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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Remote Sensing, GIS, and Vector-Borne Disease

The concept of global climate change encompasses more than merely an alteration in temperature; it also includes spatial and temporal covariations in precipitation and humidity, and more frequent occurrence of extreme weather events. The impact of these variations, which can occur at a variety of temporal and spatial scales, could have a direct impact on disease transmission through their environmental consequences for pathogen, vector, and host survival, as well as indirectly through human demographic and behavioral responses. New and future sensor systems will allow scientists to investigate the relationships between climate change and environmental risk factors at multiple spatial, temporal and spectral scales. Higher spatial resolution will provide better opportunities for mapping urban features previously only possible with high resolution aerial photography. These opportunities include housing quality (e.g., Chagas'disease, leishmaniasis) and urban mosquito habitats (e.g., dengue fever, filariasis, LaCrosse encephalitis). There are or will be many new sensors that have higher spectral resolution, enabling scientists to acquire more information about parameters such as soil moisture, soil type, better vegetation discrimination, and ocean color, to name a few. Although soil moisture content is now detectable using Landsat, the new thermal, shortwave infrared, and radar sensors will be able to provide this information at a variety of scales not achievable using Landsat. Soil moisture could become a key component in transmission risk models for Lyme disease (tick survival), helminthiases (worm habitat), malaria (vector-breeding habitat), and schistosomiasis (snail habitat).

Beck, Louisa R.↗
NASA NTRS2011

An Unlikely Radio Halo in the Low X-Ray Luminosity Galaxy Cluster RXCJ1514.9-1523

Aims: We report the discovery of a giant radio halo in the galaxy cluster RXCJ1514,9-1523 at z=0.22 with a relatively low X-ray luminosity, L(sub X) (0.1-2.4kev) approx. 7 x 10(exp 44) ergs/s. Methods: This faint, diffuse radio source is detected with the Giant Meterwave Radio Telescope at 327 MHz. The source is barely detected at 1.4 GHz in a NVSS pointing that we have reanalyzed. Results: The integrated radio spectrum of the halo is quite steep, with a slope alpha = 1.6 between 327 MHz and 1.4 GHz. While giant radio halos are common in more X-ray luminous cluster mergers, there is a less than 10% probability to detect a halo in systems with L(sub X) < 8 x 10(exp 44) ergs/s. The detection of a new giant halo in this borderline luminosity regime can be particularly useful for discriminating between the competing theories for the origin of ultrarelativistic electrons in clusters. Furthermore, if our steep radio spectral index is confirmed by future deeper radio observations, this cluster would provide another example of the very rare, new class of ultra-steep spectrum radio halos, predicted by the model in which the cluster cosmic ray electrons are produced by turbulent reacceleration.

Marketvitch, M.↗
NASA NTRS1990

Subvisual cirrus detection via a multi-spectral decomposition method

Lidar data collected on September 15, 1988 over Dayton (Ohio) were synchronized with NOAA satellite observations in order to investigate the feasibility of discriminating between observations of subvisual cirrus, other cirrus, and clear sky. It is concluded that the detection of subvisual cirrus currently requires 'ground-truth' information, such as lidar measurements, for cloud height determinations and for verification.

Schmidt, Eric O.↗
NASA NTRS1984

Mechanism of colour discrimination by a bacterial sensory rhodopsin

A photosensitive protein resembling the visual pigments of invertebrates enables phototactic archaebacteria to distinguish color. This protein exists in two spectrally-distinct forms, one of which is a transient photoproduct of the other and each of which undergoes photochemical reactions controlling the cell's swimming behaviour. Activation of a single pigment molecule in the cell is sufficient to signal the flagellar motor. This signal-transduction mechanism makes evident a color-sensing capability inherent in the retinal/protein chromophore.

Spudich, J. L.↗
NASA NTRS1973

Characteristics of cesium iodide for use as a particle discriminator for high energy cosmic rays

The possible use of CsI to discriminate between high energy cosmic ray electrons and interacting protons has been investigated. The pulse-shape properties as a function of ionization density, temperature, and spectral response are presented for thallium-activated CsI and as a function of ionization density for sodium-activated CsI. The results are based on previously published data and on corroborative measurements from the present work. Experimental results on the response of CsI to electron-induced electromagnetic cascades and to interacting hadrons are described. Bibliographies of publications dealing with the properties of CsI and with pulse-shape discrimination techniques are presented.

