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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Temperature dependence of Lorentz air-broadening and pressure-shift coefficients of (12)CH4 lines in the 2.3-micron spectral region

High-resolution (0.01/cm) absorption spectra of lean mixtures of CH4 in dry air were recorded with the McMath-Pierce Fourier transform spectrometer (FTS) of the National Solar Observatory on Kitt Peak at various temperatures between 24 and -61 C. The spectra have been analyzed to determine the values at room temperature of pressure-broadened widths and pressure-induced shifts of more than 740 transitions. The temperature dependence of air-broadened widths and pressure-induced shifts was deduced for approx. 370 transitions in the nu(sub 1) + nu(sub 4), nu(sub 3) + nu(sub 4), and nu(sub 2) + nu(sub 3) bands of (12)CH4 located between 4118 and 4615/cm. These results were obtained by analyzing a total of 29 spectra simultaneously using a multi-spectral non-linear least-squares fitting technique. This new technique allowed the determination of correlated spectral line parameters (e.g. intensity and broadening coefficient) better than the procedure of averaging values obtained by fitting the spectra individually. This method also provided a direct determination of the uncertainties in the retrieved parameters due to random errors. For each band analysed in this study the dependence of the various spectral line parameters upon the tetrahedral symmetry species and the rotational quantum numbers of the transitions is also presented.

Devi, V. Malathy↗
NASA NTRS1996

Development of the SEASIS instrument for SEDSAT

Two SEASIS experiment objectives are key: take images that allow three axis attitude determination and take multi-spectral images of the earth. During the tether mission it is also desirable to capture images for the recoiling tether from the endmass perspective (which has never been observed). SEASIS must store all its imagery taken during the tether mission until the earth downlink can be established. SEASIS determines attitude with a panoramic camera and performs earth observation with a telephoto lens camera. Camera video is digitized, compressed, and stored in solid state memory. These objectives are addressed through the following architectural choices: (1) A camera system using a Panoramic Annular Lens (PAL). This lens has a 360 deg. azimuthal field of view by a +45 degree vertical field measured from a plan normal to the lens boresight axis. It has been shown in Mr. Mark Steadham's UAH M.S. thesis that his camera can determine three axis attitude anytime the earth and one other recognizable celestial object (for example, the sun) is in the field of view. This will be essentially all the time during tether deployment. (2) A second camera system using telephoto lens and filter wheel. The camera is a black and white standard video camera. The filters are chosen to cover the visible spectral bands of remote sensing interest. (3) A processor and mass memory arrangement linked to the cameras. Video signals from the cameras are digitized, compressed in the processor, and stored in a large static RAM bank. The processor is a multi-chip module consisting of a T800 Transputer and three Zoran floating point Digital Signal Processors. This processor module was supplied under ARPA contract by the Space Computer Corporation to demonstrate its use in space.

Maier, Mark W.↗
NASA NTRS1996

Was the MSSTA 2 mission successful?

The Multi-Spectral Solar Telescope Array (MSSTA) is a rocket borne solar observatory designed to address a wide range of scientific questions relating to two aspects of the structure and dynamics of the solar atmosphere: (1) The heating and dynamics of chromospheric and coronal structures including spicules, coronal loops, bright points, and planes; and the role of the fine scale structure of the chromospheric network in the transport of mass and energy between these structures, and (2) The large scale structures of the corona, including the interface of prominences and filaments with material at coronal temperatures, the transition region structure of coronal holes and plumes, and their relationship to the solar wind. In order to address these fundamental scientific problems, the observational objective of the MSSTA is to obtain a set of high resolution spectroheliograms with the following properties: (1) Sufficiently broad spectral coverage and accurate photometry to allow modeling of structures covering the full range of temperatures observed in non-flaring chromosphere/corona, 10(exp 4) K to 10(exp 7) K; (2) Sufficient spectral resolution (lambda / delta lambda approx. 30-100) in each spectroheliogram to allow isolation of the emission from lines excited over a narrow range of temperatures; (3) To address objective (a), spatial resolution sufficient to resolve structures on the sun on a scale of 100-200 km (0.1-0.3 arc seconds); to address objective (b), images of the full disk and inner corona with resolution at least 1.0 arc second, and high sensitivity images of the extended corona (to approx. 3-4 solar radii above the limb) with resolution of approx. 3 arc seconds; for both objectives (c), direct measurements of the coronal magnetic field. (4) To access the role of non-thermal phenomena in the heating and dynamics of the chromosphere/corona interface, high resolution (lambda / delta lambda greater than 1000) spectroheliograms with spatial resolution of 1-3 arc seconds.

