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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1992

Volcanic thermal features observed by AVIRIS

In July 1991, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) was flown over Mount Etna and Stromboli, Italy. Lava-filled vents were then present within summit craters of both volcanoes. Since surfaces at magmatic temperatures radiate strongly over the wavelength ranges of the AVIRIS C- and D-spectrometers, it was hoped that the data collected would reveal clear thermal signatures, even of sub-pixel sized features, as have been observed in the 1.65 and 2.22 microns bands of Landsat Thematic Mapper images. This would provide an opportunity to explore the potential of imaging spectrometers for deriving temperature distributions of hot volcanic surfaces. Such research has implications for volcano monitoring in the EOS era, and also for any future AVIRIS deployments above active lava flows, lakes, and domes, where understanding of their behavior may be advanced by detailed thermal observations.

Oppenheimer, Clive↗
NASA NTRS1994

COSMIC monthly progress report

Activities of the Computer Software Management and Information Center (COSMIC) are summarized for the month of May 1994. Tables showing the current inventory of programs available from COSMIC are presented and program processing and evaluation activities are summarized. Nine articles were prepared for publication in the NASA Tech Brief Journal. These articles (included in this report) describe the following software items: (1) WFI - Windowing System for Test and Simulation; (2) HZETRN - A Free Space Radiation Transport and Shielding Program; (3) COMGEN-BEM - Composite Model Generation-Boundary Element Method; (4) IDDS - Interactive Data Display System; (5) CET93/PC - Chemical Equilibrium with Transport Properties, 1993; (6) SDVIC - Sub-pixel Digital Video Image Correlation; (7) TRASYS - Thermal Radiation Analyzer System (HP9000 Series 700/800 Version without NASADIG); (8) NASADIG - NASA Device Independent Graphics Library, Version 6.0 (VAX VMS Version); and (9) NASADIG - NASA Device Independent Graphics Library, Version 6.0 (UNIX Version). Activities in the areas of marketing, customer service, benefits identification, maintenance and support, and dissemination are also described along with a budget summary.

Source record↗
NASA NTRS1998

Sarnoff JND Vision Model for Flat-Panel Design

This document describes adaptation of the basic Sarnoff JND Vision Model created in response to the NASA/ARPA need for a general-purpose model to predict the perceived image quality attained by flat-panel displays. The JND model predicts the perceptual ratings that humans will assign to a degraded color-image sequence relative to its nondegraded counterpart. Substantial flexibility is incorporated into this version of the model so it may be used to model displays at the sub-pixel and sub-frame level. To model a display (e.g., an LCD), the input-image data can be sampled at many times the pixel resolution and at many times the digital frame rate. The first stage of the model downsamples each sequence in time and in space to physiologically reasonable rates, but with minimum interpolative artifacts and aliasing. Luma and chroma parts of the model generate (through multi-resolution pyramid representation) a map of differences-between test and reference called the JND map, from which a summary rating predictor is derived. The latest model extensions have done well in calibration against psychophysical data and against image-rating data given a CRT-based front-end. THe software was delivered to NASA Ames and is being integrated with LCD display models at that facility,

Brill, Michael H.↗
NASA NTRS1996

Subpixel Snow-Covered-Area and Snow Grain Size From Mixture Analysis with AVIRIS Data

Snow-covered-area (SCA) and snow grain size are crucial inputs to hydrologic and climatologic modeling of alpine and other seasonally snow-covered regions. SCA is necessary to parameterize energy budget calculations in climate models, to determine in which regions point snowmelt models are to be run for distributed snowmelt modeling efforts and to provide a basis from which estimates of snow water equivalent (SWE) may be made. Snow grain size, SWE and snow impurities determine the spectral albedo of snow, which controls the net solar flux at the snowpack surface. Snow albedo is of the utmost importance in snowmelt modeling, yet the difficulty with which grain size, SWE, and impurities are mapped has left the spatial distribution of snow albedo in alpine catchments poorly understood. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been used to estimate sub-pixel snow-covered-area and snow grain size independently. In this paper we present a technique which improves estimates of both snow parameters by treating their mapping simultaneously.

