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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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Deep narrow band imagery of the diffuse ISM in M33

Very deep narrow band images were obtained for several fields in the local group spiral galaxy M33 using a wide field reimaging Charge Coupled Device (CCD) camera on the 1.5 m telescope at Palomar Observatory. The reimaging system uses a 306 mm collimator and a 58 mm camera lens to put a 16 minute by 16 minute field onto a Texas Instruments 800 x 800 pixel CCD at a resolution of 1.2 arcseconds pixel (-1). The overall system is f/1.65. Images were obtained in the light of H alpha (S II) lambda lambda 6717, 6731, (O III) lambda 5007, and line-free continuum bands 100A wide, centered at 6450A and 5100A. Assuming a distance of 600 kpc to M33 (Humphreys 1980, Ap. J., 241, 587), this corresponds to a linear scale of 3.5 pc pixel (-1), and a field size of 2.8 kpc x 2.8 kpc. Researchers discuss the H alpha imagery of a field centered approx. equal to 8 minutes NE of the nucleus, including the supergiant HII region complex NGC 604. Two 2000 second H alpha images and two 300 second red continuum images were obtained of two slightly offset fields. The fields were offset to allow for discrimination between real emission and possible artifacts in the images. All images were resampled to align them with one of the H alpha frames. The continuum images were normalized to the line images using the results of aperture photometry on a grid of stars in the field, then the rescaled continuum data were directly subtracted from the line data.

Hester, J. Jeff↗
NASA NTRS1990

A modification of the fusion model for log polar coordinates

The fusion mechanism for application in stereo analysis of range restricted the depth of field and therefore required a shift variant mechanism in the peripheral area to find disparity. Misregistration was prevented by restricting the disparity detection range to a neighborhood spanned by the directional edge detection filters. This transformation was essentially accomplished by a nonuniform resampling of the original image in a horizontal direction. While this is easily implemented for digital processing, the approach does not (in the peripheral vision area) model the log-conformal mapping which is known to occur in the human mechanism. This paper therefore modifies the original fusion concept in the peripheral area to include the polar exponential grid-to-log conformal tesselation. Examples of the fusion process resulting in accurate disparity values are given.

Griswold, N. C.↗
NASA NTRS1991

Compositional variability of the Martian surface

Spectral reflectance data from Viking Landers and Orbiters and from telescopic observations were analyzed with the objective of isolating compositional information about the Martian surface and assessing compositional variability. Two approaches were used to calibrate the data to reflectance to permit direct comparisons with laboratory reference spectra of well characterized materials. In Viking Lander multispectral images (six spectral bands) most of the spectral variation is caused by changes in lighting geometry within individual scenes, from scene to scene, and over time. Lighting variations are both wavelength independent and wavelength dependent. By calibrating lander image radiance values to reflectance using spectral mixture analysis, the possible range of compositions was assessed with reference to a collection of laboratory samples, also resampled to the lander spectral bands. All spectra from the lander images studied plot (in six-space) within a planar triangle having at the apexes the respective spectra of tan basaltic palagonite, gray basalt, and shale. Within this plane all lander spectra fit as mixtures of these three endmembers. Reference spectra that plot outside of the triangle are unable to account for the spectral variation observed in the images.

Adams, John B.↗
NASA NTRS1991

Geometric rectification and geocoding of JPL's AIRSAR data over hilly terrain

A post-processing system was developed to georeference and geocode airborne synthetic aperture radar (SAR) data collected by the JPL-Airborne SAR (AIRSAR) System over hilly terrain during the 1990 MAESTRO1 campaign. Georectification relates image coordinates and object coordinates while the geocoding involves resampling. The georectification method uses a hybrid method based upon a number of navigational parameters and minimal two ground-control points which are referenced in both image and map space. The calculation of the intersection of the SAR signal wavefront and a digital elevation model allowed, within certain error bounds, acquisition of the object-to-image and image-to-object relationships.

Degroof, H.↗
NASA NTRS1993

Filtering Interpolators for Image Comparison Algorithms

Comparing two or more images, either by differencing or ratioing, is important to many remote sensing problems. Because the pixel sample points for the images are (almost) always separated by some nonzero shift, a resampling, or interpolation, process must be performed if one image is to be accurately compared to another. Considered in Fourier space, an interpolator acts as a filter that attenuates some frequencies (usually high) of the image. Thus, when the shifted and unshifted images are compared, the former has been filtered, while the latter has not; the effect of this difference is called interpolation error. The key idea of this paper is to apply a filter to the unshifted image that matches the filtering effect of applying the interpolator to the shifted image, thereby drastically reducing interpolation error. The resulting interpolators, called filtering interpolators, are derived and discussed in detail elsewhere. Basic results will be given in this presentation.