Crannell, C. J.↗
NASA NTRSDate not supplied

Development of a Consistent GEOsat Cloud Property Dataset for the CERES Climate Data Record

Cloud properties are critical for understanding the Earth’s radiation budget and cloud feedbacks. At NASA Langley Research Center, the Satellite ClOud and Radiative Property retrieval System (SatCORPS) provides real-time and historical analyses of clouds derived from Geostationary satellite (GEOsat) data for weather and climate applications. For the Clouds and the Earth’s Radiant Energy System (CERES) program, the global constellation of GEOsats has been analyzed since 2000 to help characterize and account for the diurnal cycle of clouds and their radiative impacts in the CERES climate data record. Obtaining consistent cloud properties over the GEOsat data record during the CERES era is a major objective but a significant challenge considering the diversity of imaging capabilities deployed during that time. The GEOsat data analysis approach for the current CERES Edition-4 (Ed4) data products was focused on accuracy and consistency with MODIS by employing as much spectral information as possible from each satellite. However, the inconsistent use of spectral information across GEOsats led to marked discontinuities in the spatial and temporal record of cloud properties that had to be accounted for post facto in downstream CERES processing. This paper reports progress in developing a new GEOsat analysis system for the next CERES edition (Ed5) that has potential to improve cross-platform consistency and continuity. In this approach, the spectral channel complement is limited to just 3-channels during daytime, ~0.65 µm (VIS), ~3.9 µm (NIR), and ~10.8 µm (IR), common to nearly all of the satellites in the record. At night, a 2-channel approach is taken with the NIR and IR, and ~6.7 µm bands that includes a machine learning approach for optically thick cloud properties. A tradeoff is the potential for reduced accuracy particularly using data from the more advanced satellites that have more spectral channels (e.g. SEVIRI, AHI and ABI) that are known to help improve thin cirrus detection, cloud-aerosol discrimination and estimates in other difficult conditions that challenge cloud remote sensing. The new continuity approach is applied to one month of global GEOSat data for each year of the CERES record since 2000 and compared with the Ed4 GEO and MODIS cloud property time series in order to evaluate the level of improved consistency in the GEOsat record and to assess the accuracy impacts. Cloud fraction will also be assessed with CALIPSO data. Outstanding issues and challenges will be discussed. The results are expected to guide future work needed to develop a more robust GEOsat cloud data record for CERES.

CERES CDR↗
NASA NTRS1981

Soil spectral characterization

The spectral characterization of soils is discussed with particular reference to the bidirectional reflectance factor as a quantitative measure of soil spectral properties, the role of soil color, soil parameters affecting soil reflectance, and field characteristics of soil reflectance. Comparisons between laboratory-measured soil spectra and Landsat MSS data have shown good agreement, especially in discriminating relative drainage conditions and organic matter levels in unvegetated soils. The capacity to measure both visible and infrared soil reflectance provides information on other soil characteristics and makes it possible to predict soil response to different management conditions. Field and laboratory soil spectral characterization helps define the extent to which intrinsic spectral information is available from soils as a consequence of their composition and field characteristics.

Stoner, E. R.↗
NASA NTRSDate not supplied

Analysis of Spacecraft Materials Discrimination Using Color Indices for Remote Sensing for Space Situational Awareness

The increasing number of space missions have resulted in an augmented density of artificial objects positioned in orbital domains near Earth. Knowing the material composition of the resident space object can be of value in object identification and risk assessment using remote sensing techniques. To perform this task, it is increasingly imperative to optically characterize spacecraft materials to identify unique material-specific spectroscopic markers. In this work, a variety of materials frequently utilized by the aerospace industry in spacecraft design and construction were analyzed using reflectance spectroscopy. The collected data provide a spectral characterization baseline for modern-day and historical spacecraft materials. The color index was computed for standard astronomical and suggested theoretical filter passbands and compared to each other in their capability to discriminate materials belonging to different classes. The color index was calculated from reflectance spectra of common spacecraft materials in their pristine, as-received conditions that fell under different family groupings. Different color-index combinations were studied using color-color diagrams. Visual and quantitative analysis of the color-color diagrams were used to evaluate the possibility of discriminating materials from one another by means of optical measurements. Results of the analysis show that polyimide and photovoltaic materials are most easy to discriminate from all other materials via color indices using different filter passbands evaluated in this study.

spectral reflectance↗
NASA NTRS1989

Remote sensing of evaporite mineral zonation in salt flats (salars)

Compositional zoning within Salar de Atacama and Salar de Llulliallaco has been mapped from Landsat Thematic Mapper (TM) data. The data were enhanced using decorrelation stretching of TM bands 7, 5, and 4, which were considered to possess the majority of the mineralogical information. The resulting 7, 5, 4 (red, green, blue) color composites provide excellent discrimination of evaporite mineral zones within the salar. The interpretation is supported by fieldwork at the Salar de Atacama and spectral considerations. A strong relationship between the mineralogy of a unit and surface roughness was observed in the field, hence there is potential for imaging radar to provide complementary zonal data.

