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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Identification of Sea Surface Temperature and Sea Surface Salinity Fronts along the California Coast: Application Using Saildrone and Satellite Derived Products

Coastal upwelling regions are one of the most dynamic areas of the world’s oceans. The California and Baja California Coasts are impacted by both coastal upwelling and the California Current, leading to frontal activity that is captured by gradients in both Sea Surface Temperature (SST) and Sea Surface Salinity (SSS). Satellite data are a great source of spatial data to study fronts. However, biases near coastal areas and coarse resolutions can impair its usefulness in upwelling areas. In this work gradients in SST from NASA Multi-Scale Ultra-High Resolution (MUR) and in two SSS products derived from the Soil Moisture Active Passive (SMAP) NASA mission are compared directly with gradients derived from the Saildrone uncrewed vehicles to validate the gradients as well as to assess their ability to detect known frontal features. The three remotely sensed data sets (MURSST/JPL, SMAP SSS/RSS, SMAP SSS) were co-located with the Saildrone data prior to the calculation of the gradients. Wavelet analysis is used to determine how well the satellite derived SST and SSS products are reproducing the Saildrone derived gradients. Overall results indicate the remote sensing products are reproducing features of known areas of coastal upwelling. Differences between the SST and SSS gradients are mainly associated with the limitations of the microwave derived SSS coverage near land and its reduced spatial resolution. The results are promising for using remote sensing data sets to monitor frontal structure along the California Coast and the application to long term changes in coastal upwelling and dynamics.

Sea Surface Salinity↗
NASA NTRSDate not supplied

Deriving Essential Climate Variable Data from Multiple Satellite Remote Sensors Using a Consistent Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms can lead to errors in the climate products when fusing data from different satellite sensors. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) data and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Aerosol and Cloud, Convection and Precipitation (ACCP).

Xu Liu↗
NASA NTRS2007

Geo-STAR: A Geostationary Microwave Sounder for the Future

The Geostationary Synthetic Thinned Aperture Radiometer (GeoSTAR) is a new Earth remote sensing instrument concept that has been under development at the Jet Propulsion Laboratory. First conceived in 1998 as a NASA New Millennium Program mission and subsequently developed in 2003-2006 as a proof-of-concept prototype under the NASA Instrument Incubator Program, it is intended to fill a serious gap in our Earth remote sensing capabilities - namely the lack of a microwave atmospheric sounder in geostationary orbit. The importance of such observations have been recognized by the National Academy of Sciences National Research Council, which recently released its report on a 'Decadal Survey' of NASA Earth Science activities1. One of the recommended missions for the next decade is a geostationary microwave sounder. GeoSTAR is well positioned to meet the requirements of such a mission, and because of the substantial investment NASA has already made in GeoSTAR technology development, this concept is fast approaching the necessary maturity for implementation in the next decade. NOAA is also keenly interested in GeoSTAR as a potential payload on its next series of geostationary weather satellites, the GOES-R series. GeoSTAR, with its ability to map out the three-dimensional structure of temperature, water vapor, clouds, precipitation and convective parameters on a continual basis, will significantly enhance our ability to observe hurricanes and other severe storms. In addition, with performance matching that of current and next generation of low-earth-orbiting microwave sounders, GeoSTAR will also provide observations important to the study of the hydrologic cycle, atmospheric processes and climate variability and trends. In particular, with GeoSTAR it will be possible to fully resolve the diurnal cycle. We discuss the GeoSTAR concept and basic design, the performance of the prototype, and a number of science applications that will be possible with GeoSTAR. The work reported on here was performed at the Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration.

Geostationary Synthetic Thinned Aperture Radiomete↗
NASA NTRS1978

Manned simulations of the SRMS in SIMFAC

SIMFAC is a general purpose real-time simulation facility currently configured with an Orbiter-like Crew Compartment and a Displays and Controls (D and C) Subsystem to support the engineering developments of the Space Shuttle Remote Manipulator (SRMS). The simulation consists of a software model of the anthropomorphic SRMS manipulator arm including the characteristics of its control system and joint drive modules. The following are discussed: (1) simulation and scene generation subsystems; (2) the SRMS task in SIMFAC; (3) operator tactics and options; (4) workload; (5) operator errors and sources; (6) areas for further work; and (7) general observations.

