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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

A Real-Time Microwave Camera at K-Band (24 GHz)

Nondestructive testing (NDT) community has been moving towards effective and robust inspection systems that can provide real-time information about materials, geometrical, structural and mechanical characteristics of composite materials/structures. Moreover, in many applications it is desired to have an image of the structure, after which the information contained in the image is correlated to the above characteristics. Microwave signals penetrate inside of dielectric composite structures and their interaction with the interior of the structure renders critical information for NDT purposes. Subsequently, this information (i.e., magnitude and phase or reflected signal) may be used to produce an image of the interior of the structure revealing potential flaws or anomalies. Image processing and reconstruction techniques may also be incorporated to produce high-resolution images (i.e., synthetic-aperture, back-propagation, etc.). There are several different approaches for designing areal-time microwave camera system. One approach is based on modulated scatterer technique (MST), which is used to tag scattered electric field in a discrete two-dimensional (2D) spatial domain (e.g. a retina) resulting in the 2D magnitude and phase distribution of the scattered electric field which is required for producing an image of a material or structure under inspection. The ability to rapidly modulate resonant slot antennas in such a retina along with using receivers with fast responses provide for real-time image production capability. Design issue and criteria become more challenging at higher frequencies and for a relatively large retina size. This paper presents the basic design and challenges for a microwave camera with a retina size of 6" by 6" operating at a frequency of 24 GHz.

Ghasr, M. T.↗
NASA NTRS2011

Phase-Sensitive Coherence and the Classical-Quantum Boundary in Ghost Imaging

The theory of partial coherence has a long and storied history in classical statistical optics. the vast majority of this work addresses fields that are statistically stationary in time, hence their complex envelopes only have phase-insensitive correlations. The quantum optics of squeezed-state generation, however, depends on nonlinear interactions producing baseband field operators with phase-insensitive and phase-sensitive correlations. Utilizing quantum light to enhance imaging has been a topic of considerable current interest, much of it involving biphotons, i.e., streams of entangled-photon pairs. Biphotons have been employed for quantum versions of optical coherence tomography, ghost imaging, holography, and lithography. However, their seemingly quantum features have been mimicked with classical-sate light, questioning wherein lies the classical-quantum boundary. We have shown, for the case of Gaussian-state light, that this boundary is intimately connected to the theory of phase-sensitive partial coherence. Here we present that theory, contrasting it with the familiar case of phase-insensitive partial coherence, and use it to elucidate the classical-quantum boundary of ghost imaging. We show, both theoretically and experimentally, that classical phase-sensitive light produces ghost imaging most closely mimicking those obtained in biphotons, and we derived the spatial resolution, image contrast, and signal-to-noise ratio of a standoff-sensing ghost imager, taking into account target-induced speckle.

coherence theory↗
NASA NTRS2018

OSIRIS-REx Encounters Bennu: Initial Assessment from the Approach Phase

The OSIRIS-REx spacecraft launched on September 8, 2016, on a seven-year journey to return samples from asteroid (101955) Bennu. This presentation summarizes the scientific results from the Approach and Preliminary Survey phases. Bennu observations are set to begin on August 17, 2018,when the asteroid is bright enough for detection by the PolyCam. PolyCam and MapCam collect data to survey the asteroid environment for any hazards and characterize the asteroid point-source photometric properties. Resolved images acquired during final approach, starting in late October 2018, allow the creation of a shape model using stereophotoclinometry (SPC), needed by both the navigation team and science planners. The OVIRS and OTES spectrometers characterize the point- source spectral properties over a full rotation period, providing a first look at any features and thermophysical properties. TAGSAM is released from the launch container and deployed into the sampling configuration then returned to the stow position.Preliminary Survey follows the Approach Phase in early December 2018. This phase consists of a series of hyperbolic trajectories that cross over the North and South poles and the equator of Bennu at a close-approach distance of 7 km. Images from these Preliminary Survey passes provide data to complete the 75-cm resolution SPC global shape model and solve for the rotation state. Once the shape model is complete, the asteroid coordinate system is defined for co-registration of all data products. These higher-resolution images also constrain the photometric properties and allow for an initial assessment of the geology. In Preliminary Survey the team also obtains the first OLA data, providing a measure of the surface topography. OVIRS and OTES collect data as "ride-along" instruments, with the spacecraft pointing driven by imaging constraints. These data provide a first look at the spectral variation across the surface of Bennu. Radio science measurements, combined with altimetry and imagery, determine Bennu's mass, a prerequisite to placing the spacecraft into orbit in late December 2018. Together, data from the Approach and Preliminary Survey phases set the stage for the extensive mapping planned for 2019. These dates are the baseline plan. Any contingency or unexpected discovery may change this mission profile.

