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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
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NASA NTRS1981

IUE observations of variability in winds from hot stars

Observations of variability in stellar winds or envelopes provide an important probe of their dynamics. For this purpose a number of O, B, Be, and Wolf-Rayet stars were repeatedly observed with the IUE satellite in high resolution mode. In the course of analysis, instrumental and data handling effects were found to introduce spurious variability in many of the spectra. software was developed to partially compensate for these effects, but limitations remain on the type of variability that can be identified from IUE spectra. With these contraints, preliminary results of multiple observations of two OB stars, one Wolf-Rayet star, and a Be star are discussed.

Grady, C. A.↗
NASA NTRS1990

The EUV dayglow at high spectral resolution

Rocket observations and spectra of the dayglow spectrum of the terrestrial atmosphere between 840 and 1860 A are studied. Three bands of the N2 c-prime 4 system are seen clearly resolved in the dayglow. Analysis of high-resolution N2 Lyman-Birge-Hopfield data shows no anomalous vibrational distribution as has been reported from other observations. Altitude profiles of the observed O and N2 emissions demonstrate that the MSIS-83 model O and N2 densities are appropriate for the conditions of the rocket flights.

Morrison, M. D.↗
NASA NTRS1992

From Mars to Greenland: Charting gravity with space and airborne instruments - Fields, tides, methods, results

This symposium on space and airborne techniques for measuring gravity fields, and related theory, contains papers on gravity modeling of Mars and Venus at NASA/GSFC, an integrated laser Doppler method for measuring planetary gravity fields, observed temporal variations in the earth's gravity field from 16-year Starlette orbit analysis, high-resolution gravity models combining terrestrial and satellite data, the effect of water vapor corrections for satellite altimeter measurements of the geoid, and laboratory demonstrations of superconducting gravity and inertial sensors for space and airborne gravity measurements. Other papers are on airborne gravity measurements over the Kelvin Seamount; the accuracy of GPS-derived acceleration from moving platform tests; airborne gravimetry, altimetry, and GPS navigation errors; controlling common mode stabilization errors in airborne gravity gradiometry, GPS/INS gravity measurements in space and on a balloon, and Walsh-Fourier series expansion of the earth's gravitational potential.

Colombo, Oscar L.↗
NASA NTRS1996

HRI observations of the Pleiades

The preliminary analysis of the data from the first four Rosat high resolution imager (HRI) pointings provided many new faint Pleiades detections. The completion of the high resolution survey of the most source-confused regions of this open cluster will lead to the construction of proper X-ray luminosity functions and will yield a definitive assessment of the coronal emission of the Pleiades members.

Harnden, F. R., Jr.↗
NASA NTRS2010

Evidence for Basinwide Mud Volcanism in Acidalia Planitia, Mars

High-albedo mounds in Acidalia Planitia occur in enormous numbers. They have been variously interpreted as pseudocraters, cinder cones, tuff cones, pingos, ice disintegration features, or mud volcanoes. Our work uses regional mapping, basin analysis, and new data from the Context Camera (CTX), High Resolution Imaging Science Experiment (HiRISE), and Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) to re-assess the origin and significance of these structures.

Oehler, Dorothy Z.↗
NASA NTRS2017

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS-national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91 percent was achieved, which is a 6 percent improvement in unmixing based classification relative to per-pixel-based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

Subpixel↗
NASA NTRS2012

Loop Evolution Observed with AIA and Hi-C

In the past decade, the evolution of EUV loops has been used to infer the loop substructure. With the recent launch of High Resolution Coronal Imager (Hi-C), this inference can be validated. In this presentation we discuss the first results of loop analysis comparing AIA and Hi-C data. In the past decade, the evolution of EUV loops has been used to infer the loop substructure. With the recent launch of High Resolution Coronal Imager (Hi-C), this inference can be validated. In this presentation we discuss the first results of loop analysis comparing AIA and Hi-C data.

Mulu-Moore, Fana↗
NASA NTRSDate not supplied

WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring

Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as the optical and SAR data proves high resolution (5-10 m) imagery, and SAR data is unaffected by cloud cover and light availability (day vs. night), which are common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a MODIS snow mask product to mask global snow coverage, which would affect land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd watershed located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management..

Lori Berberian↗
NASA NTRS1998

Neutral Networks for Subpixel Classification of Multispectral Images

In this work, the implementation and use of AVHRR (Advanced Very High Resolution Radiometer) images for subpixel analysis is studied. The work consists of two parts, the first is making training data, the second is using the training data to design a neural net subpixel analyzer. Most work on subpixel analysis has been done with images with more spectral bands. AVHRR images were chosen because of their easy acquisition, and because the five spectral bands allow investigation into the development of training data. The first step in subpixel analysis is the development of training data. This consists of image to be classified, and the classification of each pixel. In order to do the classification, a high spatial resolution image is typically needed in order to manually create a classified image. It is difficult to have both the image of interest, and a high spatial resolution image of the same area taken at the same time. Thus it was studied whether a subsampled image taken from the image of interest could serve as the training data. Statistical work has been done showing the unusefulness of this approach. In the second part of the analysis, a feedforward neural net was trained and used to classify the AVHRR images. Results of these tests, comparing the neural net with typical statistical based schemes are shown.