Lippay, A. L.↗
NASA NTRS1995

Estimating Slopes In Images Of Terrain By Use Of BRDF

Proposed method of estimating slopes of terrain features based on use of bidirectional reflectivity distribution function (BRDF) in analyzing aerial photographs, satellite video images, or other images produced by remote sensors. Estimated slopes integrated along horizontal coordinates to obtain estimated heights; generating three-dimensional terrain maps. Method does not require coregistration of terrain features in pairs of images acquired from slightly different perspectives nor requires Sun or other source of illumination to be low in sky over terrain of interest. On contrary, best when Sun is high. Works at almost all combinations of illumination and viewing angles.

Scholl, Marija S.↗
NASA NTRS2000

ACTS Satellite Telemammography Network Experiments

The Satellite Networks and Architectures Branch of NASA's Glenn Research Center has developed and demonstrated several advanced satellite communications technologies through the Advanced Communications Technology Satellite (ACTS) program. One of these technologies is the implementation of a Satellite Telemammography Network (STN) encompassing NASA Glenn, the Cleveland Clinic Foundation. the University of Virginia, and the Ashtabula County Medical Center. This paper will present a look at the STN from its beginnings to the impact it may have on future telemedicine applications. Results obtained using the experimental ACTS satellite demonstrate the feasibility of Satellite Telemammography. These results have improved teleradiology processes and mammography image manipulation, and enabled advances in remote screening methodologies. Future implementation of satellite telemammography using next generation commercial satellite networks will be explored. In addition, the technical aspects of the project will be discussed, in particular how the project has evolved from using NASA developed hardware and software to commercial off the shelf (COTS) products. Development of asymmetrical link technologies was an outcome of this work. Improvements in the display of digital mammographic images, better understanding of end-to-end system requirements, and advances in radiological image compression were achieved as a result of the research. Finally, rigorous clinical medical studies are required for new technologies such as digital satellite telemammography to gain acceptance in the medical establishment. These experiments produced data that were useful in two key medical studies that addressed the diagnostic accuracy of compressed satellite transmitted digital mammography images. The results of these studies will also be discussed.

Kachmar, Brian A.↗
NASA NTRS2000

The Dynamics of a Semi-Arid Region in Response to Climate and Water - Use Policy

The objectives of this project were to determine the response of semi-arid ecosystems to the combined forcings of climate variability and anthropogenic stress. Arid and semi-arid systems encompass close to 40% of the worlds land surface. The ecology of these regions are principally limited by water, and as the water resources wax and wane, so should the health and vigor of the ecosystems. Water, however, is a necessary and critical resource for humans living in these same regions. Thus for many and and semi-arid regions the natural systems and human systems are in direct competition for a limited resource. Increasing competition through development of and and semi-arid regions, export of water resources, as well as potential persistent changes in weather patterns are likely to lead to fundamental changes in carrying capacity, resilience, and ecology of these regions. A detailed understanding of these systems respond to forcing on a regional and local scale is required in order to better prepare for and manage future changes in the availability of water. In the Owens Valley CA, decadal changes in rainfall and increased use of groundwater resources by Los Angles (which derives 60-70% of its water from this region) have resulted in a large-scale experiment on the impacts of these changes in semi-arid ecosystems. This project works directly with the Inyo County Water Department (local water authority) and the Los Angles Department of Water and Power (regional demand on water resources) to understand changes, their causes, and impacts. Very detailed records have been kept for a number of selected sites in the valley which provide essential ground truth. These results are then scaled up through remote sensed data to regions scale to assess large scale patterns and link them to the fundamental decisions regarding the water resources of this region. A fundamental goal is to understand how resilient the native ecosystems are to large changes in water resources. Are they are on a spring (remove and return resources, do the systems return to the original state) or a vector (when water returns have the systems fundamentally changed).

