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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 NTRS1988

Planetary Spectroscopy

The goal of this task is to acquire physical data on the atmospheres of the outer planets and Titan by means of ground-based spectroscopy, spectrophotometry, and spectral imaging at visible to near-infrared wavelengths (approximately 0.3 to 2.5 micrometer). These data constrain physical parameters which characterize properties and distribution of aerosols in the atmospheres of these bodies. Reduced spectral imaging of Neptune was accomplished. The data were analyzed in several ways. Direct inspection of images reveals the distribution of discrete clouds in the atmosphere, which indicate that the global distribution of clouds has changed since earlier imaging. Disk-integrated photometry obtained from the images demonstrates that the diurnal variability at methane-band wavelengths is caused by the presence of discrete clouds; short-term variability is also seen in the rotational light curve, providing evidence for modification of cloud structure on the planet. The center-to-limb brightness profiles of the equatorial region of Neptune were analyzed, which provided constraints on the location, albedos, and optical depths of aerosol scattering layers in the troposphere and lower stratosphere.

Bergstralh, Jay T.↗
NASA NTRS2009

Evolutionary Computing Methods for Spectral Retrieval

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

Terrile, Richard↗
NASA NTRS1986

Simultaneous imaging and spectral observations in microwaves and hard X-rays of the impulsive phase of a solar limb flare

Observations of the impulsive phase of a solar flare at microwave wavelengths and in hard X-rays are used to deduce the strength of the magnetic field and the number of energetic electrons producing the burst. The microwave observations, using the VLA at 6 cm, had spatial resolution of 8 x 8 arcsec, close to the resolution of the Hard X-ray Imaging Spectrometer on SMM which also imaged this flare. The Hard X-ray Burst Spectrometer determined the spectrum of the burst in the range 25-512 keV, and several patrol telescopes recorded the microwave time profile at frequencies from 2.8 to 19.6 GHz. The combined data show that the derived number of microwave-emitting electrons is at least three orders of magnitude fewer than the number of thick target electrons producing the hard X-rays. It is proposed that the fast electrons are highly beamed and radiate gyrosynchrotron emission less efficiently than isotropically distributed electrons.

Schmahl, E. J.↗
NASA NTRS1993

Analysis of hyper-spectral AVIRIS image data over a mixed-conifer forest in Maine

An introduction to some of the potential uses of hyperspectral data for ecosystem analysis is presented. The examples given are derived from a digital dataset acquired over a sub-boreal forest in central Maine in 1990 by the NASA-JPL Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument gathers data from 400 to 2500 nm in 224 channels at bandwidths of approximately 10 nm. As a preview to the uses of the hyperspectral data, several products from this dataset were extracted. They range from the traditional false color composite made from simulated Thematic Mapper bands and the well known normalized difference vegetation index to much more exotic products such as fractions of vegetation, soil and shade based on linear spectral mixing models and estimates of the leaf water content at the landscape level derived using spectrum-matching techniques. Our research and that of many others indicates that the hyperspectral datasets carry much important information which is only beginning to be understood. This analysis gives an initial indication of the utility of hyperspectral data. Much work still remains to be done in algorithm development and in understanding the physics behind the complex information signal carried in the hyperspectral datasets. This work must be carried out to provide the fullest science support for high spectral resolution data to be acquired by many of the instruments to be launched as part of the Earth Observing System program in the mid-1990's.