Green Robert O.↗
NASA NTRS1997

Recovery of motion parameters from distortions in scanned images

Scanned images, such as those produced by the scanning-laser ophthalmoscope (SLO), show distortions when there is target motion. This is because pixels corresponding to different image regions are acquired sequentially, and so, in essence, are slices of different snapshots. While these distortions create problems for image registration algorithms, they are potentially useful for recovering target motion parameters at temporal frequencies above the frame rate. Stetter, Sendtner and Timberlake measured large distortions in SLO images to recover the time course of rapid horizontal saccadic eye movements. Here, this work is extended with the goal of automatically recovering small eye movements in two dimensions. Eye position during the frame interval is modeled using a low dimensional parametric description, which in turn is used to generate predicted distortions of a reference template. The input image is then registered to the distorted template using normalized cross correlation. The motion parameters are then varied, and the correlation recomputed, to find the motion which maximizes the peak value of the correlation. The location and value of the correlation maximum are determined with sub-pixel precision using biquadratic interpolation, yielding eye position resolution better than 1 arc minute. This method of motion parameter estimation is tested using actual SLO images as well as simulated images. Motion parameter estimation might also be applied to individual video lines in order to reduce pipeline delays for a near real-time system.

Mulligan, Jeffrey B.↗
NASA NTRS1998

Estimates of Spectral UV Irradiance from Earth Probe TOMS: Comparisons with Ground-Based Measurements

Estimates of the spectral UV flux incident on the Earth's surface are calculated based on total column ozone and cloud optical thickness determined from the Earth Probe Total Ozone Mapping Spectrometer (TOMS) satellite data. Spectral fluxes are calculated between 300 and 325 nanometers using a weighting function similar to the measured function of the Brewer Spectrophotometer. Comparisons of the TOMS-derived values with ground-based Brewer Spectrophotometer measurements at 3 locations from the Canadian Brewer network (Toronto, Saskatoon and Saturna Island) and 3 locations from the United States EPA network (Boston, Gaithersburg, and Boulder) show reasonably good agreement over a variety of clear and cloudy conditions. Some systematic differences are apparent, particularly when snow/ice is present and the TOMS instrument cannot distinguish between clouds and snow covered ground, thus leading to an underestimation of UV flux. The presence of absorbing aerosols near the ground or sub-pixel clouds can also lead to significant errors. There are also possible errors in the Brewer data due to radiometric calibration uncertainties and uncorrected cosine response.

Labow, G. J.↗
NASA NTRS2000

On-Orbit Calibration of ADEOS OCTS with an AVIRIS Underflight

The Ocean Color Temperature Scanner (OCTS) onboard the Advanced Earth Observation Satellite (ADEOS) was launched on August 17, 1996. Calibration of OCTS is required for use of the on-orbit measured data for retrieval of physical properties of the ocean. In the solar reflected portion of the electromagnetic spectrum, OCTS measures images with nominally 700-m spatial resolution through eight multispectral bands. The objective of this research was to establish the absolute radiometric calibration of OCTS on orbit through an underflight by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS is a NASA earth-observing imaging spectrometer designed, built and operated by the Jet Propulsion Laboratory (JPL). AVIRIS acquires data from 20-km altitude on a NASA ER-2 aircraft, above most of the Earth's atmosphere. AVIRIS measures the solar reflected spectrum from 370 nm to 2500 nm through 224 contiguous spectral channels. The full width at half maximum (FWHM) of the spectral channels is nominally 10-nm. AVIRIS spectra are acquired as images of 11 km by up to 800 km extent with 20-m spatial resolution. The high spectral resolution of AVIRIS data allows direct convolution to the spectral response functions of the eight multispectral bands of OCTS. The high spatial resolution of AVIRIS data allows for spatial re-sampling of the data to match the ADEOS sensors spatial resolution. In addition, the AVIRIS high spatial resolution allows assessment of the scaling effects due to environmental factors of thin cirrus clouds, sub-pixel cloud cover, white caps, ocean foam, sun-glint, and bright-target adjacency. The platform navigation information recorded by AVIRIS allows calculation of the position and observation geometry of each spectrum for matching to the OCTS measurement. AVIRIS is rigorously characterized and calibrated in the laboratory prior to and following the flight season. The stability and repeatability of AVIRIS calibration have been validated through an extensive series of inflight calibration experiments. In the OCTS portion of the spectrum, using pre-and post-flight runway calibrations of AVIRIS coupled with the on-board calibrator an absolute calibration accuracy of better than 3% spectral, 2% radiometric and 5% spatial has been achieved. An analogous satellite underflight calibration experiment was performed with AVIRIS and the Optical Sensor (OPS) onboard the Japanese Earth Resources Satellite (JERS).