Lauretta, Dante S.↗
NASA NTRS2020

Stability Assessment of OCO-2 Radiometric Calibration Using Aqua MODIS as a Reference

With three imaging grating spectrometers, the Orbiting Carbon Observatory-2 (OCO-2)measures high spectral resolution spectra (λ/∆λ≈19,000) of reflected solar radiation within the molecular oxygen (O2) A-band at 0.765 μm and two carbon dioxide (CO2) bands at 1.61 and 2.06 μm. OCO-2 uses onboard lamps with a reflective diffuser, solar observations through a transmissive diffuser, lunar measurements, and surface targets for radiometric calibration and validation. Separating calibrator aging from instrument degradation poses a challenge to OCO-2. Here we present a methodology for trending the OCO-2 Build 8R radiometric calibration using OCO-2 nadir observations over eight desert sites and nearly simultaneous observations from Moderate Resolution Imaging Spectroradiometer (MODIS) with sensor viewing zenith angles of 15 ± 0.5°. For the O2 A-band, this methodology is able to quantify a drift of−0.8 ± 0.1% per year and capture a small error in correcting the aging of the solar calibrator. For the other two OCO-2 bands, no measurable changes were seen, indicating less than 0.1% and less than 0.3% per year drift in the radiometric calibration of Band 2 and Band 3, respectively.

radiometric calibration↗
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 NTRS2023

Chile Wildland Fires: Augmenting Wildfire Risk Assessment Efforts with Satellite-based Measurements of Soil Moisture and Vegetation Health in Central and South-Central Chile

Since 2010, Central and South-Central Chile have recorded abnormally low annual precipitation, resulting in over a decade-long megadrought. This water deficit has driven more severe wildfires, which begin earlier in the year, last longer, and burn over significantly larger areas. Past studies indicated wildland fires propagate following vegetation stress and under certain soil moisture conditions. Our work further investigated the drivers of the unprecedented wildfire that devastated Central and South-Central Chile in 2017 and 2023. To that end, we leveraged NASA Earth observations from space to explore the link between terrestrial variables and wildland fires. We first delineated the burnt extent using data from Landsat 9 Operational Land Imager 2 (OLI-2), along with the combined information from Terra + Aqua Moderate Resolution Imaging Spectroradiometer (MODIS). Next, we analyzed vegetation health based on the Normalized Difference Vegetation Index (NDVI) and evapotranspiration (ET) products of Terra MODIS. Furthermore, we examined soil moisture data from the Soil Moisture Active Passive (SMAP) mission. As the megadrought continues, we found greater anomalies and stress in vegetation indices across the region. We also identified certain pre-fire conditions in soil moisture and evapotranspiration in the days and months leading to the recent wildfires. We compared these findings against control areas that were not impacted by wildfires. Using satellite-based NASA Earth observations, we were able to provide insights into potential indicators of wildfire risk, which can augment future risk assessment and management efforts.

Benjamin D Goffin↗
NASA NTRS1985

Proceedings of the Airborne Imaging Spectrometer Data Analysis Workshop

The Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on April 8 to 10, 1985. It was attended by 92 people who heard reports on 30 investigations currently under way using AIS data that have been collected over the past two years. Written summaries of 27 of the presentations are in these Proceedings. Many of the results presented at the Workshop are preliminary because most investigators have been working with this fundamentally new type of data for only a relatively short time. Nevertheless, several conclusions can be drawn from the Workshop presentations concerning the value of imaging spectrometry to Earth remote sensing. First, work with AIS has shown that direct identification of minerals through high spectral resolution imaging is a reality for a wide range of materials and geological settings. Second, there are strong indications that high spectral resolution remote sensing will enhance the ability to map vegetation species. There are also good indications that imaging spectrometry will be useful for biochemical studies of vegetation. Finally, there are a number of new data analysis techniques under development which should lead to more efficient and complete information extraction from imaging spectrometer data. The results of the Workshop indicate that as experience is gained with this new class of data, and as new analysis methodologies are developed and applied, the value of imaging spectrometry should increase.