Figueroa, Ricardo R.↗
NASA NTRSDate not supplied

SatCORPS Global Cloud Composite (GCC): the Design and Delivery of A High Quality, High Resolution, Global Cloud Product Available in Near-Real Time

The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) supports the development of an analysis ready and cloud-optimized data transformation pipeline and geospatial service enablement of a global cloud composite (GCC) product derived from global geostationary satellite imagery. This geospatial service will be available at high temporal and spatial resolution via the SatCORPS web mapping application for visualization and analysis as well as direct ingestion to common geospatial software and custom programming. The resulting global cloud composite products from the processing pipeline can then be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. Near real time global observations are created through the composition of five geostationary satellites that provides modelling and forecasting communities with the capability to provide high quality and timely information to start the projection process. The Global Cloud Composite product combines information from geostationary satellites, GOES-16, GOES-17, Himawari-8, Meteosat-11 and Meteosat-9 to create a single global composite netcdf file and images using the different products within the netcdf file. The SatCORPS team, though our Global Cloud Composite (GCC) product and web-based visualization tools including Geographical Information System (GIS) services provide near real time global cloud product information to both automated processes and traditional web users that is timely and high quality derived from geostationary satellites. The Global Cloud Composite product takes advantage of the scalable processing resources provided by the AWS batch service to provide new composites every thirty minutes. Because information from each of the low earth orbiting satellites is available on schedules tuned to the specific satellite, the processing algorithm temporally composites the final dataset as each satellite’s information becomes available. The SatCORPS team has leveraged our experience using Amazon Web Services (AWS) to build a low latency high availability tool that allows end users both human and automated to acquire high quality and high-resolution Geostationary Earth Orbiting (GEO) information at zero cost to the end user. This presentation will describe how we architected and implemented the service as well as lessons learned based on our experiences both developing and operating the system. The lessons learned include how we integrated multiple services including Amazon Batch, Amazon S3 and Amazon Lambda service to create a low cost but high-performance processing system that is capable of identifying and processing the most appropriate satellite overpass information into global cloud composites. We will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global composited cloud research products with very low latency that we see that as filling a rapidly growing need in the research and modelling community with no up-front nor ongoing costs associated with downloading or using the information.

AWS AMCE SMCE GCC SATCORPS GLOBAL CLOUD COMPOSITE ↗
NASA NTRS1992

Geologic remote sensing - New technology, new information

Results of geologic studies using data collected by the NASA/JPL Thermal Infrared Imaging Spectrometer (TIMS), Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the Airborne Synthetic Aperture Radar (AIRSAR) are discussed. These instruments represent prototypes for the Earth Observing System (EOS) satellite instruments ASTER, High Resolution Imaging Spectrometer (HIRIS), and EOS SAR. Integrated analysis of this data type is one of the keys to successful geologic research using EOS. TIMS links the physical properties of surface materials in the 8-12-*mm region to their composition. Calibrated aircraft data make direct lithological mapping possible. AVIRIS, an analog for HIRIS, provides quantitative information about the surface composition of materials based on their detailed visible and infrared spectral signatures (0.4-2.45 mm). Calibrated AVIRIS data make direct identification of minerals possible. The AIRSAR provides additional complementary information about the surface morphology of rocks and soils.

Kruse, F. A.↗
NASA NTRS1991

Determination of absolute strengths of N2 quadrupole lines from high-resolution ground-based IR solar observations

The strength of S-branch lines of the N2 (1-0) electric quadrupole vibration-rotation band are determined by an analysis of solar absorption spectra. The solar data were recorded with a Fourier transform spectrometer and are characterized by high resolution, and a high signal-to-noise ratio. By extrapolating equivalent width measurements of the lines from varying air masses to zero air mass, the line strengths are found for the transitions from S7 to S10. The results presented do not include half widths and are found to be accurate to within 5 percent, and following a redetermination the N2 transitions are accurate to within 0.0002/cm. Line-of-sight atmospheric air masses associated with remotely sensed IR spectroscopic observations can be determined directly by utilizing the highly accurate data.

Demoulin, P.↗
NASA NTRS1993

Recovery of atmospheric water vapor total column abundance from imaging spectrometer data around 940 nm - Sensitivity analysis and application to Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data

Two simple techniques (Continuum Interpolated Band Ratio, CIBR, and Narrow/Wide ratio, N/W) to retrieve path precipitable water from AVIRIS high spectral resolution radiance data using the 940 nm water absorption band are compared. A sensitivity analysis was performed using the radiative transfer code LOWTRAN 7 to determine which one of these two approaches will provide a better estimate over land and water areas. The CIBR proved to be the technique less sensitive to perturbing effects, except for errors in visibility estimate. Both techniques were applied to AVIRIS radiance data acquired over Salton Sea, California. Resulting images confirmed that the use of a constant gray reflectance in the model led to a higher overestimation of the amount of water retrieved for N/W over vegetated areas. Validation was performed through comparison between an independent estimate of water vapor from concurrent Reagan sunphotometer measurements and AVIRIS estimates. Amounts retrieved using the N/W approach match more closely in situ measurements, even after adjusting model parameters for background reflectance, viewing geometry, and type of aerosol at the site.