Lawrence, William T.↗
NASA NTRS1990

Planetary astronomy of Mars. Mars data reduction

Grant #NAGW-1408 was specifically awarded to obtain telescopic visible and near-IR spectral imaging of Mars during the 1988 apparition (9/28/88). The observing program was highly successful producing approximately 2 Gbytes of data, but was only funded for one year and virtually all of the funds were spent in data acquisition. The follow-up grant was funded the following year for reduction of these data into a scientifically productive form, which because of the size and nature of our observations, was a non-trivial task. A more detailed scientific analysis of these data (fully reduced) is in progress now and will take a number of years. Extended geologic analyses of the astronomical data are being funded by the NASA Planetary Geology and Geophysics program. The objective was to produce detailed reflectance spectra for contiguous, spatially resolved surface elements covering most of the planet (about +50 degrees to -90 degrees latitude, all longitudes). A total of 6 observing runs, of 3-4 days duration each, were conducted on the University of Arizona's 1.5m telescope on Mt. Bigelow. We present a sketch map showing the approximate total extent of our spectral image coverage. Nearly all of Mars south of 40 degrees N was observed at least once. About half of the area shown was observed multiple times. South of 65 degrees S, including the south polar cap, our coverage is heavily redundant. The first run was conducted June 29 - July 1, 1988 (all dates are UT) to serve as a baseline prior to possible dust storm activity on Mars. The other observing runs were closer to opposition: Sept. 3-6, 13-15, 24-26, and Oct. 5-7 and 16-18. The September and October observations were scheduled to provide maximum longitudinal coverage. This was also intended to provide a balance between surface observations and observations of predicted dust storm activity. No global dust storm developed in 1988, so we have a large volume of data for the surface of Mars.

Singer, Robert B.↗
NASA NTRS2007

Ground-Based Correction of Remote-Sensing Spectral Imagery

Software has been developed for an improved method of correcting for the atmospheric optical effects (primarily, effects of aerosols and water vapor) in spectral images of the surface of the Earth acquired by airborne and spaceborne remote-sensing instruments. In this method, the variables needed for the corrections are extracted from the readings of a radiometer located on the ground in the vicinity of the scene of interest. The software includes algorithms that analyze measurement data acquired from a shadow-band radiometer. These algorithms are based on a prior radiation transport software model, called MODTRAN, that has been developed through several versions up to what are now known as MODTRAN4 and MODTRAN5 . These components have been integrated with a user-friendly Interactive Data Language (IDL) front end and an advanced version of MODTRAN4. Software tools for handling general data formats, performing a Langley-type calibration, and generating an output file of retrieved atmospheric parameters for use in another atmospheric-correction computer program known as FLAASH have also been incorporated into the present soft-ware. Concomitantly with the soft-ware described thus far, there has been developed a version of FLAASH that utilizes the retrieved atmospheric parameters to process spectral image data.

Alder-Golden, Steven M.↗
NASA NTRS2021

Pluto’s Sputnik Planitia: Composition of geological units from infrared spectroscopy

We have compared spectroscopic data of Sputnik Planitia on Pluto, as acquired by New Horizons’ Linear Etalon Imaging Spectral Array (LEISA) instrument, to the geomorphology as mapped by White et al. (2017) using visible and panchromatic imaging acquired by the LOng-Range Reconnaissance Imager (LORRI) and the Multi-spectral Visible Imaging Camera (MVIC). We have focused on 13 of the geologic units identified by White et al. (2017), which include the plains and mountain units contained within the Sputnik basin. We divided the map of Sputnik Planitia into 15 provinces, each containing one or more geologic units, and we use LEISA to calculate the average spectra of the units inside the 15 provinces. Hapke-based modeling was then applied to the average spectra of the units to infer their surface composition, and to determine if the composition resulting from the modeling of LEISA spectra reflects the geomorphologic analyses of LORRI data, and if areas classified as being the same geologically, but which are geographically separated, share a similar composition. We investigated the spatial distribution of the most abundant ices on Pluto’s surface - CH4, N2, CO, H2O, and a non-ice component presumed to be a macromolecular carbon-rich material, termed a tholin, that imparts a positive spectral slope in the visible spectral region and a negative spectral slope longward of ~1.1 μm. Because the exact nature of the non-ice component is still debated and because the negative spectral slope of the available tholins in the near infrared does not perfectly match the Pluto data, for spectral modeling purposes we reference it generically as the negative spectral slope endmember (NSS endmember). We created maps of variations in the integrated band depth (from LEISA data) and areal mass fraction (from the modeling) of the components. The analysis of correlations between the occurrences of the endmembers in the geologic units led to the observation of an anomalous suppression of the strong CH4 absorption bands in units with compositions that are dominated by H2O ice and the NSS endmember. Exploring the mutual variation of the CH4 and N2 integrated band depths with the abundance of crystalline H2O and NSS endmember revealed that the NSS endmember is primarily responsible for the suppression of CH4 absorptions in mountainous units located along the western edge of Sputnik Planitia. Our spectroscopic analyses have provided additional insight into the geological processes that have shaped Sputnik Planitia. A general increase in volatile abundance from the north to the south of Sputnik Planitia is observed. Such an increase first observed and interpreted by Protopapa et al., 2017 and later confirmed by climate modeling (Bertrand et al., 2018) is expressed geomorphologically in the form of preferential deposition of N2 ice in the upland and mountainous regions bordering the plains of southern Sputnik Planitia. Relatively high amounts of pure CH4 are seen at the southern Tenzing Montes, which are a natural site for CH4 deposition owing to their great elevation and the lower insolation they are presently receiving. The NSS endmember correlates the existence of tholins within certain units, mostly those coating the low-latitude mountain ranges that are co-latitudinal with the tholin-covered Cthulhu Macula. The spectral analysis has also revealed compositional differences between the handful of occurrences of northern non-cellular plains and the surrounding cellular plains, all of which are located within the portion of Sputnik Planitia that is presently experiencing net sublimation of volatiles, and which do not therefore exhibit a surface layer of bright, freshly-deposited N2 ice. The compositional differences between the cellular and non-cellular plains here hint at the effectiveness of convection in entraining and trapping tholins within the body of the cellular plains, while preventing the spread of such tholins to abutting non-cellular plains.