Vane, G.↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

water-related ecosystems; surface water extent; ma↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped overtime for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

Raha Hakimdavar↗
NASA NTRS2020

SCExAO/CHARIS High-contrast Imaging of Spirals and Darkening Features in the HD 34700 A Protoplanetary Disk

We present Subaru/SCExAO+Coronagraphic High Angular Resolution Imaging Spectrograph (CHARIS) broadband (JHK-band) integral field spectroscopy of HD 34700 A. CHARIS data recover HD 34700 A's disk ring and confirm multiple spirals discovered by Monnier et al. We set limits on substellar companions of ∼12 MJup at 0.″3 (in the ring gap) and ∼5 M(Jup) at 0."75 (outside the ring). The data reveal darkening effects on the ring and spiral, although we do not identify the origin of each feature such as shadows or physical features related to the outer spirals. Geometric albedos converted from the surface brightness suggest a greater scale height and/or prominently abundant submicron dust at position angles between ∼45° and 90°. Spiral fitting resulted in very large pitch angles (∼30°–50°); a stellar flyby of HD 34700 B or infall from a possible envelope is perhaps a reasonable scenario to explain the large pitch angles.

Taichi Uyama↗
NASA NTRS1993

Clementine: Anticipated scientific datasets from the Moon and Geographos

The Clementine spacecraft mission is designed to test the performance of new lightweight and low-power detectors developed at the Lawrence Livermore National Laboratory (LLNL) for the Strategic Defense Initiative Office (SDIO). A secondary objective of the mission is to acquire useful scientific data, principally of the Moon and the near-Earth asteroid Geographos. The spacecraft will be in an elliptical polar orbit about the Moon for about 2 months beginning in February of 1994 and it will fly by Geographos on August 31. Clementine will carry seven detectors each weighing less than about 1 kg: two Star Trackers wide-angle uv/vis wide-angle Short Wavelength IR (SWIR) Long-Wavelength IR (LWIR) and LIDAR (Laser Image Detection And Ranging) narrow-angle imaging and ranging. Additional presentations about the mission detectors and related science issues are in this volume. If fully successful Clementine will return about 3 million lunar images, a dataset with nearly as many bits of data (uncompressed) as the first cycle of Magellan and more than 5000 images of Geographos. The complete and efficient analysis of such large data sets requires systematic processing efforts. Described below are concepts for two such efforts for the Clementine mission: global multispectral imaging of the Moon and videos of the Geographos flyby. Other anticipated datasets for which systematic processing might be desirable include multispectral observations of Earth; LIDAR altimetry of the Moon with high-resolution imaging along each ground track; high-resolution LIDAR color along each lunar ground track which could be used to identify potential titanium-rich deposits at scales of a few meters; and thermal IR imaging along each lunar ground track (including nighttime observations near the poles).

