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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Image understanding and interpretation in microwave diversity imaging

The authors investigate microwave imaging of metallic objects using a diversity method and interpret and predict the reconstructed image from an approach based on analysis of the scattering mechanism and a back-projection algorithm used in image retrieval. The connection between the various scattering mechanisms and the reconstructed images is discussed, what the images represent is interpreted, and a prediction is made as to what the image will look like over given spectral and angular windows. A brief description is given of the microwave diversity imaging system and the formulation of the microwave diversity imaging based on the physical optics approximation. The scattering mechanism of a complex shaped metallic object is then briefly reviewed and an alternate approach to interpreting the reconstructed image based on the understanding of the scattering mechanism and the reconstruction algorithm is given. Several numerical and experimental examples are included to support this interpretation approach.

Li, Hsueh-Jyh↗
NASA NTRS1989

Analysis of interstellar fragmentation structure based on IRAS images

The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct a densely sampled column density map of a cloud complex which is both self-gravitating and not (yet?) stirred up much by star formation, a column density image of the Taurus region has been constructed from IRAS data. The primary drawback to using the IRAS data for this purpose is that it contains no velocity information, and the possible importance of projection effects must be kept in mind.

Scalo, John M.↗
NASA NTRS1993

Planetary Instrument Definition and Development Program (PIDDP). Instrument for future planetary flight missions: A visible-infrared imaging spectrometer for planetary missions

The objective of this project is to develop and prove a small, light-weight, efficient imaging spectrometer design to cover the VIS/NIR spectral range for applications particularly but not exclusively to NASA inner solar system space missions. A design and a brassboard prototype will be developed and tested. Progress over the first year of this project includes design specification, optical design layout, grating specifications, infrared detector selection, and mechanical design. Mechanical and grating manufacturing drawings were begun. We developed an agreement in principle to cooperate with the German space group, DLR, to apply some of their electronics microminiaturization technology to this imaging spectrometer project, mostly or entirely at their expense. Funds from NASA for the second year of this effort have been received and the effort is on track. Release of funds for the third year of this award will be requested later this year in order to accelerate this work and bring it to a conclusion in time for new NASA missions considerations as well as to make effective use of the DLR contributions.

Mccord, Thomas B.↗
NASA NTRS1992

Analysis of interstellar cloud structure based on IRAS images

The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct densely sampled column density maps of star-forming clouds, column density images of four nearby cloud complexes were constructed from IRAS data. The regions have various degrees of star formation activity, and most of them have probably not been affected much by the disruptive effects of young massive stars. The largest region, the Scorpius-Ophiuchus cloud complex, covers about 1000 square degrees (it was subdivided into a few smaller regions for analysis). Much of the work during the early part of the project focused on an 80 square degree region in the core of the Taurus complex, a well-studied region of low-mass star formation.

Scalo, John M.↗
NASA NTRS2017

Advances in Medical Analytics Solutions for Autonomous Medical Operations on Long-Duration Missions

A review will be presented on the progress made under STMDGame Changing Development Program Funding towards the development of a Medical Decision Support System for augmenting crew capabilities during long-duration missions, such as Mars Transit. To create an MDSS, initial work requires acquiring images and developing models that analyze and assess the features in such medical biosensor images that support medical assessment of pathologies. For FY17, the project has focused on ultrasound images towards cardiac pathologies: namely, evaluation and assessment of pericardial effusion identification and discrimination from related pneumothorax and even bladder-induced infections that cause inflammation around the heart. This identification is substantially changed due to uncertainty due to conditions of fluid behavior under space-microgravity. This talk will present and discuss the work-to-date in this Project, recognizing conditions under which various machine learning technologies, deep-learning via convolutional neural nets, and statistical learning methods for feature identification and classification can be employed and conditioned to graphical format in preparation for attachment to an inference engine that eventually creates decision support recommendations to remote crew in a triage setting.

Medical Decision Support Systems↗
NASA NTRS1989

A multicolor imaging pyrometer

A multicolor imaging pyrometer was designed for accurately and precisely measuring the temperature distribution histories of small moving samples. The device projects six different color images of the sample onto a single charge coupled device array that provides an RS-170 video signal to a computerized frame grabber. The computer automatically selects which one of the six images provides useful data, and converts that information to a temperature map. By measuring the temperature of molten aluminum heated in a kiln, a breadboard version of the device was shown to provide high accuracy in difficult measurement situations. It is expected that this pyrometer will ultimately find application in measuring the temperature of materials undergoing radiant heating in a microgravity acoustic levitation furnace.