Chapman, J. E.↗
NASA NTRS1995

Mid-infrared transmission spectra of crystalline and nanophase iron oxides/oxyhydroxides and implications for remote sensing of Mars

Ferric-iron-bearing materials play an important role in the interpretation of visible to near-IR Mars spectra, and they may play a similarly important role in the analysis of new mid-IR spacecraft spectral observations to be obtained over the next decade. We review exisiting data on mid-IR transmission spectra of ferric oxides/oxyhydroxides and present new transmission spectra for ferric-bearing materials spanning a wide range of mineralogy and crystallinity. These materials include 11 samples of well-crystallized ferric oxides (hematite, maghemite, and magnetite) and ferric oxyhydroxides (goethite, lepidocrocite). We also report the first transmission spectra for purely nanophase ferric oxide samples that have been shown to exhibit spectral similarities to Mars in the visible to near-IR and we compare these data to previous and new transmission spectra of terrestial palagonites. Most of these samples show numerous, diagnostic absorption features in the mid-IR due to Fe(3+) - 0(2-) vibrational transitions, structural and/or bound OH, and/or silicates. These data indicate that high spatial resolution, moderate spectral resolution mid-IR ground-based and spacecraft observations of Mars may be able to detect and uniquely discriminate among different ferric-iron-bearing phases on the Martian surface or in the airborne dust.

Bell, James F., III↗
NASA NTRS1995

Mid-infrared transmission spectra of crystalline and nanophase iron oxides/oxyhydroxides and implications for remote sensing of Mars

Ferric-iron-bearing materials play an important role in the interpretation of visible to near-IR Mars spectra, and they may play a similarly important role in the analysis of new mid-IR spacecraft spectral observations to be obtained over the next decade. We review existing data on mid-IR transmission spectra of ferric oxides/oxyhydroxides and present new transmission spectra for ferric-bearing materials spanning a wide range of mineralogy and crystallinity. These materials include 11 samples of well-crystallized ferric oxides (hematite, maghemite, and magnetite) and ferric oxyhydroxides (goethite, lepidocrocite). We also report the first transmission spectra for purely nanophase ferric oxide samples that have been shown to exhibit spectral similarities to Mars in the visible to near-IR and we compare these data to previous and new transmission spectra of terrestrial palagonites. Most of these samples show numerous, diagnostic absorption features in the mid-IR due to Fe(3+)-O(2-) vibrational transitions, structural and/or bound OH, and/or silicates. These data indicate that high spatial resolution, moderate spectral resolution mid-IR ground-based and spacecraft observations of Mars may be able to detect and uniquely discriminate among different ferric-iron-bearing phases on the Martian surface or in the airborne dust.

Bell, James F., III↗
NASA NTRS1995

Commercial Earth Observation

Through the Earth Observation Commercial Applications Program (EOCAP) at Stennis Space Center, Applied Analysis, Inc. developed a new tool for analyzing remotely sensed data. The Applied Analysis Spectral Analytical Process (AASAP) detects or classifies objects smaller than a pixel and removes the background. This significantly enhances the discrimination among surface features in imagery. ERDAS, Inc. offers the system as a modular addition to its ERDAS IMAGINE software package for remote sensing applications. EOCAP is a government/industry cooperative program designed to encourage commercial applications of remote sensing. Projects can run three years or more and funding is shared by NASA and the private sector participant. Through the Earth Observation Commercial Applications Program (EOCAP), Ocean and Coastal Environmental Sensing (OCENS) developed SeaStation for marine users. SeaStation is a low-cost, portable, shipboard satellite groundstation integrated with vessel catch and product monitoring software. Linked to the Global Positioning System, SeaStation provides real time relationships between vessel position and data such as sea surface temperature, weather conditions and ice edge location. This allows the user to increase fishing productivity and improve vessel safety. EOCAP is a government/industry cooperative program designed to encourage commercial applications of remote sensing. Projects can run three years or more and funding is shared by NASA and the private sector participant.

Source record↗
NASA NTRS2015

Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p less than 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer's accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.

hyperspectral fusion↗
NASA NTRS2012

Sensitivity of Ocean Reflectance Inversion Models for Identifying and Discriminating Between Phytoplankton Functional Groups

