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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Conceptual design of an optic based engine control system

Use of optics in the aircraft engine control systems would provide immunity to electromagnetic effects (such as lightning, radar, and nuclear pulses) for flight and propulsion control systems located throughout the aircraft and in need of communication and would result in weight reduction. This paper discusses a conceptual design of an optic engine control system that is being developed by the Fiber Optic Control System Integration (FOCSI) program. The features inherent in each of the optic-based components of the optic system, which includes the on-engine full authority digital electonic control, optic sensors, optic-based actuators, and an optic data bus for communication with the aircraft flight control system are described in detail. The diagrams of the FOCSI control system and its components are included.

Davies, W. J.↗
NASA NTRS1979

Multisensor analysis of hydrologic features in the Wind River Range, Wyoming with emphasis on the SEASAT SAR

The author has identified the following significant results. Analysis of imagery obtained over west-central Wyoming indicates that Seasat SAR has capability for hydrologic mapping. Both the L-Band (Seasat) and the X-Band (aircraft) SAR imagery were useful for observing drainage detail. Streams have bright signatures on the SAR imagery because the riparian vegetation produces a rough surface and thus high radar returns. Lakes appear relatively bright on the Seasat image presumably in response to surface ripples and waves induced by wind action. SAR imagery did not reveal snow at either the 23.5 cm (L-Band) or 2.8 cm (X-Band) wavelengths. Comparing Seasat and X-Band aircraft SAR imagery to LANDSAT RBV imagery, U-2 photography, and topographic maps of the Wind River Range, it appears that the SAR data do not seem to provide as much hydrologic information as do the other sensors in the visible and near infrared portions of the spectrum.

Foster, J. L.↗
NASA NTRS1987

L-band radar backscatter modeling of forest stands

An L-band HH radar backscatter model of a coniferous forest stand is described and compared with SIR-B L-band image data of the Mount Shasta region of northern California. Being based upon an identification and implementation of the expected major components of forest backscattering, the model is simple in form and thus fast computationally, making possible extensive simulations of forest stands. A particularly important component in the model relates to representing the specular reflections expected from tree trunks to the ground and then back to the sensor. These are strong returns and are seen to be necessary to explain both the forest measurements made by the authors and the observations of others. Although the experimental data is limited in quantity and quality, agreement between available experimental and simulated values of forest backscatter is better than the residual uncertainty and relative calibration error of the experimental data, provided the model and experiment are matched initially at one set of parameter values.

Richards, John A.↗
DOE OSTI2017

Vehicle track segmentation using higher order random fields

Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure on a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Windshear detection - Airborne system perspective

Functional requirements for airborne windshear detection and warning are discussed based on performance criteria of remote sensor devices such as Doppler radar, Doppler laser radar, and infrared radiometric techniques. These types of sensors are considered able to detect hazardous windshear conditions and provide adequate warning time for the flight crew to escape the encounter. Radar simulation and analysis show that windshear from microbursts can be detected. The Doppler systems can provide line-of-sight information from a region extending 2-4 km in front of the aircraft. The temperature drop associated with the formation of windshear can be measured by an airborne infrared radiometer which compares emission from CO2 in the immediate neighborhood of the aircraft to the emissions from CO2 in the air 4-5 km away. It is suggested that an integration of airborne sensor and ground derived data can support microburst avoidance.

Bowles, Roland L.↗
NASA NTRSDate not supplied

Mapping National Forest Aboveground Biomass in Mexico by Integrating GEDI, Sentinel‐1 and Sentinel‐2 Data

Accurate mapping of forest aboveground biomass density (AGBD) is required to better understand the role of forests in the global carbon cycle and to support international policies for climate change mitigation and adaptation. Mexico is one of the countries having great potential for the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (or UN-REDD program) and there is a growing demand for unbiased Monitoring Reporting Verification systems at a national level. As an effort under NASA’s Carbon Monitoring System (CMS) program, we developed a machine learning model using multi-stream remote sensing measurements as well as topographic data to create a high spatial resolution AGBD map (~100 m) over Mexico (circa 2020). The remote sensing data includes Global Ecosystem Dynamic Investigation (GEDI) lidar, Sentinel 1 Synthetic-Aperture Radar (SAR), and Sentinel-2 multispectral imagery (MSI). GEDI onboard the International Space Station provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. Our analysis indicates that the developed random forest model can capture 63 % of the spatial variation (RMSE = 33.7 Mg/ha) of AGBD of Mexican forests. We find that shortwave infrared bands of Sentinel-2 MSI and topographical variables from elevation data are the most important variables in the developed AGBD model. Our study highlights methodological opportunities in synergistic uses of multiple sensors for large-scale forest AGBD mapping and shows potential for retrospective analysis and operational monitoring of forest AGBD and its dynamics.