Mustard, John F.↗
NASA NTRS2018

Automated Pneumothorax Diagnosis using Deep Neural Networks

Thoracic ultrasound can provide information leading to rapid diagnosis of pneumothorax with improved accuracy over the standard physical examination and with higher sensitivity than anteroposterior chest radiography. However, the clinical We have Furthermore, remote environments, such as the battlefield or deep-space exploration, may lack expertise for diagnosing developed an automated image interpretation pipeline for the analysis of thoracic ultrasound data and the classification of pneumothorax events to provide decision support in such situations. Our pipeline consists of image preprocessing, data augmentation, and deep learning architectures for medical diagnosis. In this work, we demonstrate that robust, accurate interpretation of chest images and video can be achieved using deep neural networks. A number of novel image processing techniques were employed to achieve this result. Affine transformations were applied for data augmentation. Hyperparameters were optimized for learning rate, dropout regularization, batch size, and epoch iteration by a sequential model-based Bayesian approach. In addition, we utilized pretrained architecturesinterpretation of a patient medical image is highly operator dependent. certain pathologies., applying transfer learning and fine-tuning techniques to fully connected layers. Our pipeline yielded binary classification validation accuracies of 98.3% for M-mode images and 99.8% with B-mode video frames.

US Army collaboration↗
NASA NTRS2019

Development of Pericyclic Gearbox for Roving Application

Many aerospace mechanisms require high gear reduction ratios to reduce the high output speed of a motor to much lower speeds for precision rotation. Conventionally this actuation is performed with multiple gear stages, typically including a harmonic gearbox, and is required to be lightweight for spaceflight. One application of multiple gear stages is in rover wheel actuators intended for use on the Moon and Mars. These actuators require low total mass, high reliability, and precision actuation due to their remote operation. The pericyclic gearbox has the capability in a single stage to provide high reduction ratios equivalent to multiple conventional stages. Some benefits of utilizing pericyclic gear technology over multiple conventional stages are a compact form, fewer total parts, no reliance on flexible members (such as in harmonic drives), and lower total system mass. The goal of this work was to modify and build on existing modeling tools to determine the feasibility of utilizing the pericyclic gearbox for such an application. Critical aspects to consider were gear tooth loads, gear mesh efficiency, bearing loads, bearing efficiency, and total system mass. Developed tools were then used to examine a single stage pericyclic gearbox's trends in mass and efficiency for a Mars 2020 rover wheel actuator mechanism design case which was then compared to multistage gearbox designs.

Krantz, Timothy↗
NASA NTRS2016

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters : Aerosols - Part 2

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

aerosol retrieval↗
NASA NTRS2018

Human-Automation Allocations for Current Robotic Space Operations

Within the Human Research Program, one risk delineates the uncertainty surrounding crew working with automation and robotics in spaceflight. The Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is concerned with the detrimental effects on crew performance due to ineffective user interfaces, system designs and/or functional task allocation, potentially compromising mission success and safety. Risk arises because we have limited experience with complex automation and robotics. One key gap within HARI, is the gap related to functional allocation. The gap states: We need to evaluate, develop, and validate methods and guidelines for identifying human-automation/robot task information needs, function allocation, and team composition for future long duration, long distance space missions. Allocations determine the human-system performance as it identifies the functions and performance levels required by the automation/robotic system, and in turn, what work the crew is expected to perform and the necessary human performance requirements. Allocations must take into account each of the human, automation, and robotic systems capabilities and limitations. Some functions may be intuitively assigned to the human versus the robot, but to optimize efficiency and effectiveness, purposeful role assignments will be required. The role of automation and robotics will significantly change in future exploration missions, particularly as crew becomes more autonomous from ground controllers. Thus, we must understand the suitability of existing function allocation methods within NASA as well as the existing allocations established by the few robotic systems that are operational in spaceflight. In order to evaluate future methods of robotic allocations, we must first benchmark the allocations and allocation methods that have been used. We will present 1) documentation of human-automation-robotic allocations in existing, operational spaceflight systems; and 2) To gather existing lessons learned and best practices in these role assignments, from spaceflight operational experience of crew and ground teams that may be used to guide development for future systems. NASA and other space agencies have operational spaceflight experience with two key Human-Automation-Robotic (HAR) systems: heavy lift robotic arms and planetary robotic explorers. Additionally, NASA has invested in high-fidelity rover systems that can carry crew, building beyond Apollo's lunar rover. The heavy lift robotic arms reviewed are: Space Station Remote Manipulator System (SSRMS), Japanese Remote Manipulator System (JEMRMS), and the European Robotic Arm (ERA, designed but not deployed in space). The robotic rover systems reviewed are: Mars Exploration Rovers, Mars Science Laboratory rover, and the high-fidelity K10 rovers. Much of the design and operational feedback for these systems have been communicated to flight controllers and robotic design teams. As part of the mitigating the HARI risk for future human spaceflight operations, we must document function allocations between robots and humans that have worked well in practice.