Pluto's Sputnik Planitia↗
NASA NTRS1973

Spectral ratio imaging methods for geological remote sensing from aircraft and satellites

The author has identified the following significant results. The production of ratio images from multispectral scanner data is described and several examples of ratio images from aircraft and ERTS-1 data are given for visible, reflective infrared, and thermal infrared wavelengths. The application of photogrammetric techniques to ratio images, defined for this paper as ratio scannergrammetry, is considerably aided by the lesser dependence of ratio images on atmospheric and solar illumination variations, compared with single channel scanner imagery or aerial photos. Ratio scannergrammetry is further aided by the proportionality between ratios of a target deduced from ratio images and ratios of reflectances calculated from laboratory spectra of samples from the target area. Consequently, ratios calculated from laboratory data can be used to predict which ratios are best for discriminating a given rock or mineral, to predict what other rocks or minerals will be confused with it, and finally, to place ratio scannergrammetry on an absolute basis, within an estimated standard error on the order of 5% to 10%. Examples of relative agreement between laboratory data and ratio images are given from two iron oxides, hematite and magnetite.

Vincent, R. K.↗
NASA NTRS1973

Spectral ratio imaging methods for geological remote sensing from aircraft and satellites

An improved photogrammetric technique (scannergrammetry) for the production of ratio images from multispectral scanner data is described. The multispectral technique is less affected by variations in atmospheric and solar illumination levels than single-channel scanner imagery of aerial photographs. Another advantage of the multispectral technique is the proportionality between ratios of a target deduced from ratio images, on the one hand, and ratios of reflectances calculated from laboratory spectra of samples from the target area, on the other hand. Several representative ratio images from aircraft and satellite data in the visible, reflective IR, and thermal IR regions are included. The geological applications suggested for ratio scannergrammetry include exploration of construction materials, soils, stratigraphy, volcanic ash flows, beaches, and sand dunes.

Vincent, R. K.↗
NASA NTRS1977

Cluster compression algorithm: A joint clustering/data compression concept

The Cluster Compression Algorithm (CCA), which was developed to reduce costs associated with transmitting, storing, distributing, and interpreting LANDSAT multispectral image data is described. The CCA is a preprocessing algorithm that uses feature extraction and data compression to more efficiently represent the information in the image data. The format of the preprocessed data enables simply a look-up table decoding and direct use of the extracted features to reduce user computation for either image reconstruction, or computer interpretation of the image data. Basically, the CCA uses spatially local clustering to extract features from the image data to describe spectral characteristics of the data set. In addition, the features may be used to form a sequence of scalar numbers that define each picture element in terms of the cluster features. This sequence, called the feature map, is then efficiently represented by using source encoding concepts. Various forms of the CCA are defined and experimental results are presented to show trade-offs and characteristics of the various implementations. Examples are provided that demonstrate the application of the cluster compression concept to multi-spectral images from LANDSAT and other sources.