Taejin Park↗
NASA NTRS1981

Satellite detection of oil on the marine surface

The ability of two widely dissimilar spaceborne imaging sensors to detect surface oil accumulations in the marine environment has been evaluated using broadly different techniques. Digital Landsat multispectral scanner (MSS) data consisting of two visible and two near infrared channels has been processed to enhance contrast between areas of known oil coverage and background clean surface water. These enhanced images have then been compared to surface verification data gathered by aerial reconnaissance during the October 15, 1975, Landsat overpass. A similar evaluation of oil slick imaging potential has been made for digitally enhanced Seasat-A synthetic aperture radar (SAR) data from July 18, 1979. Due to the premature failure of this satellite, however, no concurrent surface verification data were collected. As a substitute, oil slick configuration information has been generated for the comparison using meteorological and oceanographic data. The test site utilized in both studies was the extensive area of natural seepage located off Coal Oil Point, adjacent to the University of California, Santa Barbara.

Wilson, M. J.↗
NASA NTRS1995

Evaluation of passive microwave precipitation algorithms in wintertime midlatitude situations

The second intercomparison project of the Global Precipitation Climatology Project (GPCP) examined the estimation of midlatitude, cool-season precipitation. As part of that effort, the authors report here on the results of two microwave techniques, the Goddard scattering algorithm and the physical retrieval algorithm of Kummerow. Results from the estimation of instantaneous rain rate for five overpasses of the Special Sensor Microwave/Imager (SSM/I) are presented in a case study mode to illustrate both the strong and weak points of each technique. These five cases represent a sampling of the various types of precipitating systems observed. Results for the complete set of 20 swaths chosen by the United Kingdom Meteorological Office (UKMO) are then categorized by scatterplots and statistics of instantaneous radar versus microwave-estimated rain rate, rain no-rain contingency tables, and scatterplots of areal coverage of rainfall. Neither algorithm produced a good statistical correlation with the radar data, yet in general, both did well at determining rainy areas. Two reasons are suggested for the low correlation coefficients between both algorithms and the radar data. Time differences between the SSM/I overpass and the radar observations can occasionally account for some of the differences. The primary reason for the low correlations, however, appears to be the predominance of very light rain in the area of interest during the winter. Both algorithms are in good spatial agreement with the radar when the radar data are restricted to rates above 1 mm/h. When all radar rain rates are included, the radar areal coverage increases by as much as a factor of 10 in some cases. Because the Kummerow algorithm does not handle such low rain rates over land very well, and because the Goddard scattering algorithm uses 1 mm/h as the minimum reliably detectable rain rate, regimes that contain large areas of very light rain present inherent difficulties for these retrieval methods. Therefore, the proliferation of low rain rates observed during the experiment is the main contributor to low correlation coefficients and high root-mean-square differences. Mididentification of cold surface (e.g., snow cover) as precipitation was also a problem in several instances.

Negri, Andrew J.↗
NASA NTRS2011

Deriving Soil Moisture with the Combined L-Band Radar and Radiometer Measurements

In this study, we develop a combined active/passive technique to estimate surface soil moisture with the focus on the short vegetated surfaces. We first simulated a database for both active and passive signals under SMAP s sensor configurations using the radiative transfer model with a wide range of conditions for surface soil moisture, roughness and vegetation properties that we considered as the random orientated disks and cylinders. Using this database, we developed 1) the techniques to estimate surface backscattering and emission components and 2) the technique to estimate soil moisture with the estimated surface backscattering and emission components. We will demonstrate these techniques with the model simulated data and its validation with the airborne PALS image data from the soil moisture SGP 99 and SMEX 02 experiments.

