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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Improved disparity map analysis through the fusion of monocular image segmentations

The focus is to examine how estimates of three dimensional scene structure, as encoded in a scene disparity map, can be improved by the analysis of the original monocular imagery. The utilization of surface illumination information is provided by the segmentation of the monocular image into fine surface patches of nearly homogeneous intensity to remove mismatches generated during stereo matching. These patches are used to guide a statistical analysis of the disparity map based on the assumption that such patches correspond closely with physical surfaces in the scene. Such a technique is quite independent of whether the initial disparity map was generated by automated area-based or feature-based stereo matching. Stereo analysis results are presented on a complex urban scene containing various man-made and natural features. This scene contains a variety of problems including low building height with respect to the stereo baseline, buildings and roads in complex terrain, and highly textured buildings and terrain. The improvements are demonstrated due to monocular fusion with a set of different region-based image segmentations. The generality of this approach to stereo analysis and its utility in the development of general three dimensional scene interpretation systems are also discussed.

Perlant, Frederic P.↗
NASA NTRS1974

Automated thematic mapping and change detection of ERTS-1 images

Results of an automated thematic mapping investigation using ERTS-1 MSS images are presented. A diffraction pattern analysis of MSS images led to the development of spatial signatures for farm land, urban areas, and mountains. Four spatial features are employed to describe the spatial characteristics of image cells in the digital data. Three spectral features are combined with the spatial features to form a seven dimensional vector describing each cell. Then, the classification of the feature vectors is accomplished by using the maximum likelihood criterion. Three ERTS-1 images from the Phoenix, Arizona area were processed, and recognition rates between 85% and 100% were obtained for the terrain classes of desert, farms, mountains and urban areas. To eliminate the need for training data, a new clustering algorithm has also been developed.

Gramenopoulos, N.↗
NASA NTRS1974

Automated thematic mapping and change detection of ERTS-A images

The author has identified the following significant results. A diffraction pattern analysis of MSS images led to the development of spatial signatures for farm land, urban areas and mountains. Four spatial features are employed to describe the spatial characteristics of image cells in the digital data. Three spectral features are combined with the spatial features to form a seven dimensional vector describing each cell. Then, the classification of the feature vectors is accomplished by using the maximum likelihood criterion. It was determined that the recognition accuracy with the maximum likelihood criterion depends on the statistics of the feature vectors. It was also determined that for a given geographic area the statistics of the classes remain invariable for a period of a month, but vary substantially between seasons. Three ERTS-1 images from the Phoenix, Arizona area were processed, and recognition rates between 85% and 100% were obtained for the terrain classes of desert, farms, mountains, and urban areas. To eliminate the need for training data, a new clustering algorithm has been developed. Seven ERTS-1 images from four test sites have been processed through the clustering algorithm, and high recognition rates have been achieved for all terrain classes.

Gramenopoulos, N.↗
NASA NTRS1980

Seasat views North America, the Caribbean, and Western Europe with imaging radar

Forty-one digitally correlated Seasat synthetic-aperture radar images of land areas in North America, the Caribbean, and Western Europe are presented to demonstrate this microwave orbital imagery. The characteristics of the radar images, the types of information that can be extracted from them, and certain of their inherent distortions are briefly described. Each atlas scene covers an area of 90 X 90 kilometers, with the exception of the one that is the Nation's Capital. The scenes are grouped according to salient features of geology, hydrology and water resources, urban landcover, or agriculture. Each radar image is accompanied by a corresponding image in the optical or near-infrared range, or by a simple sketch map to illustrate features of interest. Characteristics of the Seasat radar imaging system are outlined.

Ford, J. P.↗
NASA NTRSDate not supplied

Rapid Aero Modeling for Urban Air Mobility Aircraft in Wind-Tunnel Tests

Rapid Aero Modeling (RAM) applied to wind tunnel testing, RAM-T, is an approach to efficiently and automatically obtain aerodynamic models during testing. The approach saves time and resources by responding to the demand for experimental efficiency and model fidelity. Motivation for this demand is more acute when investigating a class of vehicles categorized as Urban Air Mobility (UAM) aircraft where many features from both aircraft and rotorcraft are present. RAM-T provides a feedback loop around the test facility to guide the test toward high-fidelity, statistically rigorous aircraft models. The general RAM approach is applicable to computational or physical experiments. It combines concepts from design of experiment theory and aircraft system identification theory that allow the user the freedom to choose, in advance of the test, a specific level of fidelity in terms of prediction error. RAM only collects data required to meet the user-specified fidelity and fidelity is only limited by the facility and test article capabilities. This paper presents results from tests conducted for development of an automated RAM-T technology. The results highlight some of the unique features of RAM applied to eVTOL configurations.