Frish, Michael B.↗
NASA NTRS1981

Rock type discrimination techniques using Landsat and Seasat image data

Results of a sedimentary rock type discrimination project using Seasat radar and Landsat multispectral image data of the San Rafael Swell, in eastern Utah, are presented, which has the goal of determining the potential contribution of radar image data to Landsat image data for rock type discrimination, particularly when the images are coregistered. The procedure employs several images processing techniques using the Landsat and Seasat data independently, and then both data sets are coregistered. The images are evaluated according to the ease with which contacts can be located and rock units (not just stratigraphically adjacent ones) separated. Results show that of the Landsat images evaluated, the image using a supervised classification scheme is the best for sedimentary rock type discrimination. Of less value, in decreasing order, are color ratio composites, principal components, and the standard color composite. In addition, for rock type discrimination, the black and white Seasat image is less useful than any of the Landsat color images by itself. However, it is found that the incorporation of the surface textural measures made from the Seasat image provides a considerable and worthwhile improvement in rock type discrimination.

Blom, R.↗
NASA NTRS1975

Impact of remote sensing upon the planning, management, and development of water resources

Principal water resources users were surveyed to determine the impact of remote data streams on hydrologic computer models. Analysis of responses demonstrated that: most water resources effort suitable to remote sensing inputs is conducted through federal agencies or through federally stimulated research; and, most hydrologic models suitable to remote sensing data are federally developed. Computer usage by major water resources users was analyzed to determine the trends of usage and costs for the principal hydrologic users/models. The laws and empirical relationships governing the growth of the data processing loads were described and applied to project the future data loads. Data loads for ERTS CCT image processing were computed and projected through the 1985 era.

Castruccio, P. A.↗
NASA NTRS2003

Optoelectronic Tool Adds Scale Marks to Photographic Images

A simple, easy-to-use optoelectronic tool projects scale marks that become incorporated into photographic images (including film and electronic images). The sizes of objects depicted in the images can readily be measured by reference to the scale marks. The role played by the scale marks projected by this tool is the same as that of the scale marks on a ruler placed in a scene for the purpose of establishing a length scale. However, this tool offers the advantage that it can put scale marks quickly and safely in any visible location, including a location in which placement of a ruler would be difficult, unsafe, or time-consuming. The tool (see Figure 1) includes an aluminum housing, within which are mounted four laser diodes that operate at a wavelength of 670 nm. The laser diodes are spaced 1 in. (2.54 cm) apart along a baseline. The laser diodes are mounted with setscrews, which are used to adjust their beams to make them all parallel to each other and perpendicular to the baseline. During the adjustment process, the effect of the adjustments is observed by measuring the positions of the laser-beam spots on a target 80 ft (approx.24 m) away. Once the adjustments have been completed, the laser beams define three 1-in. (2.54-cm) intervals and the location of each beam is defined to within 1/16 in. (approx.1.6 mm) at any target distance out to about 80 ft (approx.24 m). The distance between the laser-beam spots as seen in an image is strictly defined only along an axis parallel to the baseline and perpendicular to the laser beam (also perpendicular to the line of sight of the camera, assuming that the camera-to-target distance is much greater than the distance between the tool and the camera lens). If a flat target surface illuminated by the laser beams is tilted with respect to the aforesaid axis, then the distance along the target surface between scale marks is proportional to the secant of the tilt angle. If one knows the tilt angle, one can correct for it. Even if one does not know the tilt angle precisely, it may not matter: For example, at a tilt of 10 , the secant is approximately 1.0154, so that the tilt error is only about 1.54 percent, which is negligibly small for a typical application in which only approximate measurements are needed.

Stevenson, Charlie↗
NASA NTRS2012

Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing

As imagery is collected from an airborne platform, an individual viewing the images wants to know from where on the Earth the images were collected. To do this, some information about the camera needs to be known, such as its position and orientation relative to the Earth. This can be provided by common inertial navigation systems (INS). Once the location of the camera is known, it is useful to project an image onto some representation of the Earth. Due to the non-smooth terrain of the Earth (mountains, valleys, etc.), this projection is highly non-linear. Thus, to ensure accurate projection, one needs to project onto a digital elevation map (DEM). This allows one to view the images overlaid onto a representation of the Earth. A code has been developed that takes an image, a model of the camera used to acquire that image, the pose of the camera during acquisition (as provided by an INS), and a DEM, and outputs an image that has been geo-rectified. The world coordinate of the bounds of the image are provided for viewing purposes. The code finds a mapping from points on the ground (DEM) to pixels in the image. By performing this process for all points on the ground, one can "paint" the ground with the image, effectively performing a projection of the image onto the ground. In order to make this process efficient, a method was developed for finding a region of interest (ROI) on the ground to where the image will project. This code is useful in any scenario involving an aerial imaging platform that moves and rotates over time. Many other applications are possible in processing aerial and satellite imagery.