Shi, Jiancheng↗
NASA NTRS2016

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster, causing approximately 6.8 million deaths in the twentieth century alone. Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD. Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries. Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change. Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assess flooding and extend analytical methods to estimate impacted population and infrastructure. Measuring flood extent in situ is generally impractical, time consuming, and can be inaccurate. Remotely sensed imagery acquired from space-borne and airborne sensors provides a viable platform for consistent and rapid wall-to-wall monitoring of large flood events through time. Terabytes of freely available satellite imagery are made available online each day by NASA, ESA, and other international space research institutions. Advances in cloud computing and data storage technologies allow researchers to leverage these satellite data and apply analytical methods at scale. Repeat-survey earth observations help provide insight about how natural phenomena change through time, including the progression and recession of floodwaters. In recent years, cloud-penetrating radar remote sensing techniques (e.g., Synthetic Aperture Radar) and high temporal resolution imagery platforms (e.g., MODIS and its 1-day return period), along with high performance computing infrastructure, have enabled significant advances in software systems that provide flood warning, assessments, and hazard reduction potential. By incorporating social and economic data, researchers can develop systems that automatically quantify the socioeconomic impacts resulting from flood disaster events.

Ahamed, Aakash↗
NASA NTRS1990

Advanced Microwave Precipitation Radiometer (AMPR) for remote observation of precipitation

The design, development, and tests of the Advanced Microwave Precipitation Radiometer (AMPR) operating in the 10 to 85 GHz range specifically for precipitation retrieval and mesoscale storm system studies from a high altitude aircraft platform (i.e., ER-2) are described. The primary goals of AMPR are the exploitation of the scattering signal of precipitation at frequencies near 10, 19, 37, and 85 GHz together to unambiguously retrieve precipitation and storm structure and intensity information in support of proposed and planned space sensors in geostationary and low earth orbit, as well as storm-related field experiments. The development of AMPR will have an important impact on the interpretation of microwave radiances for rain retrievals over both land and ocean for the following reasons: (1) A scanning instrument, such as AMPR, will allow the unambiguous detection and analysis of features in two dimensional space, allowing an improved interpretation of signals in terms of cloud features, and microphysical and radiative processes; (2) AMPR will offer more accurate comparisons with ground-based radar data by feature matching since the navigation of the ER-2 platform can be expected to drift 3 to 4 km per hour of flight time; and (3) AMPR will allow underflights of the SSM/I satellite instrument with enough spatial coverage at the same frequencies to make meaningful comparisons of the data for precipitation studies.

Galliano, J. A.↗
DOE OSTI2024

VISSS Raw data from SAIL at Gothic from November 2022 to June 2023

A Video in situ Snowfall Sensor (VISSS) records shadow images of precipitating hydrometeors from two perspective at a 90 degree angle with a frequency of 140 Hz. From this, hydrometeor properties such as particle size, shape, complexity, degree of riming, and fall velocity can be derived. The VISSS was set up next to the ARM mobile facility during the SAIL project located in the East River Watershed near Crested Butte, Colorado from November 2022 to June 2023. The deployment was funded by the CORSIPP project (Characterization of orography-influenced riming and secondary ice production and their effects on precipitation rates using radar polarimetry and Doppler spectra) funded by the German Research Foundation (DFG). More information about the VISSS can be found in Maahn et al. 2023 ( https://dx.doi.org/10.5194/egusphere-2023-655 )

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Availability of Seasat synthetic aperture radar imagery

One of the sensors of the Seasat satellite was a synthetic aperture radar (SAR), which was operated over both oceanic and land areas. The Seasat SAR was an active imaging microwave system which transmitted and received horizontally polarized radiation at L-band frequency (1.275 GHz, 23-cm wavelength). Extensive coverage was obtained over North America, Europe, the Eastern Pacific Ocean, the Western and Northern Atlantic Ocean, and the Beaufort Sea. Surface coverage was also acquired over limited portions of Central America, the Gulf of Mexico, and the Caribbean Sea. The majority of the data has been optically processed in a so-called survey mode. Each optically processed Seasat pass has a swath width of 100 km at a scale of 1:500,000. A subset of the SAR data has been digitally processed in a so-called high-resolution mode. Digital processing has been performed upon selected scenes with dimensions of 100 x 100 km. Digitally processed imagery has a nominal ground resolution of 25 m.