Carrere, Veronique↗
NASA NTRS1984

High resolution GLAS on the MCIDAS

The GLAS physical inversion method for analysis of HIRS2/MSU data was implemented on the McIDAS. The method of analysis is identical to that used in processing global retrievals for six months of 1979, with the exception that the McIDAS retrievals are done on a higher spatial resolution, with one sounding attempted in every 4 x 4 array of HIRS2 spots, corresponding to roughly 80 x 80 km at nadir. This 4 x 4 array is further subdivided in 4 2 x 2 arrays with the sounding being performed utilizing all the spots in the single warmest 2 x 2 quadrant as sensed by the 11 micrometer window channel. Whether accurate retrievals can be performed on the high resolution grid without editing was determined. Different retrievals for a synoptic situation was compared and the guess dependence of the high resolution GLAS retrievals were examined. The orbit crossing the central United States at 1/21/79 09257 was studied. Radiosondes at 1200Z were used for comparison.

Susskind, J.↗
NASA NTRS1988

Arctic Sea ice studies with passive microwave satellite observations

The objectives of this research are: (1) to improve sea ice concentration determinations from passive microwave space observations; (2) to study the role of Arctic polynyas in the production of sea ice and the associated salinization of Arctic shelf water; and (3) to study large scale sea ice variability in the polar oceans. The strategy is to analyze existing data sets and data acquired from both the DMSP SSM/I and recently completed aircraft underflights. Special attention will be given the high resolution 85.5 GHz SSM/I channels for application to thin ice algorithms and processes studies. Analysis of aircraft and satellite data sets is expected to provide a basis for determining the potential of the SSM/I high frequency channels for improving sea ice algorithms and for investigating oceanic processes. Improved sea ice algorithms will aid the study of Arctic coastal polynyas which in turn will provide a better understanding of the role of these polynyas in maintaining the Arctic watermass structure. Analysis of satellite and archived meteorological data sets will provide improved estimates of annual, seasonal and shorter-term sea ice variability.

Cavalieri, D. J.↗
NASA NTRS1998

Giant Molecular Clouds and High-Mass Star Formation in the Milky Way

We are conducting an extensive investigation of high-mass (OB) star formation within the dense cores of giant molecular clouds (GMCS) throughout the first Galactic quadrant of the Milky Way using enhanced resolution Infrared Astronomical Satellite (IRAS) images in combination with high-resolution ground-based observations in millimeter wave molecular transitions and radio continuum. As part of this investigation several resolution enhancement algorithms are applied to the IRAS data, including the HIgh RESolution (HIRES) algorithm developed at the IRAS Processing and Analysis Center (IPAC), as well as others ("pixon" image reconstruction). In addition, as part of a related study, we have completed a large survey of the CO emission in the first Galactic quadrant using the 15-element array detector (QUARRY) with the Five College Radio Astronomy Observatory (FCRAO) 14 m antenna, which provides sampling at an angular resolution of 50", comparable to that attained in the reprocessed IRAS data. Both of these data sets are compared with a sample of ultra-compact (UC) H II regions taken from a high-resolution multi-wavelength (6 and 20 cm) radio survey of the Galactic plane using the NRAO Very Large Array (VLA). Selected regions are observed in 1.3 mm continuum, which has proven to be particularly sensitive to the dust column density. Extensive observations of molecular clouds at high resolution in CO, CS and HCN are combined with the reprocessed IRAS high-resolution images to give a more complete picture of the physical conditions and kinematics of high-mass star forming GMCS. Our goals are to study in detail the morphology, structure, and rate of high-mass star formation within GMCs throughout the Galactic disk from the inner edge of the molecular ring to the outer Galaxy.

Source record↗
NASA NTRS2007

Measuring a Precise Ultra-Lightweight Spaceflight Mirror on Earth: The Analysis of the SHARPI PM Mirror Figure Data during Mirror Processing at GSFC

The SHARPI (Solar High Angular Resolution Photometric Imager) primary mirror is a 5kg, 0.5m paraboloid, diffraction limited at FUV wavelengths when placed in a 0-G environment. The ULE sandwich honeycomb mirror and the attached mount pads were delivered by ITT (then Kodak) in 2003 to NASA s Goddard Space Flight Center (GSFC). At GSFC, we accepted, coated, mounted, and vibration tested this mirror in preparation for flight on the PICTURES (Planet Imaging Concept Testbed Using a Rocket Experiment) mission. At each step, the integrated analysis of interferometer data and FEA models was essential to quantify the 0-G mirror figure. This task required separating nanometer sized variations from hundreds of nanometers of gravity induced distortion. The ability to isolate such features allowed in-situ monitoring of mirror figure, diagnosis of perturbations, and remediation of process errors. In this paper, we describe the technical approach used to achieve these measurements and overcome the various difficulties maintaining UV diffraction-limited performance with this aggressively lightweighted mirror.

Antonille, Scott↗