Mcewen, A. S.↗
NASA NTRS1999

Intercomparison of Satellite-Derived Snow-Cover Maps

In anticipation of the launch of the Earth Observing System (EOS) Terra, and the PM-1 spacecraft in 1999 and 2000, respectively, efforts are ongoing to determine errors of satellite-derived snow-cover maps. EOS Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer-E (AMSR-E) snow-cover products will be produced. For this study we compare snow maps covering the same study area acquired from different sensors using different snow- mapping algorithms. Four locations are studied: 1) southern Saskatchewan; 2) a part of New England (New Hampshire, Vermont and Massachusetts) and eastern New York; 3) central Idaho and western Montana; and 4) parts of North and South Dakota. Snow maps were produced using a prototype MODIS snow-mapping algorithm used on Landsat Thematic Mapper (TM) scenes of each study area at 30-m and when the TM data were degraded to 1 -km resolution. National Operational Hydrologic Remote Sensing Center (NOHRSC) 1 -km resolution snow maps were also used, as were snow maps derived from 1/2 deg. x 1/2 deg. resolution Special Sensor Microwave Imager (SSM/1) data. A land-cover map derived from the International Geosphere-Biosphere Program (IGBP) land-cover map of North America was also registered to the scenes. The TM, NOHRSC and SSM/I snow maps, and land-cover maps were compared digitally. In most cases, TM-derived maps show less snow cover than the NOHRSC and SSM/I maps because areas of incomplete snow cover in forests (e.g., tree canopies, branches and trunks) are seen in the TM data, but not in the coarser-resolution maps. The snow maps generally agree with respect to the spatial variability of the snow cover. The 30-m resolution TM data provide the most accurate snow maps, and are thus used as the baseline for comparison with the other maps. Comparisons show that the percent change in amount of snow cover relative to the 3 0-m resolution TM maps is lowest using the TM I -km resolution maps, ranging from 0 to 40%. The highest percent change (less than 100%) is found in the New England study area, probably due to the presence of patchy snow cover. A scene with patchy snow cover is more difficult to map accurately than is a scene with a well-defined snowline such as is found on the North and South Dakota scene where the percent change ranged from 0 to 40%. There are also some important differences in the amount of snow mapped using the two different SSM/I algorithms because they utilize different channels.

Hall, Dorothy K.↗
NASA NTRS1998

Clementine High Resolution Camera Mosaicking Project

This report constitutes the final report for NASA Contract NASW-5054. This project processed Clementine I high resolution images of the Moon, mosaicked these images together, and created a 22-disk set of compact disk read-only memory (CD-ROM) volumes. The mosaics were produced through semi-automated registration and calibration of the high resolution (HiRes) camera's data against the geometrically and photometrically controlled Ultraviolet/Visible (UV/Vis) Basemap Mosaic produced by the US Geological Survey (USGS). The HiRes mosaics were compiled from non-uniformity corrected, 750 nanometer ("D") filter high resolution nadir-looking observations. The images were spatially warped using the sinusoidal equal-area projection at a scale of 20 m/pixel for sub-polar mosaics (below 80 deg. latitude) and using the stereographic projection at a scale of 30 m/pixel for polar mosaics. Only images with emission angles less than approximately 50 were used. Images from non-mapping cross-track slews, which tended to have large SPICE errors, were generally omitted. The locations of the resulting image population were found to be offset from the UV/Vis basemap by up to 13 km (0.4 deg.). Geometric control was taken from the 100 m/pixel global and 150 m/pixel polar USGS Clementine Basemap Mosaics compiled from the 750 nm Ultraviolet/Visible Clementine imaging system. Radiometric calibration was achieved by removing the image nonuniformity dominated by the HiRes system's light intensifier. Also provided are offset and scale factors, achieved by a fit of the HiRes data to the corresponding photometrically calibrated UV/Vis basemap, that approximately transform the 8-bit HiRes data to photometric units. The sub-polar mosaics are divided into tiles that cover approximately 1.75 deg. of latitude and span the longitude range of the mosaicked frames. Images from a given orbit are map projected using the orbit's nominal central latitude. Polar mosaics are tiled into squares 2250 pixels on a side, which spans approximately 2.2 deg. Two mosaics are provided for each pole: one corresponding to data acquired while periapsis was in the south, the other while periapsis was in the north. The CD-ROMs also contain ancillary data files that support the HiRes mosaic. These files include browse images with UV/Vis context stored in a Joint Photographic Experts Group (JPEG) format, index files ('imgindx.tab' and 'srcindx.tab') that tabulate the contents of the CD, and documentation files.