Green, Robert O.↗
NASA NTRS1998

On-Orbit Calibration of ADEOS OCTS with an AVIRIS Underflight

The Ocean Color Temperature Scanner (OCTS) onboard the Advanced Earth Observation Satellite (ADEOS) was launched on August 17, 1996. Calibration of OCTS is required for use of the on-orbit measured data for retrieval of physical properties of the ocean. In the solar reflected portion of the electromagnetic spectrum, OCTS measures images with nominally 700-m spatial resolution through eight multispectral bands. The objective of this research was to establish the absolute radiometric calibration of OCTS on orbit through an underflight by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS is a NASA Earth-observing imaging spectrometer designed, built and operated by the Jet Propulsion Laboratory (JPL). AVIRIS acquires data from 20-km altitude on a NASA ER-2 aircraft, above most of the Earth's atmosphere. AVIRIS measures the solar reflected spectrum from 370 nm to 2500 nm through 224 contiguous spectral channels. The full width at half maximum (FWHM) of the spectral channels is nominally 10-nm. AVIRIS spectra are acquired as images of 11 km by up to 800 km extent with 20-m spatial resolution. The high spectral resolution of AVIRIS data allows direct convolution to the spectral response functions of the eight multispectral bands of OCTS. The high spatial resolution of AVIRIS data allows for spatial re-sampling of the data to match the ADEOS sensors spatial resolution. In addition, the AVIRIS high spatial resolution allows assessment of the scaling effects due to environmental factors of thin cirrus clouds, sub-pixel cloud cover, white caps, ocean foam, sun-glint, and bright-target adjacency. The platform navigation information recorded by AVIRIS allows calculation of the position and observation geometry of each spectrum for matching to the OCTS measurement. AVIRIS is rigorously characterized and calibrated in the laboratory prior to and following the flight season. The stability and repeatability of AVIRIS calibration have been validated through an extensive series of inflight calibration experiments. In the OCTS portion of the spectrum, using pre- and post-flight runway calibrations of AVIRIS coupled with the on-board calibrator an absolute calibration accuracy of better than 3% spectral, 2% radiometric, and 5% spatial, has been achieved. An analogous satellite underflight calibration experiment was performed with AVIRIS and the Optical Sensor (OPS) onboard the Japanese Earth Resources Satellite (JERS).

Green, Robert O.↗
NASA NTRS2000

Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) Global Snow-Cover Maps

Following the 1999 launch of the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), the capability exists to produce global snow-cover maps on a daily basis at 500-m resolution. Eight-day composite snow-cover maps will also be available. MODIS snow-cover products are produced at Goddard Space Flight Center and archived and distributed by the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado. The products are available in both orbital and gridded formats. An online search and order tool and user-services staff will be available at NSIDC to assist users with the snow products. The snow maps are available at a spatial resolution of 500 m, and 1/4 degree x 1/4 degree spatial resolution, and provide information on sub-pixel (fractional) snow cover. Pre-launch validation work has shown that the MODIS snow-mapping algorithms perform best under conditions of continuous snow cover in low vegetation areas, but can also map snow cover in dense forests. Post-launch validation activities will be performed using field and aircraft measurements from a February 2000 validation mission, as well as from existing satellite-derived snow-cover maps from NOAA and Landsat-7 Enhanced Thematic Mapper Plus (ETM+).

Hall, Dorothy K.↗
NASA NTRS1998

The Surface Displacement Field of the November 8, 1997, Mw7.6 Manyi (Tibet) Earthquake Observed with ERS InSAR Data