Lucke, R. L.↗
NASA NTRS1993

Spectral classification with the International Ultraviolet Explorer: An atlas of B-type spectra

New criteria for the spectral classification of B stars in the ultraviolet show that photospheric absorption lines in the 1200-1900A wavelength region can be used to classify the spectra of B-type dwarfs, subgiants, and giants on a 2-D system consistent with the optical MK system. This atlas illustrates a large number of such spectra at the scale used for classification. These spectra provide a dense matrix of standard stars, and also show the effects of rapid stellar rotation and stellar winds on the spectra and their classification. The observational material consists of high-dispersion spectra from the International Ultraviolet Explorer archives, resampled to a resolution of 0.25 A, uniformly normalized, and plotted at 10 A/cm. The atlas should be useful for the classification of other IUE high-dispersion spectra, especially for stars that have not been observed in the optical.

Rountree, Janet↗
NASA NTRS1992

Linear regression in astronomy. II

A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

Feigelson, Eric D.↗
NASA NTRS1994

Development and implementation of a scrub habitat compensation plan for Kennedy Space Center

Kennedy Space Center (KSC), located on Merritt Island on the east coast of central Florida, is one of three remaining major populations of the Florida Scrub Jay (Aphelocoma coerulescens coerulescens), listed as threatened by the U.S. Fish and Wildlife Service (USFWS) since 1987. Construction of new facilities by the National Aeronautics and Space Administration (NASA) on KSC over the next five years has the potential to impact up to 193 ac (78.1 ha) of Scrub Jay habitat. Under an early consultation process with the Endangered Species Office of the USFWS, NASA agreed to a compensation plan for loss of Scrub Jay habitat. The compensation plan required NASA to restore or create scrub on KSC at a 2:1 ratio for that lost. The compensation plan emphasized restoration of scrub habitat that is of marginal or declining suitability to Scrub Jays because it has remained unburned. Although prescribed burning has been conducted by the USFWS Merritt Island National Wildlife Refuge (MINWR) for more than ten years, significant areas of scrub remain unburned because they have been excluded from fire management units or because landscape fragmentation and a period of fire suppression allowed scrub to reach heights and diameters that are fire resistant. For such areas, mechanical cutting followed by prescribed burning was recommended for restoration. A second part of the restoration plan is an experimental study of scrub reestablishment (i.e., creation) on abandoned, well drained agricultural sites by planting scrub oaks and other scrub plants. The compensation plan identified 260 ac (105 ha) of scrub restoration in four areas and a 40 ac (16 ha) scrub creation site. Monitoring of restoration sites required under the plan included: establishing permanent vegetation sample transects before treatment and resampling annually for ten years after treatment, and color banding Scrub Jays to determine territories prior to treatment followed by monitoring reproductive success and survival for ten years after treatment. Monitoring scrub creation sites included determining survival of planted material for five years and establishing permanent transects to follow vegetation development for ten years after planting. Scrub Jay monitoring of creation sites is incorporated with that of adjacent restoration sites.

Schmalzer, Paul A.↗
NASA NTRS1994

Overview on METEOSAT geometrical image data processing

Digital Images acquired from the geostationary METEOSAT satellites are processed and disseminated at ESA's European Space Operations Centre in Darmstadt, Germany. Their scientific value is mainly dependent on their radiometric quality and geometric stability. This paper will give an overview on the image processing activities performed at ESOC, concentrating on the geometrical restoration and quality evaluation. The performance of the rectification process for the various satellites over the past years will be presented and the impacts of external events as for instance the Pinatubo eruption in 1991 will be explained. Special developments both in hard and software, necessary to cope with demanding tasks as new image resampling or to correct for spacecraft anomalies, are presented as well. The rotating lens of MET-5 causing severe geometrical image distortions is an example for the latter.