Holt, B.↗
NASA NTRS1995

Satellite Snow-Cover Mapping: A Brief Review

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow and ice cover using Earth Algorithms to map global snow cover using passive-microwave data have also cover and of snow grain size, globally, limits the utility of a single algorithm to map global snow cover.

Hall, Dorothy K.↗
NASA NTRS2002

Real-Time Integrity Monitoring of Stored Geo-Spatial Data Using Forward-Looking Remote Sensing Technology

Terrain Awareness and Warning Systems (TAWS) and Synthetic Vision Systems (SVS) provide pilots with displays of stored geo-spatial data (e.g. terrain, obstacles, and/or features). As comprehensive validation is impractical, these databases typically have no quantifiable level of integrity. This lack of a quantifiable integrity level is one of the constraints that has limited certification and operational approval of TAWS/SVS to "advisory-only" systems for civil aviation. Previous work demonstrated the feasibility of using a real-time monitor to bound database integrity by using downward-looking remote sensing technology (i.e. radar altimeters). This paper describes an extension of the integrity monitor concept to include a forward-looking sensor to cover additional classes of terrain database faults and to reduce the exposure time associated with integrity threats. An operational concept is presented that combines established feature extraction techniques with a statistical assessment of similarity measures between the sensed and stored features using principles from classical detection theory. Finally, an implementation is presented that uses existing commercial-off-the-shelf weather radar sensor technology.

Young, Steven D.↗
NASA NTRSDate not supplied

Reanalysis of Fly's Eye GLM Simulator (FEGS) Optical Pulse Detections from the 2017 GOES-R Post Launch Test (GOES-R PLT) Field Campaign

In 2017, the GOES-R PLT field campaign was conducted to validate new instruments on board GOES-16, including the Geostationary Lightning Mapper (GLM). A NASA ER-2 high altitude aircraft was equipped with a sensor suite including FEGS and an electric field change meter (EFCM) for complementary observations of lightning. As part of a modern reanalysis, we plan to combine aircraft and ground observations from the lightning instrumentation and polarimetric Doppler radars for a more complete characterization of optical lightning measurements in the context of convective properties. This presentation focuses on our initial efforts which include a reanalysis of the FEGS multi-spectral optical waveforms using an updated pulse detection algorithm and a comparison of detected pulses with coincident EFCM and Lightning Mapping Array (LMA) data. We will present on characteristics of discharge processes including leaders, strokes, and continuing current signatures as observed by the suite of aircraft and ground-based lightning instrumentation.

T Daniel Walker↗
NASA NTRS1972

Surface studies on Surveyor 3 tubing sections

Sections C and E of the unpainted, polished aluminum tubing from the strut of the radar altimeter and Doppler velocity sensor were examined in a transmission electron microscope for micrometeorite damage and ion bombardment. Both sections were contaminated and eroded on one side; it is suggested that these conditions were caused by sandblasting by lunar dust and retrorocket plume contamination during Surveyor 3 landing. Microcraters of different configurations were found on the bright sides of the tubes. Several degrees of violence were involved in the formation of the craters, and the particle size could be responsible for some differences. All micropits found were on the bright areas and data indicate 0.2 hypervelocity impact/sq cm and 2/sq cm for other types of craters. The greatest degree of damage resulted from particle impact and was limited to a maximum depth of 2 microns.

Buvinger, E. A.↗
NASA NTRS1977

Technology advances in active and passive microwave sensing through 1985

As a result of a growing awareness by the remote sensing community of the unique capabilities of passive and active microwave sensors, these instruments are expected to grow in the next decade in numbers, versatility and complexity. The Nimbus-G and Seasat-A Scanning Multichannel Microwave Spectrometer (SMMR), the Seasat-A radar altimeter, scatterometer and synthetic aperture radar represent the first systematic attempt at exploring a wide variety of applications utilizing microwave sensing techniques and are indicators of the directions in which the pertinent technology is likely to evolve. The trend is toward high resolution multi-frequency imagers spanning wide frequency ranges and wide swaths requiring sophisticated receivers, real-time data processors and most importantly, complex antennas.

Barath, F. T.↗