Ansar, Adnan I.↗
NASA NTRSDate not supplied

Using DSCOVR EPIC as a Transfer Radiometer to Scale Multiple VIIRS Sensors Over Tropical Earth Views

The NASA CERES project provides Energy Balanced and Filled (EBAF) product climate-quality observed TOA and computed surface fluxes to the climate community. The CERES instruments are on board the Terra, Aqua, Suomi-NPP, and NOAA-20 satellites. The CERES project radiometrically scales the MODIS and VIIRS imager visible channel radiances to the Aqua- MODIS reference to retrieve consistent imager cloud properties between sensors, which are used to retrieve cloud properties required for converting CERES radiance observations into fluxes. The NPP, NOAA-20, and the future NOAA-21 VIIRS imagers will be in the same sun- synchronous orbit but spaced equally apart, which means that no simultaneous nadir overpasses (SNO) may be used to inter-calibrate the VIIRS imagers to each one another. Currently, the CERES project uses Aqua-MODIS to radiometrically scale between VIIRS imagers. Once the Terra and Aqua satellites start drifting toward the terminator, Aqua-MODIS can no longer be utilized as the transfer radiometer between VIIRS sensors and there will be no SNOs in common between either MODIS and or VIIRS imagers. The DSCOVR satellite orbits the Lagrange-1 (L1) point about 1.5 million kilometers from Earth. The Earth Polychromatic Imaging Camera (EPIC) instrument on the Earth-facing side of DSCOVR takes images ranging from the UV to the NIR of the sunlit side of the Earth. While the EPIC sensor has no onboard calibration systems, multiple inter-calibration studies have indicated that the EPIC instrument response is radiometrically stable. The stability of the EPIC instrument allows it to be used as a transfer radiometer between all MODIS and VIIRS imagers and is especially suited for drifting orbits because EPIC imager frequently samples the Earth diurnally. The study will demonstrate the use of EPIC as a transfer radiometer to radiometrically scale the NPP and NOAA-20 VIIRS imagers. The scaling factors will be compared with the scaling factors using Aqua-MODIS as the transfer radiometer.

Conor Haney↗
NASA NTRS2017

Imaging Systems for Size Measurements of Debrisat Fragments

The overall objective of the DebriSat project is to provide data to update existing standard spacecraft breakup models. One of the key sets of parameters used in these models is the physical dimensions of the fragments (i.e., length, average-cross sectional area, and volume). For the DebriSat project, only fragments with at least one dimension greater than 2 mm are collected and processed. Additionally, a significant portion of the fragments recovered from the impact test are needle-like and/or flat plate-like fragments where their heights are almost negligible in comparison to their other dimensions. As a result, two fragment size categories were defined: 2D objects and 3D objects. While measurement systems are commercially available, factors such as measurement rates, system adaptability, size characterization limitations and equipment costs presented significant challenges to the project and a decision was made to develop our own size characterization systems. The size characterization systems consist of two automated image systems, one referred to as the 3D imaging system and the other as the 2D imaging system. Which imaging system to use depends on the classification of the fragment being measured. Both imaging systems utilize point-and-shoot cameras for object image acquisition and create representative point clouds of the fragments. The 3D imaging system utilizes a space-carving algorithm to generate a 3D point cloud, while the 2D imaging system utilizes an edge detection algorithm to generate a 2D point cloud. From the point clouds, the three largest orthogonal dimensions are determined using a convex hull algorithm. For 3D objects, in addition to the three largest orthogonal dimensions, the volume is computed via an alpha-shape algorithm applied to the point clouds. The average cross-sectional area is also computed for 3D objects. Both imaging systems have automated size measurements (image acquisition and image processing) driven by the need to quickly and accurately measure tens of thousands of debris fragments. Moreover, the automated size measurement reduces potential fragment damage/mishandling and ability for accuracy and repeatability. As the fragment characterization progressed, it became evident that the imaging systems had to be revised. For example, an additional view was added to the 2D imaging system to capture the height of the 2D object. This paper presents the DebriSat project's imaging systems and calculation techniques in detail; from design and development to maturation. The experiences and challenges are also shared.

Shiotani, B.↗
NASA NTRS1973

Precision annotation of predetermined primary sampling units on ERTS-1 MSS images

Resectioning programs were developed for projecting the boundary corners of sample units, management units, and counties into U2 RC-10 and ERTS-1 MSS images. The technique used includes corrections for earth curvature, terrain elevation, and MSS distortions. The minimum standard error obtained was about 0.15 mm or 150 meters on the ground. This technique now makes it possible to include land ownership as an integral part of forest resource sampling plans using ERTS imagery.

