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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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NASA NTRS1994

Cometary coma chemical composition (C4) mission

Cometary missions are of enormous fundamental importance for many different space science disciplines, including exobiology. Comets are presumed relics of the earliest, most primitive material in the solar nebula and are related to the planetesimals. They undoubtedly provided a general enrichment of volatiles to the inner solar system (contributing to atmospheres and oceans) and may have been key to the origin of life. A Discovery class, comet rendezvous mission, the Cometary Coma Chemical Composition (C4) Mission, was selected for further study by NASA earlier this year. The C4 Mission is a highly focused and usefully-limited subset of the Cometary Rendezvous Asteroid Flyby (CRAF) Mission, concentrating exclusively on measurements which will lead to an understanding of the chemical composition and make-up of the cometary nucleus. The scientific goals of the Cometary Coma Chemical Composition (C4) Mission are to rendezvous with a short-period comet and (1) to determine the elemental, chemical, and isotopic composition of the nucleus and (2) to characterize the chemical and isotopic nature of its atmosphere. Further, it is a goal to obtain preliminary data on the development of the coma (dust and gas composition) as a function of time and orbital position.

Carle, G. C.↗
NASA NTRS1991

Molecular clouds in starburst galaxy nuclei

New CO observations of a complete sample of starburst galaxies are presented in order to determine the range of molecular gas masses and star-formation efficiencies that characterize these systems. The properties of the galaxies in the sample are given, and the H-alpha and R-band CCD images for six of the galaxies are shown. The novel feature of this study is that the galaxies in this study are infrared selected as opposed to optically selected. They exhibit levels of nuclear star formation activity which are comparable to the starburst galaxies M82 and NGC 253. A subset of galaxies with unusually narrow CO line widths, high star-formation efficiencies, and compact 10-micron distributions is revealed. It is proposed that, if gas distributions in these galaxies are also compact, as the narrow linewidths suggest, the high yields of massive stars per unit mass of molecular gas may be attributed to a star-formation mechanism which becomes more efficient as the gas density increases.

Young, Judith S.↗
NASA NTRS2007

Serving Fisheries and Ocean Metadata to Communities Around the World

NASA's Global Change Master Directory (GCMD) assists the oceanographic community in the discovery, access, and sharing of scientific data by serving on-line fisheries and ocean metadata to users around the globe. As of January 2006, the directory holds more than 16,300 Earth Science data descriptions and over 1,300 services descriptions. Of these, nearly 4,000 unique ocean-related metadata records are available to the public, with many having direct links to the data. In 2005, the GCMD averaged over 5 million hits a month, with nearly a half million unique hosts for the year. Through the GCMD portal (http://gcmd.nasa.gov/), users can search vast and growing quantities of data and services using controlled keywords, free-text searches, or a combination of both. Users may now refine a search based on topic, location, instrument, platform, project, data center, spatial and temporal coverage, and data resolution for selected datasets. The directory also offers data holders a means to advertise and search their data through customized portals, which are subset views of the directory. The discovery metadata standard used is the Directory Interchange Format (DIF), adopted in 1988. This format has evolved to accommodate other national and international standards such as FGDC and IS019115. Users can submit metadata through easy-to-use online and offline authoring tools. The directory, which also serves as the International Directory Network (IDN), has been providing its services and sharing its experience and knowledge of metadata at the international, national, regional, and local level for many years. Active partners include the Committee on Earth Observation Satellites (CEOS), federal agencies (such as NASA, NOAA, and USGS), international agencies (such as IOC/IODE, UN, and JAXA) and organizations (such as ESIP, IOOS/DMAC, GOSIC, GLOBEC, OBIS, and GoMODP).

Meaux, Melanie F.↗
NASA NTRS2020

Using X-Ray Computed Tomography to Image Apollo Drive Tube 73002

The Apollo missions collected 382 kg of rock, regolith, and core samples from six locations on the nearside of the Moon. Today, just over 84% by mass of the Apollo collection remains in pristine condition within the curation facility at Johnson Space Center. Most Apollo samples have been well characterized, however there are several types of samples that have remained wholly or largely unstudied since their return, and/or that have been curated under special conditions. These sample types are: (1) unopened samples sealed under vacuum on the Moon; (2) unopened (but unsealed) drive tubes; (3) Apollo 17 samples frozen shortly after their return; and (4) Apollo 15 samples opened and stored in a helium atmosphere since their return. Last summer, NASA solicited proposals for the Apollo Next Generation Sample Analysis Program (ANGSA), and 9 teams were selected to study: (1) unsealed, unopened drive tube 73002; (2) sealed, unopened drive tube 73001 (paired with 73002); and (3) a subset of the frozen and He-purged samples [1]. The first sample opened as part of the ANGSA program was drive tube 73002. This is a 30 cm long, 4 cm diameter drive tube collected on a landslide deposit near Lara Crater at the Apollo 17 landing site. It was part of a 60 cm long double drive tube collected, and the bottom half of the tube (73001) was sealed under vacuum on the Moon [2]. Prior to opening sample 73002, the sample was imaged with a high resolution Xray Computed Tomography (XCT) scan of the entire tube. Additional XCT scans have been made of “large” clasts removed from the core as part of the dissection process [3]. Here we present a first look at the XCT data from 73002, and talk about the utility of the scans as part of the curation process, including the potential for future science returns from the high resolutions scans.