robotic allocation↗
NASA NTRS2005

Space-based Remote Sensing: A Tool for Studying Bird Migration Across Multiple Scales

The study of bird migration on a global scale is one of the compelling and challenging problems of modern biology with major implications for human health and conservation biology. Migration and conservation efforts cross national boundaries and are subject to numerous international agreements and treaties. Space based technology offers new opportunities to shed understanding on the distribution and migration of organisms on the planet and their sensitivity to human disturbances and environmental changes. Our working hypothesis is that individual organism biophysical models of energy and water balance, driven by satellite measurements of spatio-temporal gradients in climate and habitat, will help us to explain the variability in avian species richness and distribution. Further, these models provide an ecological forecasting tool for science and application users to visualize the possible consequences of loss of wetlands, flooding, or other natural disasters such as hurricanes on avian biodiversity and bird migration.

Smith, James A.↗
NASA NTRSDate not supplied

Generating Essential Climate Variables from Multiple Satellite Hyperspectral Remote Sensors

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. There are two shortcomings of this approach. First, it is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Secondly, differences in level-2 retrieval algorithms can lead to errors in the fused multi-satellite data. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to data collected from Atmospheric Infrared Sounder (AIRS) on Aqua satellite and Cross-track Infrared Sounder (CrIS) on SNPP and NOAA20 and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Atmosphere Observing System (AOS).

Xu Liu↗
NASA NTRS2000

Video Based Sensor for Tracking 3-Dimensional Targets

Video-Based Sensor for Tracking 3-Dimensional Targets The National Aeronautics and Space Administration's (NASAs) Marshall Space Flight Center (MSFC) has been developing and testing video-based sensors for automated spacecraft guidance for several years, and the next generation of video sensor will have tracking rates up to 100 Hz and will be able to track multiple reflectors and targets. The Video Guidance Sensor (VGS) developed over the past several years has performed well in testing and met the objective of being used as the terminal guidance sensor for an automated rendezvous and capture system. The first VGS was successfully tested in closed-loop 3-degree-of-freedom (3- DOF) tests in 1989 and then in 6-DOF open-loop tests in 1992 and closed-loop tests in 1993-4. Development and testing continued, and in 1995 approval was given to test the VGS in an experiment on the Space Shuttle. The VGS flew in 1997 and in 1998, performing well for both flights. During the development and testing before, during, and after the flight experiments, numerous areas for improvement were found. The VGS was developed with a sensor head and an electronics box, connected by cables. The VGS was used in conjunction with a target that had wavelength-filtered retro-reflectors in a specific pattern, The sensor head contained the laser diodes, video camera, and heaters and coolers. The electronics box contained a frame grabber, image processor, the electronics to control the components in the sensor head, the communications electronics, and the power supply. The system works by sequentially firing two different wavelengths of laser diodes at the target and processing the two images. Since the target only reflects one wavelength, it shows up well in one image and not at all in the other. Because the target's dimensions are known, the relative positions and attitudes of the target and the sensor can be computed from the spots reflected from the target. The system was designed to work from I meter out to I 10 meters. The VGS was mounted on the Space Shuttle while its target was mounted on the Spartan free-flyer carried on the same Shuttle flight. The VGS tracked the Spartan at ranges up to 170m, and the VGS range data very closely matched the range data from the Hand-Held Laser- Rangefinder used by the astronauts on board the Shuttle. While the VGS was designed primarily as a terminal guidance sensor for an automated spacecraft, it could be applied to other uses. It could be used as an alignment aid for an operator of a remote system (giving position and attitude feedback data, as well as a camera view of the target), as a feedback system for a robotic arm, or for automated vehicle guidance. The next generation VGS, with its higher tracking rates, smaller size, and lower power could be used in more places than the original VGS, and by using LED's instead of laser diodes, the system would be eye-safe at any range. Other possible uses include tracking 3-dimensional objects with retro-reflectors mounted at various locations or motion analysis by placing several retro-reflectors on the moving object and tracking them at high speeds. There are few sensors capable of performing tasks similar to those the VGS can perform, and the next generation VGS will be even more capable than the original. Some of this work is previously presented in the papers.