Aerodynamics↗
NASA NTRS1974

Multidisciplinary study of Wyoming test sites

The author has identified the following significant results. Investigation of a variety of applications of EREP photographic data demonstrated that EREP S-190 data offer a unique combination of synoptic coverage and image detail. The broad coverage is ideal for regional geologic mapping and tectonic analysis while the detail is adequate for mapping of crops, mines, urban areas, and other relatively small features. The investigative team at the University of Wyoming has applied the EREP S-190 data to: (1) analysis of photolinear elements of the Powder River Basin, southern Montana, and the Wind River Mountains; (2) drainage analysis of the Powder River Basin and Beartooth Mountains; (3) lithologic and geologic mapping in the Powder River Basin, Black Hills, Green River Basin, Bighorn Basin and Southern Bighorn Mountains; (4) location of possible mineralization in the Absaroka Range; and (5) land use mapping near Riverton and Gillette. All of these applications were successful to some degree. Image enhancement procedures were useful in some efforts requiring distinction of small objects or subtle contrasts.

Houston, R. S.↗
NASA NTRS2010

Digital Astronaut Photography: A Discovery Dataset for Archaeology

Astronaut photography acquired from the International Space Station (ISS) using commercial off-the-shelf cameras offers a freely-accessible source for high to very high resolution (4-20 m/pixel) visible-wavelength digital data of Earth. Since ISS Expedition 1 in 2000, over 373,000 images of the Earth-Moon system (including land surface, ocean, atmospheric, and lunar images) have been added to the Gateway to Astronaut Photography of Earth online database (http://eol.jsc.nasa.gov ). Handheld astronaut photographs vary in look angle, time of acquisition, solar illumination, and spatial resolution. These attributes of digital astronaut photography result from a unique combination of ISS orbital dynamics, mission operations, camera systems, and the individual skills of the astronaut. The variable nature of astronaut photography makes the dataset uniquely useful for archaeological applications in comparison with more traditional nadir-viewing multispectral datasets acquired from unmanned orbital platforms. For example, surface features such as trenches, walls, ruins, urban patterns, and vegetation clearing and regrowth patterns may be accentuated by low sun angles and oblique viewing conditions (Fig. 1). High spatial resolution digital astronaut photographs can also be used with sophisticated land cover classification and spatial analysis approaches like Object Based Image Analysis, increasing the potential for use in archaeological characterization of landscapes and specific sites.

Stefanov, William L.↗
NASA NTRS2017

Image Detective 2.0: Engaging Citizen Scientists with NASA Astronaut Photography

Image Detective 2.0 engages citizen scientists with NASA astronaut photography of the Earth obtained by crew members on the International Space Station (ISS). Engaged citizen scientists are helping to build a more comprehensive and searchable database by geolocating this imagery and contributing to new imagery collections. Image Detective 2.0 is the newest addition to the suite of citizen scientist projects available through CosmoQuest, an effort led by the Astronomical Society of the Pacific (ASP) and supported through a NASA Science Mission Directorate Cooperative Agreement Notice award. CosmoQuest hosts a number of citizen science projects enabling individuals from around the world to engage in authentic NASA science. Image Detective 2.0, an effort that focuses on imagery acquired by astronauts on the International Space Station, builds on work initiated in 2012 by scientists and education specialists at the NASA Johnson Space Center. Through the many lessons learned, Image Detective 2.0 enhances the original project by offering new and improved options for participation. Existing users, as well as new Image Detective participants joining through the CosmoQuest platform, gain first-hand experience working with astronaut photography and become more engaged with this valuable data being obtained from the International Space Station. Citizens around the world are captivated by astronauts living and working in space. As crew members have a unique vantage point from which to view our Earth, the Crew Earth Observations (CEO) online database, referred to as the Gateway to Astronaut Photography of Earth (https://eol.jsc.nasa.gov/), provides a means for crew members to share their unique views of our home planet from the ISS with the scientific community and the public. Astronaut photography supports multiple uses including scientific investigations, visualizations, education, and outreach. These astronaut images record how the planet is changing over time, from human-made changes like urban growth and agriculture, to natural features and landforms such as tropical cyclones, aurora, coastlines, volcanoes and more. This imagery provides researchers on Earth with data to understand the planet from the perspective of the ISS, and is a useful complement to other remotely sensed datasets collected from robotic satellite platforms.