ERS2 radar data acquired before and after the Mw7.6, Manyi (Tibet) earthquake of November 8, 1997, provide geodetic information about the surface displacement produced by the earthquake in two ways. (1) The sub-pixel geometric adjustment of the before and after images provides a two dimensional offset field with a resolution of approx, 1m in both the range (radar line of sight) and azimuth (satellite track) directions. Comparison of offsets in azimuth and range indicates that the displacement along the fault is essentially strike-slip and in a left-lateral sense. The offset map reveals a relatively smooth and straight, N78E surface rupture that exceeds 150 km in length, consistent with the EW plane of the Harvard CMT solution. The rupture follows the trace of a quaternary fault visible on satellite imagery (Tapponnier and Molnar, 1978; Wan Der Woerd, pers. comm.). (2) Interferometric processing of the SAR data provides a range displacement map with a precision of a few millimeters. The slip distribution along the rupture reconstructed from the range change map is a bell-shaped curve in the 100-km long central section of the fault with smaller, local maxima near both ends. The curve shows that the fault slip exceeds 2.2 m in range, or 6.2 in strike-slip, along a 30-km long section of the fault and remains above 1 m in range, approx. 3 m strike-slip, along most of its length. Preliminary forward modeling of the central section of the rupture, assuming a uniform slip distribution with depth, indicates that the slip occur-red essentially between 0 and the depth of 10 km, consistent with a relatively shallow event (Velasco et al., 1998).

Peltzer, G.↗
NASA NTRS1999

Location and Geologic Setting for the Three U.S. Mars Landers

Super resolution of the horizon at both Viking landing sites has revealed "new" features we use for triangulation, similar to the approach used during the Mars Pathfinder Mission. We propose alternative landing site locations for both landers for which we believe the confidence is very high. Super resolution of VL-1 images also reveals some of the drift material at the site to consist of gravel-size deposits. Since our proposed location for VL-2 is NOT on the Mie ejecta blanket, the blocky surface around the lander may represent the meter-scale texture of "smooth palins" in the region. The Viking Lander panchromatic images typically offer more repeat coverage than does the IMP on Mars Pathfinder, due to the longer duration of these landed missions. Sub-pixel offsets, necessary for super resolution to work, appear to be attributable to thermal effects on the lander and settling of the lander over time. Due to the greater repeat coverage (particularly in the near and mid-fields) and all-panchromatic images, the gain in resolution by super resolution processing is better for Viking than it is with most IMP image sequences. This enhances the study of textural details near the lander and enables the identification rock and surface textures at greater distances from the lander. Discernment of stereo in super resolution im-ages is possible to great distances from the lander, but is limited by the non-rotating baseline between the two cameras and the shorter height of the cameras above the ground compared to IMP. With super resolution, details of horizon features, such as blockiness and crater rim shapes, may be better correlated with Orbiter images. A number of horizon features - craters and ridges - were identified at VL-1 during the misison, and a few hils and subtle ridges were identified at VL-2. We have added a few "new" horizon features for triangulation at the VL-2 landing site in Utopia Planitia. These features were used for independent triangulation with features visible in Viking Orbiter and MGS MOC images, though the actual location of VL-1 lies in a data dropout in the MOC image of the area. Additional information is contained in the original extended abstract.

Parker, T. J.↗
NASA NTRS1997

Neural Network Prediction of Failure of Damaged Composite Pressure Vessels from Strain Field Data Acquired by a Computer Vision Method

This effort used a new and novel method of acquiring strains called Sub-pixel Digital Video Image Correlation (SDVIC) on impact damaged Kevlar/epoxy filament wound pressure vessels during a proof test. To predict the burst pressure, the hoop strain field distribution around the impact location from three vessels was used to train a neural network. The network was then tested on additional pressure vessels. Several variations on the network were tried. The best results were obtained using a single hidden layer. SDVIC is a fill-field non-contact computer vision technique which provides in-plane deformation and strain data over a load differential. This method was used to determine hoop and axial displacements, hoop and axial linear strains, the in-plane shear strains and rotations in the regions surrounding impact sites in filament wound pressure vessels (FWPV) during proof loading by internal pressurization. The relationship between these deformation measurement values and the remaining life of the pressure vessels, however, requires a complex theoretical model or numerical simulation. Both of these techniques are time consuming and complicated. Previous results using neural network methods had been successful in predicting the burst pressure for graphite/epoxy pressure vessels based upon acoustic emission (AE) measurements in similar tests. The neural network associates the character of the AE amplitude distribution, which depends upon the extent of impact damage, with the burst pressure. Similarly, higher amounts of impact damage are theorized to cause a higher amount of strain concentration in the damage effected zone at a given pressure and result in lower burst pressures. This relationship suggests that a neural network might be able to find an empirical relationship between the SDVIC strain field data and the burst pressure, analogous to the AE method, with greater speed and simplicity than theoretical or finite element modeling. The process of testing SDVIC neural network analysis and some encouraging preliminary results are presented in this paper. Details are given concerning the processing of SDVIC output data such that it may be used as back propagation neural network (BPNN) input data. The software written to perform this processing and the BPNN algorithm are also discussed. It will be shown that, with limited training, test results indicate an average error in burst pressure prediction of approximately six percent,