Hilbert, E. E.↗
NASA NTRS1987

X-ray observations of spiral galaxies. II - Images and spectral parameters of 13 galaxies

The results of a spatial and spectral analysis of a sample of spiral galaxies observed in X-rays with the Einstein satellite indicate that the X-ray emission is generally extended and complex. In some cases, discrete, very bright X-ray sources are detected, some of these coincident with the nuclear regions. The spectral fit of the IPC data to a thermal bremsstrahlung spectrum with a low-energy absorption cutoff shows that the average spectrum could be rather hard with kT greater than 2 keV, and with low-energy cutoff consistent with line-of-sight absorption. Results on NGC 4631, NGC 6946, and the nuclei of IC 342 and NGC 1313 are discussed and compared with previous observations in different energy ranges.

Fabbiano, G.↗
NASA NTRS1996

Algal Accessory Pigment Detection Using AVIRIS Image-Derived Spectral Radiance Data

Visual and derivative analyses of AVIRIS spectral data can be used to detect algal accessory pigments in aquatic communities. This capability extends the use of remote sensing for the study of aquatic ecosystems by allowing detection of taxonomically significant pigment signatures which yield information about the type of algae present. Such information allows remote sensing-based assessment of aquatic ecosystem health, as in the detection of nuisance blooms of cyanobacteria or toxic blooms of dinoflagellates. Remote sensing of aquatic systems has traditionally focused on quantification of chlorophyll a, a photoreactive (and light-harvesting) pigment which is common to all algae as well as cyanobacteria (bluegreen algae). Due to the ubiquitousness of this pigment within algae, chl a is routinely measured to estimate algal biomass both during ground-truthing and using various airborne or satellite based sensors, including AVIRIS. Within the remote sensing and aquatic sciences communities, ongoing research has been performed to detect algal accessory pigments for assessment of algal population composition. This research is based on the fact that many algal accessory pigments are taxonomically significant, and all are spectrally unique. Aquatic scientists have been refining pigment analysis techniques, primarily high performance liquid chromatography, or HPLC, to detect specific pigments as a time-saving alternative to individual algal cell identifications and counts. Remote sensing scientists are investigating the use of pigment signatures to construct pigment libraries analogous to mineral spectral libraries used in geological remote sensing applications. The accessory pigment approach has been used successfully in remote sensing using data from the Thematic Mapper, low-altitude, multiple channel scanners, field spectroradiometers and the AVIRIS hyperspectral scanner. Due to spectral and spatial resolution capabilities, AVIRIS is the sensor of choice for such studies. We present here our results on detection of algal accessory pigments using AVIRIS data.

Richardson, Laurie L.↗
NASA NTRS1993

Multi-Spectral Digital Imaging of Dead Sea Scrolls and Other Ancient Documents

It is well known that the Dead Sea scrolls and similar soft media texts are often difficult to read due to the inability of the epigrapher to distinguish the black ink with which they were written from the aged, blacked parchment on which they were inscribed. While considerable success has been achieved in enhancing the readability of these texts through infrared photography, this technique-as conventionally applied today-has distinct limitations.