Higgins, Melissa↗
NASA NTRSDate not supplied

Preliminary Steps in Developing Rapid Aero Modeling Technology

The Rapid Aero Modeling (RAM) approach is a method to efficiently and automatically obtain aerodynamic models during testing, significantly saving time and resources. Motivation for this technology results from demand for experimental efficiency and model fidelity that has increased with growing aircraft complexity and aerodynamic nonlinearities. These issues are typical in the responses presented by a class of vehicles categorized as Urban Air Mobility aircraft where many features from both airplane and rotorcraft are present. For UAM configurations, with typically many more factors than conventional aircraft, traditional test methods can lead to increased costs and missed interactions. RAM guides the test to obtain high-fidelity, statistically rigorous aircraft models, and the approach is applicable to computational, ground, or flight-test experiments. It combines concepts from Design of Experiment theory and Aircraft System Identification theory that allow the user the freedom to choose, in advance of the test, a specific level of fidelity typically, in terms of prediction error. RAM only collects data required to meet the user-specified fidelity and fidelity is only limited by the facility and test article capabilities. An initial wind tunnel test to support development of RAM was conducted to assess potential metrics, algorithms, and procedures. This paper presents results from initial tests for the development of RAM technology and highlights some of the unique features of RAM applied toa conventional configuration during a ground-based, static, wind-tunnel test.

Patrick C Murphy↗
NASA NTRS1986

Spatial resolution requirements for urban land cover mapping from space

Very low resolution (VLR) satellite data (Advanced Very High Resolution Radiometer, DMSP Operational Linescan System), low resolution (LR) data (Landsat MSS), medium resolution (MR) data (Landsat TM), and high resolution (HR) satellite data (Spot HRV, Large Format Camera) were evaluated and compared for interpretability at differing spatial resolutions. VLR data (500 m - 1.0 km) is useful for Level 1 (urban/rural distinction) mapping at 1:1,000,000 scale. Feature tone/color is utilized to distinguish generalized urban land cover using LR data (80 m) for 1:250,000 scale mapping. Advancing to MR data (30 m) and 1:100,000 scale mapping, confidence in land cover mapping is greatly increased, owing to the element of texture/pattern which is now evident in the imagery. Shape and shadow contribute to detailed Level II/III urban land use mapping possible if the interpreter can use HR (10-15 m) satellite data; mapping scales can be 1:25,000 - 1:50,000.

Todd, William J.↗
NASA NTRS2001

Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperature

Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (+/-5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

Laymon, Charles A.↗
NASA NTRS2001

Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperatures

Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (plus or minus 5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

Laymon, Charles A.↗
NASA NTRSDate not supplied

Practical Conceptual Design of Quieter Urban VTOL Aircraft

A toolchain and process for conceptual design of VTOL rotorcraft, employing low- and mid-fidelity tools is presented. The approach is capable of providing more quantitatively-credible trades between noise, size, and cost metrics than the methods commonly used for conceptual design. In addition to a general conceptual design tool, the approach employs comprehensive analysis for trim, blade motion, and airloads; these are then used by acoustic analysis software to develop source sound, propagate it, and calculate noise metrics. A key aspect of the approach is flexibility to assess varied aircraft types and different technologies and design features. Vehicles are sized using a representative Urban Air Mobility design mission. Demonstration cases are presented for a single main rotor helicopter, quadrotor, side-by-side helicopter, and lift+cruise aircraft. Noise metrics used for demonstration are the FAA/EASA certification Effective Perceived Noise Levels for takeoff, flyover, and approach. The concept aircraft in this study are shown to achieve reductions in noise relative the initial design points, with changes in mission performance and cost as a consequence. Many of the designs are predicted to be tens of EPNdB quieter in the certification metrics than existing helicopters.

Conceptual Design↗
NASA NTRS2004

Human-Induced Climate Variations Linked to Urbanization: From Observations to Modeling

The goal of this session is to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results focusing on the impact of urbanization on the climate. The discussion will highlight current observational and modeling capabilities being employed for investigating the urban environment and its linkage to the change in the Earth's climate system. The goal of the session is to identify our current stand and the future direction on the topic. Urbanization is one of the extreme cases of land use change. Most of population of the world has moved to urban areas. By 1995, more than 70% of population of North America and Europe were living in cities. By 2025, the United Nations estimates that 60% of the worlds population will live in cities. Although currently only 1.2% of the land is urban, better understanding of how the atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of human activities on this system is critical. Our understanding of urbanization effect is incomplete, partly because human activities induce new changes on climate in addition to the original natural variations, and partly because previously few data available for study urban effect globally. Urban construction changes surface roughness, albedo, heat capacity and vegetation coverage. Traffic and industry increase atmospheric aerosol. It is suggested that urbanization may modify rainfall processes through aerosol-cloud interactions or dynamic feedbacks. Because urbanization effect on climate is determined by many factors including land cover, the city's microscale features, population density, and human lifestyle patterns, it is necessary to study urban areas over globe.