Source record↗
DOE OSTI2021

Surface albedo spatial variability in North America: Gridded data vs. local measurements

Considering the current booming interest for the large-scale deployment of bifacial photovoltaic modules, the solar industry now requires accurate estimates of broadband surface albedo at high spatial resolution. In this context, the present study evaluates the adequacy and performance over North America of two Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky albedo products (at 500-m and 1-km resolution) and the National Solar Radiation Database (NSRDB) product at 4-km resolution. Two variations of the 500-m MODIS product are also considered: black-sky albedo and all-sky albedo. Albedo observations from 36 radiometric stations during 2011–2015 are analyzed while considering the apparent homogeneity of the surface characteristics over the 4x4 km NSRDB pixel in which they are located. Even at sites where the albedo around the station has been found “homogeneous” in the literature, marked differences are found between the daily observations and the gridded estimates at any spatial resolution. Furthermore, differences in seasonal behavior and between the three different albedo types also impact the accuracy of the albedo estimates, with overtones caused by local specificities and inhomogeneities. All this precludes the desirable evaluation of the local albedo at a specific site of relatively small size compared to its corresponding 4x4-km pixel if only the mean albedo over that pixel is known. Significant discrepancies are also found at snow-impacted sites, most importantly in the case of the NSRDB albedo estimates, which are typically much too high.

14 SOLAR ENERGY↗
DOE OSTI2024

Enhancing Diagnosis through AI-driven Analysis of Reflectance Confocal Microscopy

Reflectance Confocal Microscopy (RCM) is a non-invasive imaging technique used in biomedical research and clinical dermatology. It provides virtual high-resolution images of the skin and superficial tissues, reducing the need for physical biopsies. RCM employs a laser light source to illuminate the tissue, capturing the reflected light to generate detailed images of microscopic structures at various depths. Recent studies explored AI and machine learning, particularly CNNs, for analyzing RCM images. Our study proposes a segmentation strategy based on textural features to identify clinically significant regions, empowering dermatologists in effective image interpretation and boosting diagnostic confidence. This approach promises to advance dermatological diagnosis and treatment.

Yoon, Hong-Jun↗
NASA NTRS1980

Comet Science Working Group report on the Halley Intercept Mission

The Halley Intercept Mission is described and the scientific benefits expected from the program are defined. One characteristic of the mission is the optical navigation and resulting accurate delivery of the spacecraft to a desired point near the nucleus. This accuracy of delivery has two important implications: (1) high probability that the mass spectrometers and other in situ measurement devices will reach the cometary ionosphere and the zone of parent molecules next to the nucleus; (2) high probability that sunlit, high resolution images of Halley's nucleus will be obtained under proper lighting conditions. In addition an observatory phase is included during which high quality images of the tail and coma structure will be obtained at progressively higher spatial resolutions as the spacecraft approaches the comet. Complete measurements of the comet/solar wind interaction can be made around the time of encounter. Specific recommendations are made concerning project implementation and spacecraft requirements.

Source record↗
NASA NTRS1980

X-ray variability in active galaxy nuclei and quasars in less than one day

Data obtained from the Einstein Observatory demonstrating variations in X-ray emission from the nuclei of active galaxies and quasars on time scales of hours rather than previously observed days or years is presented. Light curves obtained from the Einstein imaging proportional counter for the Seyfert 1 galaxy NGC 6814 and from the High Resolution Imager for the quasars OX 169 and 3C 273 are illustrated, and variations by factors greater than two on time scales less than 20,000 sec for the first two objects and by a factor of 10% on a time scale over 50,000 sec for 3C 273 are pointed out. The measurements are also used to determine that thermal bremsstrahlung cannot be the cause of the intensity decay in OX 169, and that, in the absence of relativistic effects, the efficiency for energy release in the matter involved in the emission of 3C 273 is at least 0.1.

Elvis, M.↗
NASA NTRS1983

X-ray variability of BL Lac objects - H2155-304 and PKS 0548-322

X-ray emission from two BL Lacertae objects (H2155-304 and PKS 0548-322) has been studied with the High-Resolution Imager and Monitor Proportional Counter (MPC) on the Einstein Observatory. The high-spatial-resolution observations confirm the identification of these X-ray sources with the BL Lac objects and give a source size less than about 2 arcsec. Variations in the X-ray intensity and spectrum of these sources were detected over time scales of a few hours from analysis of the MPC observations.

Agrawal, P. C.↗