Diekmann, Frank J.↗
NASA NTRS1995

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Fisher, Douglas H.↗
NASA NTRS1994

Kriging in the Shadows: Geostatistical Interpolation for Remote Sensing

It is often useful to estimate obscured or missing remotely sensed data. Traditional interpolation methods, such as nearest-neighbor or bilinear resampling, do not take full advantage of the spatial information in the image. An alternative method, a geostatistical technique known as indicator kriging, is described and demonstrated using a Landsat Thematic Mapper image in southern Chiapas, Mexico. The image was first classified into pasture and nonpasture land cover. For each pixel that was obscured by cloud or cloud shadow, the probability that it was pasture was assigned by the algorithm. An exponential omnidirectional variogram model was used to characterize the spatial continuity of the image for use in the kriging algorithm. Assuming a cutoff probability level of 50%, the error was shown to be 17% with no obvious spatial bias but with some tendency to categorize nonpasture as pasture (overestimation). While this is a promising result, the method's practical application in other missing data problems for remotely sensed images will depend on the amount and spatial pattern of the unobscured pixels and missing pixels and the success of the spatial continuity model used.

Rossi, Richard E.↗
NASA NTRS1997

WFPC2 photometry from subtraction of TinyTim PSFs

Based upon the subtraction of TinyTim Point Spread Function (PSFs) from Principle Component Image (PC1) point-like objects, a method has been developed to determine the optimal values for the telescope jitter and the Z4 relative focus during calibration or science observations. Using these jitter and focus values, an optimal TinyTim PSF, computed over a resampled grid, is then iteratively fitted to the object, yielding an improvement in the PSF centering, more accurate photometric results and a better detection of underlying structures. Preliminary results seem to indicate that appropriate synthetic TinyTim PSFs perform as well as observed PSFs.

Remy, M.↗
NASA NTRS1997

Multitemporal and Multiscaled Fractal Analysis of Landsat Satellite Data Using the Image Characterization and Modeling System (ICAMS)

The Image Characterization And Modeling System (ICAMS) is a public domain software package that is designed to provide scientists with innovative spatial analytical tools to visualize, measure, and characterize landscape patterns so that environmental conditions or processes can be assessed and monitored more effectively. In this study ICAMS has been used to evaluate how changes in fractal dimension, as a landscape characterization index, and resolution, are related to differences in Landsat images collected at different dates for the same area. Landsat Thematic Mapper (TM) data obtained in May and August 1993 over a portion of the Great Basin Desert in eastern Nevada were used for analysis. These data represent contrasting periods of peak "green-up" and "dry-down" for the study area. The TM data sets were converted into Normalized Difference Vegetation Index (NDVI) images to expedite analysis of differences in fractal dimension between the two dates. These NDVI images were also resampled to resolutions of 60, 120, 240, 480, and 960 meters from the original 30 meter pixel size, to permit an assessment of how fractal dimension varies with spatial resolution. Tests of fractal dimension for two dates at various pixel resolutions show that the D values in the August image become increasingly more complex as pixel size increases to 480 meters. The D values in the May image show an even more complex relationship to pixel size than that expressed in the August image. Fractal dimension for a difference image computed for the May and August dates increase with pixel size up to a resolution of 120 meters, and then decline with increasing pixel size. This means that the greatest complexity in the difference images occur around a resolution of 120 meters, which is analogous to the operational domain of changes in vegetation and snow cover that constitute differences between the two dates.

Quattrochi, Dale A.↗
NASA NTRS1998

Seasonally Frozen Soil Monitoring Using Passive Microwave Satellite Data and Simulation Modeling

Satellite data and simulation modeling were used to assess seasonally frozen soils in the central US - Canada borders area (46-53 degrees N and 96-108 degrees). We used Scanning Multichannel Microwave Radiometer (SMMR) satellite data to delineate the top layer of frozen soils. SMMR is a passive microwave sensor having five channels (6.6, 10, 18, 21 and 37 GHz) with a horizontal and vertical polarization. SMRR data are available between 1978-1987 with noon and midnight overpass and footprint sizes between 25 km and 150 km. SMMR data were processed from resampled 1/4 degree grid cells during fall freeze-up and spring thaw (fall 1985 - spring 1987). The dielectric properties of a target may directly affect the satellite signal. The dielectric value is an order of magnitude smaller for frozen soil water. There are other significant changes to the emitted microwave signal from changes to the surface physical temperature, attenuation of the soil signal from plant water and soil moisture. We further characterized the temporal and spatial dynamic of frozen soils using the FroST (Frozen Soil Temperature) simulation model. The FroST model was used to further predict soil water and ice content, and soil temperature. SMMR results were compared versus 5-cm soil temperature data from available weather stations (14 in Canada and 11 for available months in the US). SMMR data were analyzed as a function of frequency, polarization, polarization difference, and "frequency gradient". In addition, vegetation density, physical temperature and snow depth were also considered. Preliminary analysis of SMMR derived frozen soil/thaw classification using a simple threshold classification indicates a mean overall classification accuracy by season of 85 percent. A sensitivity analysis for different soils with varying amounts of snow was conducted with FroST, which showed that the amount of snow, and the time of snow fall and melt affected the ice and water content, and depth of thaw. These results indicate a potential source of flooding and erosion under conditions when melting snow and spring rains provide a source of infiltrating water.