Shepherd, J. Marshall↗
NASA NTRS1995

Terrain classification using circular polarimetric features

Conventional representations of polarization response are referred to a horizontally and vertically polarized basis. Recent studies by Freeman and Durden, van Zyl, and others suggest that alternative polarimetric features which more easily resolve the contributions of simple scattering mechanisms such as odd-bounce, even-bounce, and diffuse scattering could offer several advantages in terrain classification. The circular polarization covariance matrix is a potential source of such features. In this paper, we derive its relationship to the Stokes matrix, describe some of its properties, and compare the utility of linear and circular polarimetric features in classifying an AIRSAR scene containing urban, park, and ocean terrain.

Michelson, David G.↗
NASA NTRS1993

Multifrequency observations

Analyses of synthetic aperture radar (SAR) image data were performed at DLR to classify various kinds of vegetation and different terrain types. The data were collected both with the DLR experimental synthetic aperture radar (E-SAR) in X-band, C-band, and L-band and with the NASA/JPL DC-8 SAR in C-band, L-band, and P-band. E-SAR is a single frequency and single polarization system (both parameters can be selected) but several flights were used to collect multifrequency/multipolarization data which were geometrically matched after processing. Classification of different crop types was based on comparison of the backscatter coefficients of calibrated SAR data in different frequency bands and polarizations. The DC-8 STAR collects polarimetric data in different bands simultaneously. Data acquired with the NASA/JPL DC-8 STAR are qualified for scientific investigations by reducing the cross-talk and channel imbalance to a tolerable extent. The data are absolutely calibrated by using reference targets with known backscattering cross-sections. The signatures and polarimetric features of terrain types, such as grassland, concrete, sea, forest (coniferous; deciduous) and urban areas, are extracted and discussed with respect to frequency and incidence angle dependence. A multifrequency polarimetric feature vector was applied for classification. The results of this new approach for separating and classifying different object classes are presented.

Glitz, R.↗
NASA NTRS1973

Application of Earth Resources Technology Satellite data to urban development and regional planning: Test site, County of Los Angeles

The author has identified the following significant results. Signigicant results have been obtained from the analyses of ERTS-1 imagery from five cycles over Test Site SR 124 by classical photointerpretation and by an interactive hybrid multispectral information extraction system (GEMS). Photointerpretation has produced over 25 overlays at 1:1,000,000 scale depicting regional relations and urban structure in terms of several hundred linear and areal features. A possible new fault lineament has been discovered on the northern slope of the Santa Monica mountains. GEMS analysis of the ERTS-1 products has provided new or improved information in the following planning data categories: urban vegetation; land cover segregation; manmade and natural impact monitoring; urban design; land suitability. ERTS-1 data analysis has allowed planners to establish trends that directly impact planning policies. For example, detectable grading and new construction sites quantitatively indicated the extent, direction, and rate of urban expansion which enable planners to forecast demand and growth patterns on a regional scale. This new source of information will not only assist current methods to be more efficient, but permits entirely new planning methodologies to be employed.

Raje, S.↗
NASA NTRS1993

High resolution depiction of atmospheric moisture, stability and surface temperature from combined MAMS and VAS radiances

In order to elucidate mesoscale variability of the earth-atmosphere system, aircraft-borne Multi-spectral Atmospheric Mapping Sensor (MAMS), 100-meter-resolution radiometric data, and geostationary-borne VISSR Atmospheric Sounder (VAS) 8-km-resolution radiometric data are used together in a physical retrieval method to produce 100-m-resolution depictions of atmospheric moisture, stability, and skin temperature. The VAS, with its IR-sounding capability, provides the vertical information to the retrieval while the MAMS, with its 100-m resolution, provides the horizontal information. The retrievals show mesoscale features, including a moist tongue intrusion and an urban heat island. Mesogamma-scale gradients are found to exceed mesobeta-scale gradients, and significant mesogamma-scale variability is not captured in current geostationary sounding data. It is suggested that improvements to the spatial resolution of operating sounding data will yield improved information on atmospheric and surface gradients, especially at the mesogamma scale.

Moeller, C. C.↗