Howard, R. T.↗
NASA NTRS1987

Spectrometric test of a linear array sensor

A spectroradiometer which measures spectral reflectivities and irradiance in discrete spectral channels was tested to determine the accuracy of its wavelength calibration. This sensor is a primary tool in the remote sensing investigations conducted on biomass at NASA's Goddard Space Flight Center. Measurements have been collected on crop and forest plants both in the laboratory and field with this radiometer to develop crop identification and plant stress remote sensing techniques. Wavelength calibration is essential for use in referencing the study measurements with those of other investigations and satellite remote sensor data sets. This calibration determines a wavelength vs channel address conversion which was found to have an RMS deviation of approximately half a channel, or 1.5 nm in the range from 360 to 1050 nm. A comparison of these results with those of another test showed an average difference of approximately 4 nm, sufficiently accurate for most investigative work.

Brown, Kenneth S.↗
NASA NTRS1992

AVIRIS study of Death Valley evaporite deposits using least-squares band-fitting methods

Minerals found in playa evaporite deposits reflect the chemically diverse origins of ground waters in arid regions. Recently, it was discovered that many playa minerals exhibit diagnostic visible and near-infrared (0.4-2.5 micron) absorption bands that provide a remote sensing basis for observing important compositional details of desert ground water systems. The study of such systems is relevant to understanding solute acquisition, transport, and fractionation processes that are active in the subsurface. Observations of playa evaporites may also be useful for monitoring the hydrologic response of desert basins to changing climatic conditions on regional and global scales. Ongoing work using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to map evaporite minerals in the Death Valley salt pan is described. The AVIRIS data point to differences in inflow water chemistry in different parts of the Death Valley playa system and have led to the discovery of at least two new North American mineral occurrences. Seven segments of AVIRIS data were acquired over Death Valley on 31 July 1990, and were calibrated to reflectance by using the spectrum of a uniform area of alluvium near the salt pan. The calibrated data were subsequently analyzed by using least-squares spectral band-fitting methods, first described by Clark and others. In the band-fitting procedure, AVIRIS spectra are fit compared over selected wavelength intervals to a series of library reference spectra. Output images showing the degree of fit, band depth, and fit times the band depth are generated for each reference spectrum. The reference spectra used in the study included laboratory data for 35 pure evaporite spectra extracted from the AVIRIS image cube. Additional details of the band-fitting technique are provided by Clark and others elsewhere in this volume.

Crowley, J. K.↗
NASA NTRS1992

Using high-performance networks to enable computational aerosciences applications

One component of the U.S. Federal High Performance Computing and Communications Program (HPCCP) is the establishment of a gigabit network to provide a communications infrastructure for researchers across the nation. This gigabit network will provide new services and capabilities, in addition to increased bandwidth, to enable future applications. An understanding of these applications is necessary to guide the development of the gigabit network and other high-performance networks of the future. In this paper we focus on computational aerosciences applications run remotely using the Numerical Aerodynamic Simulation (NAS) facility located at NASA Ames Research Center. We characterize these applications in terms of network-related parameters and relate user experiences that reveal limitations imposed by the current wide-area networking infrastructure. Then we investigate how the development of a nationwide gigabit network would enable users of the NAS facility to work in new, more productive ways.

Johnson, Marjory J.↗
NASA NTRS1996

Color Image Processing and Object Tracking System

This report describes a personal computer based system for automatic and semiautomatic tracking of objects on film or video tape, developed to meet the needs of the Microgravity Combustion and Fluids Science Research Programs at the NASA Lewis Research Center. The system consists of individual hardware components working under computer control to achieve a high degree of automation. The most important hardware components include 16-mm and 35-mm film transports, a high resolution digital camera mounted on a x-y-z micro-positioning stage, an S-VHS tapedeck, an Hi8 tapedeck, video laserdisk, and a framegrabber. All of the image input devices are remotely controlled by a computer. Software was developed to integrate the overall operation of the system including device frame incrementation, grabbing of image frames, image processing of the object's neighborhood, locating the position of the object being tracked, and storing the coordinates in a file. This process is performed repeatedly until the last frame is reached. Several different tracking methods are supported. To illustrate the process, two representative applications of the system are described. These applications represent typical uses of the system and include tracking the propagation of a flame front and tracking the movement of a liquid-gas interface with extremely poor visibility.

Klimek, Robert B.↗