human learning relies more heavily on previous decisions than on the provided feedback, resulting in no human learning on trials following a previous incorrect localization decision. Finally, the proposed theory and paradigm provide a flexible framework for future studies to evaluate the optimality of human learning of other visual cues and/or sensory modalities.

Non-NASA Center↗
NASA NTRS2000

Development and Implementation of Real-Time Information Delivery Systems for Emergency Management

The disaster management community has an on-going need for real-time data and information, especially during catastrophic events. Currently, twin engine or jet aircraft with limited altitude and duration capabilities collect much of the data. Flight safety is also an issue. Clearly, much of the needed data could be delivered via over-the-horizon transfer through a uninhabited aerial vehicles (UAV) platform to mission managers at various locations on the ground. In fact, because of the ability to stay aloft for long periods of time, and to fly above dangerous situations, UAV's are ideally suited for disaster missions. There are numerous situations that can be considered disastrous for the human population. Some, such as fire or flood, can continue over a period of days. Disaster management officials rely on data from the site to respond in an optimum way with warnings, evacuations, rescue, relief, and to the extent possible, damage control. Although different types of disasters call for different types of response, most situations can be improved by having visual images and other remotely sensed data available. "Disaster Management" is actually made up of a number of activities, including: - Disaster Prevention and Mitigation - Emergency Response Planning - Disaster Management (real-time deployment of resources, during an event) - Disaster / Risk Modeling All of these activities could benefit from real-time information, but a major focus for UAV-based technology is in real-time deployment of resources (i.e., emergency response teams), based on changing conditions at the location of the event. With all these potential benefits, it is desirable to demonstrate to user agencies the ability to perform disaster management missions as described. The following demonstration project is the first in a program designed to prove the feasibility of supporting disaster missions with UAV technology and suitable communications packages on-board. A several-year program is envisioned, in which a broad range of disaster-related activities are demonstrated to the appropriate user communities.

Wegener, Steve↗
NASA NTRS1997

In-Flight Flow Visualization Using Infrared Thermography

The feasibility of remote infrared thermography of aircraft surfaces during flight to visualize the extent of laminar flow on a target aircraft has been examined. In general, it was determined that such thermograms can be taken successfully using an existing airplane/thermography system (NASA Dryden's F-18 with infrared imaging pod) and that the transition pattern and, thus, the extent of laminar flow can be extracted from these thermograms. Depending on the in-flight distance between the F-18 and the target aircraft, the thermograms can have a spatial resolution of as little as 0.1 inches. The field of view provided by the present remote system is superior to that of prior stationary infrared thermography systems mounted in the fuselage or vertical tail of a subject aircraft. An additional advantage of the present experimental technique is that the target aircraft requires no or minimal modifications. An image processing procedure was developed which improves the signal-to-noise ratio of the thermograms. Problems encountered during the analog recording of the thermograms (banding of video images) made it impossible to evaluate the adequacy of the present imaging system and image processing procedure to detect transition on untreated metal surfaces. The high reflectance, high thermal difussivity, and low emittance of metal surfaces tend to degrade the images to an extent that it is very difficult to extract transition information from them. The application of a thin (0.005 inches) self-adhesive insulating film to the surface is shown to solve this problem satisfactorily. In addition to the problem of infrared based transition detection on untreated metal surfaces, future flight tests will also concentrate on the visualization of other flow phenomena such as flow separation and reattachment.

vanDam, C. P.↗
NASA NTRS1974

Skylab 4 visual observations project report

The Skylab 4 Visual Observations Project was undertaken to determine the ways in which man can contribute to future earth-orbital observational programs. The premission training consisted of 17 hours of lectures by scientists representing 16 disciplines and provided the crewmen information on observational and photographic procedures and the scientific significance of this information. During the Skylab 4 mission, more than 850 observations and 2000 photographs with the 70-millimeter Hasselblad and 35-millimeter Nikon cameras were obtained for many investigative areas. Preliminary results of the project indicate that man can obtain new and unique information to support satellite earth-survey programs because of his inherent capability to make selective observations, to integrate the information, and to record the data by describing and photographing the observational sites.

Kaltenbach, J. L.↗
NASA NTRS1981

1548C27 - An interesting new cometary nebula

The object 1548C27, a faint cometary nebula of classical form, discovered by an examination of early Near Infrared Photographic Sky Survey (NIPSS) data (1979) is presented. Direct imaging and polarimetric, photometric, and spectroscopic observations are reported. Early survey test photographs show that the object lies at R.A. 19h40m48s, Decl. +23 deg 17 arcmin 09 arc sec (1950) in the Vulpecula constellation in the immediate vicinity of the complex H II region and galactic cluster NGC 6820/6823. From the photographs, the nebula was estimated to be 15 m visual and of color class one. The object was observed spectroscopically in the region 5700-6800 A using an Image Dissector Scanner with a 1.8 m reflector, and the spectral scan, obtained on November 4, 1978, is presented. New information on cometary nebulae may further illuminate the evolutionary importance of the objects.

Craine, E. R.↗