Dead Sea Scrolls soft media texts infrared photogr↗
NASA NTRS2010

Context Modeler for Wavelet Compression of Spectral Hyperspectral Images

A context-modeling sub-algorithm has been developed as part of an algorithm that effects three-dimensional (3D) wavelet-based compression of hyperspectral image data. The context-modeling subalgorithm, hereafter denoted the context modeler, provides estimates of probability distributions of wavelet-transformed data being encoded. These estimates are utilized by an entropy coding subalgorithm that is another major component of the compression algorithm. The estimates make it possible to compress the image data more effectively than would otherwise be possible. The following background discussion is prerequisite to a meaningful summary of the context modeler. This discussion is presented relative to ICER-3D, which is the name attached to a particular compression algorithm and the software that implements it. The ICER-3D software is summarized briefly in the preceding article, ICER-3D Hyperspectral Image Compression Software (NPO-43238). Some aspects of this algorithm were previously described, in a slightly more general context than the ICER-3D software, in "Improving 3D Wavelet-Based Compression of Hyperspectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. In turn, ICER-3D is a product of generalization of ICER, another previously reported algorithm and computer program that can perform both lossless and lossy wavelet-based compression and decompression of gray-scale-image data. In ICER-3D, hyperspectral image data are decomposed using a 3D discrete wavelet transform (DWT). Following wavelet decomposition, mean values are subtracted from spatial planes of spatially low-pass subbands prior to encoding. The resulting data are converted to sign-magnitude form and compressed. In ICER-3D, compression is progressive, in that compressed information is ordered so that as more of the compressed data stream is received, successive reconstructions of the hyperspectral image data are of successively higher overall fidelity.

Kiely, Aaron↗
NASA NTRS2012

ORIGIN: Metal Creation and Evolution from the Cosmic Dawn

ORIGIN is a proposal for the M3 mission call of ESA aimed at the study of metal creation from the epoch of cosmic dawn. Using high-spectral resolution in the soft X-ray band, ORIGIN will be able to identify the physical conditions of all abundant elements between C and Ni to red-shifts of z=10, and beyond. The mission will answer questions such as: When were the first metals created? How does the cosmic metal content evolve? Where do most of the metals reside in the Universe? What is the role of metals in structure formation and evolution? To reach out to the early Universe ORIGIN will use Gamma-Ray Bursts (GRBs) to study their local environments in their host galaxies. This requires the capability to slew the satellite in less than a minute to the GRB location. By studying the chemical composition and properties of clusters of galaxies we can extend the range of exploration to lower redshifts (z approx. 0.2). For this task we need a high-resolution spectral imaging instrument with a large field of view. Using the same instrument, we can also study the so far only partially detected baryons in the Warm-Hot Intergalactic Medium (WHIM). The less dense part of the WHIM will be studied using absorption lines at low redshift in the spectra for GRBs. The ORIGIN mission includes a Transient Event Detector (coded mask with a sensitivity of 0.4 photon/sq cm/s in 10 s in the 5-150 keV band) to identify and localize 2000 GRBs over a five year mission, of which approx.65 GRBs have a redshift >7. The Cryogenic Imaging Spectrometer, with a spectral resolution of 2.5 eV, a field of view of 30 arcmin and large effective area below 1 keV has the sensitivity to study clusters up to a significant fraction of the virial radius and to map the denser parts of the WHIM (factor 30 higher than achievable with current instruments). The payload is complemented by a Burst InfraRed Telescope to enable onboard red-shift determination of GRBs (hence securing proper follow up of high-z bursts) and also probes the mildly ionized state of the gas. Fast repointing is achieved by a dedicated Controlled Momentum Gyro and a low background is achieved by the selected low Earth orbit.

Kouveliotou, C.↗
NASA NTRS2016

Multi Spectral Fluorescence Imager (MSFI)

Genetic transformation with in vivo reporter genes for fluorescent proteins can be performed on a variety of organisms to address fundamental biological questions. Model organisms that may utilize an ISS imager include unicellular organisms (Saccharomyces cerevisiae), plants (Arabidopsis thaliana), and invertebrates (Caenorhabditis elegans). The multispectral fluorescence imager (MSFI) will have the capability to accommodate 10 cm x 10 cm Petri plates, various sized multi-well culture plates, and other custom culture containers. Features will include programmable temperature and light cycles, ethylene scrubbing (less than 25 ppb), CO2 control (between 400 ppm and ISS-ambient levels in units of 100 ppm) and sufficient airflow to prevent condensation that would interfere with imaging.

Fluorescence↗
NASA NTRS1994

ASTER Instrument Design and Science Objectives

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), a multi-spectral imaging radiometer with 14 spectral bands, is a research facility instrument that will be launched in 1998 on NASA's EOS AM-1 platform.

ASTER↗