Spencer, Dwight C.↗
NASA NTRS1996

A technique for determining cloud free vs cloud contaminated pixels in satellite imagery

Since the first earth orbiting satellite sent pictures of the earth back to them, atmospheric scientists have been focused on the possibilities of using that information as both a forecasting tool and as a meteorological research tool. With the latest generation of Geostationary Operational Environmental Satellites (GOES) now entering service, that view of the earth yields views at a frequency and resolution never before available. These satellites have imagers with a five band multi-spectral capability with high spatial resolution. In addition, the sounder has eighteen thermal infrared (IR) channels plus one low-resolution visible band. With a resolution as small as one kilometer, GOES provides scientists with a powerful eye on the atmosphere. Menzel and Purdom (1994) detail both the imager and sounder capability as well as other systems on the GOES satellites. Immediately apparent in the visible channel are the patterns of clouds swirling over both oceans and continents. These clouds range in size from huge planetary systems covering thousands of kilometers to puffy fair weather cumulus clouds on the order of half a kilometer in size. With the IR sensors temperature patterns are observed. High clouds appear very cold, while low stratus field show temperatures near that of the surface. The surface, in turn, generally appears warmer than the clouds. It would seem then a simple manner to determine cloud and surface temperature from the imagery, but such is not the case. While most of the atmospheric constituents are well mixed and homogeneous, water vapor is not. The water molecule, because of its unique structure and vibration modes, affects the transmittance of the atmosphere most notably in the infrared regions. There are regions of the IR spectrum where water vapor acts as a strong absorber, and at others it is nearly transparent. The transparent wavelengths are called windows, and one such window occurs at 11.2 microns. Adjacent to this window at 12.7 microns which is strongly absorbed by water vapor. These two wavelengths form what is known as a split window, the utility of which was used. Using the linearized form of the radiative transfer equation, they were able to use the split window to determine the amount of water vapor present in the atmosphere. Jedlovec developed the physical split-window (PSW) technique which determines the integrated water content (IWC). The PSW method using Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) found on the older versions of the GOES satellites was used. Recently, Jedlovec and colleagues have been attempting to apply the PSW method using full disk IR imagery obtained by the new generation of GOES satellites. IWC is essential for improved analysis and prediction of convective storms which have been observed to develop in regions of both strong and rapidly evolving moisture gradients. It has also been used in the prediction of clouds and precipitation.

Wohlman, Richard A.↗
NASA NTRS1998

Theoretical Calculation and Validation of the Water Vapor Continuum Absorption

The primary objective of this investigation is the development of an improved parameterization of the water vapor continuum absorption through the refinement and validation of our existing theoretical formalism. The chief advantage of our approach is the self-consistent, first principles, basis of the formalism which allows us to predict the frequency, temperature and pressure dependence of the continuum absorption as well as provide insights into the physical mechanisms responsible for the continuum absorption. Moreover, our approach is such that the calculated continuum absorption can be easily incorporated into satellite retrieval algorithms and climate models. Accurate determination of the water vapor continuum is essential for the next generation of retrieval algorithms which propose to use the combined constraints of multi-spectral measurements such as those under development for EOS data analysis (e.g., retrieval algorithms based on MODIS and AIRS measurements); current Pathfinder activities which seek to use the combined constraints of infrared and microwave (e.g., HIRS and MSU) measurements to improve temperature and water profile retrievals, and field campaigns which seek to reconcile spectrally-resolved and broad-band measurements such as those obtained as part of FIRE. Current widely used continuum treatments have been shown to produce spectrally dependent errors, with the magnitude of the error dependent on temperature and abundance which produces errors with a seasonal and latitude dependence. Translated into flux, current water vapor continuum parameterizations produce flux errors of order 10 W/ml, which compared to the 4 W/m' magnitude of the greenhouse gas forcing and the 1-2 W/m' estimated aerosol forcing is certainly climatologically significant and unacceptably large. While it is possible to tune the empirical formalisms, the paucity of laboratory measurements, especially at temperatures of interest for atmospheric applications, preclude tuning the empirical continuum models over the full spectral range of interest for remote sensing and climate applications. Thus, we propose to further develop and refine our existing far-wing formalism to provide an improved treatment applicable from the near-infrared through the microwave. Based on the results of this investigation, we will provide to the remote sensing/climate modeling community a practical and accurate tabulation of the continuum absorption covering the near-infrared through the microwave region of the spectrum for the range of temperatures and pressures of interest for atmospheric applications.