The daily, synoptic images provided by satellite ocean color instruments provide viable data streams for observing changes in the biogeochemistrY of marine ecosystems. Ocean reflectance inversion models (ORMs) provide a common mechanism for inverting the "color" of the water observed a satellite into marine inherent optical properties (lOPs) through a combination of empiricism and radiative transfer theory. lOPs, namely the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents, describe the contents of the upper ocean, information critical for furthering scientific understanding of biogeochemical oceanic processes. Many recent studies inferred marine particle sizes and discriminated between phytoplankton functional groups using remotely-sensed lOPs. While all demonstrated the viability of their approaches, few described the vertical distributions of the water column constituents under consideration and, thus, failed to report the biophysical conditions under which their model performed (e.g., the depth and thickness of the phytoplankton bloom(s)). We developed an ORM to remotely identifY Noctiluca miliaris and other phytoplankton functional types using satellite ocean color data records collected in the northern Arabian Sea. Here, we present results from analyses designed to evaluate the applicability and sensitivity of the ORM to varied biophysical conditions. Specifically, we: (1) synthesized a series of vertical profiles of spectral inherent optical properties that represent a wide variety of bio-optical conditions for the northern Arabian Sea under aN Miliaris bloom; (2) generated spectral remote-sensing reflectances from these profiles using Hydrolight; and, (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N Miliaris for each example. By comparing the estimates from the inversion model to those from synthesized vertical profiles, we were able to identifY those bio-optical conditions under which the inversion model performs both well and poorly.

Werdell, P. Jeremy↗
NASA NTRS1972

Iron-absorption band analysis for the discrimination of iron-rich zones

The author has identified the following significant results. Analysis of ERTS-1 images of Nevada has followed two courses: comparative lineament mapping and spectral reflectance evaluation. The comparative lineament mapping was conducted by mapping lineaments on 9 x 9 inch prints of MSS bands 5 and 7, transferring the data to a base map, and comparing the results with existing geologic maps. The most significant results are that lineaments are more numerous on the band 7 images, and approximately 100 percent more were mapped than appear on existing maps. Geologic significance of these newly mapped lineaments will not be known until they are checked in the field: many are probably faults. Spectral analysis has been limited to visual comparison among the four MSS bands. In general, higher scene contrast is shown in the near infrared bands (6 and 7) than in the visible wavelength bands (4 and 5). The economic implications of these results derive chiefly from the greater efficiency that can be obtained by using near infrared as well as visible wavelength images.

Rowan, L. C.↗
NASA NTRS1984

Benchmark data on the separability among crops in the southern San Joaquin Valley of California

Landsat MSS data were input to a discriminant analysis of 21 crops on each of eight dates in 1979 using a total of 4,142 fields in southern Fresno County, California. The 21 crops, which together account for over 70 percent of the agricultural acreage in the southern San Joaquin Valley, were analyzed to quantify the spectral separability, defined as omission error, between all pairs of crops. On each date the fields were segregated into six groups based on the mean value of the MSS7/MSS5 ratio, which is correlated with green biomass. Discriminant analysis was run on each group on each date. The resulting contingency tables offer information that can be profitably used in conjunction with crop calendars to pick the best dates for a classification. The tables show expected percent correct classification and error rates for all the crops. The patterns in the contingency tables show that the percent correct classification for crops generally increases with the amount of greenness in the fields being classified. However, there are exceptions to this general rule, notably grain.

Morse, A.↗
NASA NTRS1994

High sensitivity dynamic spectral search for flare star radio

We observed ten well-known flare stars with the Arcibo radio telescope at 1.4 GHz and 5 GHz, using a special observing technique to discriminate between real flares and radio freqeuncy interference. With a high sensitivity of 5.5 K/Jy at 1.4 GHz when averaged over a 50 MHz band, we are able to recognize flux enhancements as weak as approximately 6 mJy above the sky background variations. In about 85 hours of observation, about a dozen bursts were detected, only from AD Leo. All had flux densities lower than 70 mJy, which probably explains their lack of fine structures (except for the strongest one), such as were reported in the literature for stronger flares. Half of the bursts that we recorded are 100% circularly polarized, and half are not circularly polarized. Our results are a first attempt of reliable statistics on dMe flare rates at 1.4 GHz. The high brightness temperatures we infer for the observed bursts are interpreted in terms of coherent emission processes, either the cyclotron maser instability or plasma radiation. Efficiencies are comparable to those of solar or planetary radio emissions in the case of the cyclotron maser, and higher than the solar efficiency in the case of plasma radiation, with the caveat that there are great uncertainties in the coronal model and the source size.

Abada-Simon, M.↗
NASA NTRS1983

The effect of irradiation and reflectance variability on vegetation condition assessment

Surface reflectance and global irradiance variations across an imaged area determine the minimum signal difference from groups of pixels in different targets needed to discriminate them. The factors affecting such variations and their magnitudes are considered. The sensor output also depends upon the interaction of the spectral response of the sensor and the spectral upwelling radiance from the target. From a consideration of the spectral instrument responses of detectors in the Landsat multispectral scanners (MS), together with measured reflectance factors of a vegetative canopy stressed to different levels of severity, the feasibility of mapping and quantifying disease stress witlh Landsat vegetative indices (VINs) is demonstrated.

Duggin, M. J.↗