Vanroessel, J. W.↗
NASA NTRSDate not supplied

The Application of Remote Sensing using NASA Earth Observations paired with Sociodemographic Indicators to Identify Communities Most Susceptible to Urban Heat Exposure in Austin, Texas

In recent years, Austin, Texas has experienced an increase in population and urban development. Additionally, the City’s climate—already characterized by periods of extreme heat and drought—continues to change. As temperatures and demand for utilities and cooling resources rise, the number of heat-related deaths and illnesses in socially vulnerable populations (e.g., older, lower-income populations) is expected to increase. The City of Austin, The University of Texas at Austin (UT Austin), and The University of Texas Health Science Center at Houston (UT Health) partnered with NASA DEVELOP to examine the distribution of urban heat throughout the City. This project used land surface temperature, greenness, plant water content, and urban surface material analysis parameters derived from NASA Earth observations from Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), and Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The project team produced three different indices to create a spatial analysis for the study area including a social vulnerability index (SoVI), heat exposure index (HEI), and an overall heat priority index (HPI) score. This overall score was determined with a weighted analysis of heat-related environmental variables from NASA Earth observations and socioeconomic data from the 2019 American Community Survey. Based on the HPI score, the project team identified 121 census block groups out of 605 total that are designated as being most at risk of adverse impacts from extreme heat events. To test the sensitivity of the HPI, the team used a Monte Carlo analysis using different approaches for geographic scale, variable inclusion, census uncertainty, and index aggregation. Based on the sensitivity analysis, the resulting HPI score showed the metric was consistent with the baseline HPI. This provided increased confidence the score can be used as a tool to make informed infrastructure improvement plans in targeted areas (e.g., siting of cooling centers) and ensure equitable sustainable development.

Ryan Hammock↗
NASA NTRS1996

A Visual Database System for Image Analysis on Parallel Computers and its Application to the EOS Amazon Project

The goal of this task was to create a design and prototype implementation of a database environment that is particular suited for handling the image, vision and scientific data associated with the NASA's EOC Amazon project. The focus was on a data model and query facilities that are designed to execute efficiently on parallel computers. A key feature of the environment is an interface which allows a scientist to specify high-level directives about how query execution should occur.

Shapiro, Linda G.↗
NASA NTRS1981

Development of Great Lakes algorithms for the Nimbus-G coastal zone color scanner

A series of experiments in the Great Lakes designed to evaluate the application of the Nimbus G satellite Coastal Zone Color Scanner (CZCS) were conducted. Absorption and scattering measurement data were reduced to obtain a preliminary optical model for the Great Lakes. Available optical models were used in turn to calculate subsurface reflectances for expected concentrations of chlorophyll-a pigment and suspended minerals. Multiple nonlinear regression techniques were used to derive CZCS water quality prediction equations from Great Lakes simulation data. An existing atmospheric model was combined with a water model to provide the necessary simulation data for evaluation of the preliminary CZCS algorithms. A CZCS scanner model was developed which accounts for image distorting scanner and satellite motions. This model was used in turn to generate mapping polynomials that define the transformation from the original image to one configured in a polyconic projection. Four computer programs (FORTRAN IV) for image transformation are presented.

Tanis, F. J.↗
NASA NTRS1993

Digital Image Compression Using Artificial Neural Networks

The problem of storing, transmitting, and manipulating digital images is considered. Because of the file sizes involved, large amounts of digitized image information are becoming common in modern projects. Our goal is to described an image compression transform coder based on artificial neural networks techniques (NNCTC). A comparison of the compression results obtained from digital astronomical images by the NNCTC and the method used in the compression of the digitized sky survey from the Space Telescope Science Institute based on the H-transform is performed in order to assess the reliability of the NNCTC.

Serra-Ricart, M.↗
NASA NTRSDate not supplied

Short timescale stability monitoring of GOES-16 visible channels based on daily inter-calibration events with VIIRS and MODIS

The CERES project uses geostationary (GEO) imager derived broadband fluxes to estimate the diurnal flux variations between the Terra (10:30 LT) and Aqua (1:30 LT) flux obs. The GEO derived cloud properties are utilized for narrowband to broadband and angular directional model (ADM) algorithms. The GEO imager channels are first inter-calibrated to the Aqua-MODIS C6.1 calibration reference to ensure that the retrieved clouds and fluxes will be consistent. The CERES project has a 2-month latency, all GEO, MODIS and VIIRS calibration anomalies must be identified and mitigated. Convert the monthly GEO ray-matching algorithm into a daily monitoring algorithm to catch any daily calibration anomalies.

geostationary sensor calibration↗