Toll, D. L.↗
NASA NTRS2000

Application of Radar Data to Remote Sensing and Geographical Information Systems

The field of synthetic aperture radar changed dramatically over the past decade with the operational introduction of advance radar techniques such as polarimetry and interferometry. Radar polarimetry became an operational research tool with the introduction of the NASA/JPL AIRSAR system in the early 1980's, and reached a climax with the two SIR-C/X-SAR flights on board the space shuttle Endeavour in April and October 1994. Radar interferometry received a tremendous boost when the airborne TOPSAR system was introduced in 1991 by NASA/JPL, and further when data from the European Space Agency ERS-1 radar satellite became routinely available in 1991. Several airborne interferometric SAR systems are either currently operational, or are about to be introduced. Radar interferometry is a technique that allows one to map the topography of an area automatically under all weather conditions, day or night. The real power of radar interferometry is that the images and digital elevation models are automatically geometrically resampled, and could be imported into GIS systems directly after suitable reformatting. When combined with polarimetry, a technique that uses polarization diversity to gather more information about the geophysical properties of the terrain, a very rich multi-layer data set is available to the remote sensing scientist. This talk will discuss the principles of radar interferometry and polarimetry with specific application to the automatic categorization of land cover. Examples will include images acquired with the NASA/JPL AIRSAR/TOPSAR system in Australia and elsewhere.

vanZyl, Jakob J.↗
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

High Altitude Measurements of Radiance at High Spectral and Spatial Resolution for SIMBIOS Sensor Calibration, Validation, and Intercomparisons

The successful combination of data from different ocean color sensors depends on the correct interpretation of signal from each of these sensors. Ideally, the sensor measured signals are calibrated to geophysical units of spectral radiance, and sensor artifacts are removed and corrected. The calibration process resamples the signal into a common radiometric data space so that subsequent ocean color algorithms that are applied to the data are based on physical processes and are inherently sensor independent. The objective of this project is to calibrate and validate the on-orbit radiometric characteristics of Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) with underflights of NASA's calibrated Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This objective is feasible because AVIRIS measures the same spectral range as SeaWIFS at higher spectral resolution. In addition to satellite sensor underflights, the AVIRIS project has supported comparison and analysis of the radiometric calibration standards used for AVIRIS and SeaWIFS. To date, both the OCTS and SeaWIFS satellite sensors have been underflown by AVIRIS with matching spectral, spatial, geometric, radiometric, and temporal domains. The calibration and validation objective of this project is pursued for the following reasons: (1) Calibration is essential for the quantitative use of SeaWIFS and other SIMBIOS (Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies) sensor data; (2) Calibration in the laboratory of spaceborne sensors is challenging; (3) Satellite sensors are subjected aging on the ground and to trauma during launch; (4) The Earth orbit environment is significantly different than the laboratory calibration environment; (5) Through years of effort AVIRIS has been demonstrated to be well calibrated; and (6) AVIRIS can match the spectral and spatial observation characteristics near the top of the atmosphere at the time of SeaWIFS measurements.

Green, Robert O.↗
NASA NTRS2002

Comparing IKONOS and Landsat 7 Images

This work is a continuation of the simulations presented at the previous workshop.INformation is presented on the following: 20 IKONOS images compared with 10 Landsat 7 ETM+VNIR images acquired on the same days. Comparisons are based on simulations of the Landsat 7 images from the IKONOS data. IKONOS and Landsat 7 images used in simulations are on a similar processing level with radiometric correction, georeferenced with cubic-convolution resampling, and UTM projection with WGS-84 datum.

Blonski, Slawomir↗