Russell, Samuel S.↗
NASA NTRS2001

Characterization of Measurement Error Sources in Doppler Global Velocimetry

Doppler global velocimetry uses the absorption characteristics of iodine vapor to provide instantaneous three-component measurements of flow velocity within a plane defined by a laser light sheet. Although the technology is straightforward, its utilization as a flow diagnostics tool requires hardening of the optical system and careful attention to detail during data acquisition and processing if routine use in wind tunnel applications is to be achieved. A development program that reaches these goals is presented. Theoretical and experimental investigations were conducted on each technology element to determine methods that increase measurement accuracy and repeatability. Enhancements resulting from these investigations included methods to ensure iodine vapor calibration stability, single frequency operation of the laser and image alignment to sub-pixel accuracies. Methods were also developed to improve system calibration, and eliminate spatial variations of optical frequency in the laser output, spatial variations in optical transmissivity and perspective and optical distortions in the data images. Each of these enhancements is described and experimental examples given to illustrate the improved measurement performance obtained by the enhancement. The culmination of this investigation was the measured velocity profile of a rotating wheel resulting in a 1.75% error in the mean with a standard deviation of 0.5 m/s. Comparing measurements of a jet flow with corresponding Pitot measurements validated the use of these methods for flow field applications.

Meyers, James F.↗
NASA NTRS2001

A Comparison of Seasonal and Interannual Variability of Soil Dust Aerosols Over the Atlantic Ocean as Inferred by the Toms AI and AVHRR AOT Retrievals

The seasonal cycle and interannual variability of two estimates of soil (or 'mineral') dust aerosols are compared: Advanced Very High Resolution Radiometer (AVHRR) aerosol optical thickness (AOT) and Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI), Both data sets, comprising more than a decade of global, daily images, are commonly used to evaluate aerosol transport models. The present comparison is based upon monthly averages, constructed from daily images of each data set for the period between 1984 and 1990, a period that excludes contamination from volcanic eruptions. The comparison focuses upon the Northern Hemisphere subtropical Atlantic Ocean, where soil dust aerosols make the largest contribution to the aerosol load, and are assumed to dominate the variability of each data set. While each retrieval is sensitive to a different aerosol radiative property - absorption for the TOMS AI versus reflectance for the AVHRR AOT - the seasonal cycles of dust loading implied by each retrieval are consistent, if seasonal variations in the height of the aerosol layer are taken into account when interpreting the TOMS AI. On interannual time scales, the correlation is low at most locations. It is suggested that the poor interannual correlation is at least partly a consequence of data availability. When the monthly averages are constructed using only days common to both data sets, the correlation is substantially increased: this consistency suggests that both TOMS and AVHRR accurately measure the aerosol load in any given scene. However, the two retrievals have only a few days in common per month so that these restricted monthly averages have a large uncertainty. Calculations suggest that at least 7 to 10 daily images are needed to estimate reliably the average dust load during any particular month, a threshold that is rarely satisfied by the AVHRR AOT due to the presence of clouds in the domain. By rebinning each data set onto a coarser grid, the availability of the AVHRR AOT is increased during any particular month, along with its interannual correlation with the TOMS AI The latter easily exceeds the sampling threshold due to its greater ability to infer the aerosol load in the presence of clouds. Whether the TOMS AI should be regarded as a more reliable indicator of interannual variability depends upon the extent of contamination by sub-pixel clouds.

Cakmur, R. V.↗
NASA NTRS2001

Obstacle Detection Algorithms for Rotorcraft Navigation

In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. Wires present a serious hazard to rotorcrafts. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. The performance of the algorithm was evaluated both, at the pixel and the wire levels. It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter.

Kasturi, Rangachar↗
NASA NTRS2001

Multi-Sensor Registration of Earth Remotely Sensed Imagery

Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

LeMoigne, Jacqueline↗
NASA NTRS2001

Earth beacon acquisition and tracking under various illumination conditions

This paper develops an algorithm for determining the geocenter of the Earth regardless of the illumination by the sun using sub-pixel scanning and a simple thresholding technique. To complete this approach the acquisition algorithm is paired with a tracking technique based on maximum likelihood estimation.

beacon↗