Ma, Qiancheng↗
NASA NTRS1997

Chromospheric and Coronal Structure of Polar Plumes: Magnetic Structure and Radiative Energy Balance - 1

The Multi-Spectral Solar Telescope Array (MSSTA), a rocket-borne solar observatory, was successfully launched from White Sands Missile Range, New Mexico, on May 13, 1991 at 19:05 UT. The telescope systems onboard the MSSTA obtained several full disk solar images in narrow bandpasses centered around strong soft X-ray, EUV, and FUV emission lines. Each telescope was designed to be sensitive to the coronal plasmas at a particular temperature, for seven temperatures ranging from 20,000 K to 4,000,000 K. We report here on the images obtained during the initial flight of the MSSTA, and on the chromospheric and coronal structure of polar plumes observed over both poles of the Sun. We have also co-aligned the MSSTA images with Kitt Peak magnetograms taken on the same day. We are able to positively identify the magnetic structures underlying the polar plumes we analyze as unipolar. We discuss the plume observations and present a radiative energy balance model derived from them.

Allen, Maxwell J.↗
NASA NTRS1998

A Photo Album of Earth Scheduling Landsat 7 Mission Daily Activities

Landsat7 is a member of a new generation of Earth observation satellites. Landsat7 will carry on the mission of the aging Landsat 5 spacecraft by acquiring high resolution, multi-spectral images of the Earth surface for strategic, environmental, commercial, agricultural and civil analysis and research. One of the primary mission goals of Landsat7 is to accumulate and seasonally refresh an archive of global images with full coverage of Earth's landmass, less the central portion of Antarctica. This archive will enable further research into seasonal, annual and long-range trending analysis in such diverse research areas as crop yields, deforestation, population growth, and pollution control, to name just a few. A secondary goal of Landsat7 is to fulfill imaging requests from our international partners in the mission. Landsat7 will transmit raw image data from the spacecraft to 25 ground stations in 20 subscribing countries. Whereas earlier Landsat missions were scheduled manually (as are the majority of current low-orbit satellite missions), the task of manually planning and scheduling Landsat7 mission activities would be overwhelmingly complex when considering the large volume of image requests, the limited resources available, spacecraft instrument limitations, and the limited ground image processing capacity, not to mention avoidance of foul weather systems. The Landsat7 Mission Operation Center (MOC) includes an image scheduler subsystem that is designed to automate the majority of mission planning and scheduling, including selection of the images to be acquired, managing the recording and playback of the images by the spacecraft, scheduling ground station contacts for downlink of images, and generating the spacecraft commands for controlling the imager, recorder, transmitters and antennas. The image scheduler subsystem autonomously generates 90% of the spacecraft commanding with minimal manual intervention. The image scheduler produces a conflict-free schedule for acquiring images of the "best" 250 scenes daily for refreshing the global archive. It then equitably distributes the remaining resources for acquiring up to 430 scenes to satisfy requests by international subscribers. The image scheduler selects candidate scenes based on priority and age of the requests, and predicted cloud cover and sun angle at each scene. It also selects these scenes to avoid instrument constraint violations and maximizes efficiency of resource usage by encouraging acquisition of scenes in clusters. Of particular interest to the mission planners, it produces the resulting schedule in a reasonable time, typically within 15 minutes.

Potter, William↗
NASA NTRS1998

Back in Time

Under a Jet Propulsion Laboratory SBIR (Small Business Innovative Research), Cambridge Research and Instrumentation Inc., developed a new class of filters for the construction of small, low-cost multispectral imagers. The VariSpec liquid crystal enables users to obtain multi-spectral, ultra-high resolution images using a monochrome CCD (charge coupled device) camera. Application areas include biomedical imaging, remote sensing, and machine vision.

Source record↗
NASA NTRS1995

Sensitivity of Multi-Angle Remote Sensing Observations to Aerosol Sphericity

Multi-angle, multi-spectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) Multi-angle Imaging SpectroRadiometer (MISR), can distinguish spherical from non-spherical particles over calm ocean for mineral-dust-like particles with the range of sizes and column amounts expected under natural conditions. The ability to make such distinctions is critical if remote sensing of atmospheric aerosol properties is to provide significant new contributions to our understanding of the global-scale, clear-sky solar radiation balance.

MISR aerosol aerosol properties↗
NASA NTRS1994

Lossless Compression and Rate Control for the Galileo NIMS Experiment

The Galileo Near-Infrared Mapping Spectrometer (NIMS) is a sophisticated multi-spectral instrument that was developed to study the spatial/compositional aspects of the atmosphere of Jupiter and the surfaces of it's satellites. Since its original development, the communication capability of the Galileo spacecraft has been severly reduced as the result of a failure of ground controllers to open the main antenna. The data rate which will be available for all instruments at the first Jupiter encounter in 1995 has been reduced by several orders of magnitude (even after recent numerous improvements to data link efficiency.).

data compression NIMS instrument Galileo↗
NASA NTRS1994

Development of an Aerosol Opacity Retrieval Algorithm for Use with Multi-Angle Land Surface Images

In 1998, the Multi-angle Imaging SpectroRadiometer (MISR) will fly aboard the EOS-AM1 spacecraft. MISR will enable unique methods for retrieving the properties of atmospheric aerosols, by providing global imagery of the Earth at nine viewing angles in four visible and near-IR spectral bands. As part of the MISR algorithm development, theoretical methods of analyzing multi-angle, multi-spectral data are being tested using images acquired by the airborne Advanced Solid-State Array Spectroradiometer (ASAS). In this paper we derive a method to be used over land surfaces for retrieving the change in opacity between spectral bands, which can then be used in conjunction with an aerosol model to derive a bound on absolute opacity.

Advanced Solid-State Array Spectroradiometer ASAS ↗
NASA NTRS1994

A New Generation of Intelligent Trainable Tools for Analyzing Large Scientific Image Databases

In a variety of scientific disciplines two-dimensional digital image data is now relied on as a basic component of routine scientific investigation. The proliferation of image acquisition hardware such as multi-spectral remote-sensing platforms, medical imaging sensors, and high-resolution cameras have led to the widespread use of image data in fields such as atmospheric studies, planetary geology, ecology, agriculture, glacielogy, forestry, astronomy, diagnostic medicine, to name but a few.

machine↗
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↗
NASA NTRS1996

Evolution of Imaging Spectrometry: Past, Present and Future

An overview of the physical principals of imaging spectrometry for detailed characterization of remote objects and of gas vapors is given. The terms Multi-spectral, Hyperspectral, and Ultra-spectral are defined within the framework of applications and instrument system design approaches.

imaging↗
NASA NTRS2026

Satellite Optical Remote Sensing of Clouds and Aerosols: From Particle Single-Scattering and Gaseous Absorption Through Radiative Transfer to Retrieval Products

Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.

Aerosols↗
DOE OSTI2025

Hyper Spectral Anomaly Detection

Anomaly detection is a common machine learning (ML) task with growing importance in the fields of imaging, quality assurance, and multiple security related disciplines. Anomaly detection is more difficult than traditional machine learning methods due to the inherent unlabeled nature of the datasets. Existing anomaly detection architectures commonly face challenges with explainability, retaining information related to the relational structure of the data, and false positive rates. Hyperspectral Imaging Anomaly Detection (HSI) is a statistical model that employs vertex and edge weighted graphs to preserve the data’s relationships on different topographical scales. The model is able to generalize from anomaly detection in 2D images to novel datasets related to cyber-security. Furthermore, the use of multi-spectral and other filtering methods results in fewer false positives and increases the explainability of model predictions. When applying HSI to cyber-security datasets, we are able to successfully detect malicious activity with a relatively high degree of accuracy.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Integrating AI and Multi-sensor Technology for better Bioenergy Preprocessing

Integrating multi-sensor identification with machine learning significantly enhances bioenergy preprocessing by using non-destructive, multi-spectral sensors to improve feedstock purity and quality. This approach not only reduces preprocessing costs but also ensures a more efficient and sustainable bioenergy production process.

09 - BIOMASS FUELS↗