Zeigler, R. A.↗
NASA NTRSDate not supplied

Using X-Ray Computed Tomography to Image Apollo Drive Tube 73002

The Apollo missions collected 382 kg of rock, regolith, and core samples from six locations on the nearside of the Moon. Today, just over 84% by mass of the Apollo collection remains in pristine condition within the curation facility at Johnson Space Center. Most Apollo samples have been well characterized, however there are several types of samples that have remained wholly or largely unstudied since their return, and/or that have been curated under special conditions. These sample types are: (1) unopened samples sealed under vacuum on the Moon; (2) unopened (but unsealed) drive tubes; (3) Apollo 17 samples frozen shortly after their return; and (4) Apollo 15 samples opened and stored in a helium atmosphere since their return. NASA solicited proposals for the Apollo Next Generation Sample Analysis Program (ANGSA), and 9 teams were selected to study: (1) unsealed, unopened drive tube 73002; (2) sealed, unopened drive tube 73001 (paired with 73002); and (3) a subset of the frozen and He-purged samples [1]. The first sample opened as part of the ANGSA program was drive tube 73002. This was originally a ~30 cm long, 4 cm diameter drive tube collected on a landslide deposit near Lara Crater at the Apollo 17 landing site. It was part of a ~60 cm long double drive tube collected, and the bottom half of the tube (73001) was sealed under vacuum on the Moon [2]. Prior to opening sample 73002, the sample was imaged with a high resolution X-ray Computed Tomography (XCT) scan of the entire tube. Additional XCT scans have been made of “large” clasts removed from the core as part of the dissection process [3]. Here we present the whole tube and close-up XCT data from 73002, and talk about the utility of the scans as part of the curation process, including the potential for future science returns from the high resolutions scans.

R A Zeigler↗
NASA NTRS1987

Gravity field fine structure estimation techniques for a spaceborne gravity gradiometer

Use of standard estimation techniques to recover geopotential fine structure from gradiometer data requires the adjustment of small subsets of parameters while constraining others to their a priori values in order to minimize the computational load. Here, gravitational anomalies are selected as a parametrization of the gravity field which permits such an approach. Techniques coupled with numerical results for a spaceborne gravity gradiometer mission simulation are described which demonstrate that if a satellite is in a polar/circular orbit at an altitude of 160 km, 1 deg mean free air gravity anomalies can be recovered to an accuracy of 0.4 mgal, where 1 mgal = 0.001 cm/sq s.

Kahn, W. D.↗
NASA NTRS2007

Emission-Line Galaxies from the PEARS Hubble Ultra Deep Field: A 2-D Detection Method and First Results

The Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) grism PEARS (Probing Evolution And Reionization Spectroscopically) survey provides a large dataset of low-resolution spectra from thousands of galaxies in the GOODS North and South fields. One important subset of objects in these data are emission-line galaxies (ELGs), and we have investigated several different methods aimed at systematically selecting these galaxies. Here we present a new methodology and results of a search for these ELGs in the PEARS observations of the Hubble Ultra Deep Field (HUDF) using a 2D detection method that utilizes the observation that many emission lines originate from clumpy knots within galaxies. This 2D line-finding method proves to be useful in detecting emission lines from compact knots within galaxies that might not otherwise be detected using more traditional 1D line-finding techniques. We find in total 96 emission lines in the HUDF, originating from 81 distinct "knots" within 63 individual galaxies. We find in general that [0 1111 emitters are the most common, comprising 44% of the sample, and on average have high equivalent widths (70% of [0 1111 emitters having rest-frame EW> 100A). There are 12 galaxies with multiple emitting knots; several show evidence of variations in H-alpha flux in the knots, suggesting that the differing star formation properties across a single galaxy can in general be probed at redshifts approximately greater than 0.2 - 0.4. The most prevalent morphologies are large face-on spirals and clumpy interacting systems, many being unique detections owing to the 2D method described here, thus highlighting the strength of this technique.

Gardner, J. P.↗
NASA NTRS2012

The Effects of an Absorbing Smoke Layer on MODIS Marine Boundary Layer Cloud Optical Property Retrievals and Radiative Forcing

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer . (MBL) clouds off the southern Atlantic coast of Africa and the effects on MODIS cloud optical property retrievals (MOD06) of an overlying absorbing smoke layer. During much of August and September, a persistent smoke layer resides over this region, produced from extensive biomass burning throughout the southern African savanna. The resulting absorption, which increases with decreasing wavelength, potentially introduces biases into the MODIS cloud optical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 micron (effective particle size retrievals are derived from the longer-wavelength near-IR channels at 1.6, 2.1, and 3.7 microns). Here, the spatial distributions of the scalar statistics of both the cloud and aerosol layers are first determined from the CALIOP 5 km layer products. Next, the MOD06 look-up tables (LUTs) are adjusted by inserting an absorbing smoke layer of varying optical thickness over the cloud. Retrievals are subsequently performed for a subset of MODIS pixels collocated with the CALIOP ground track, using smoke optical thickness from the CALIOP 5km aerosol layer product to select the appropriate LUT. The resulting differences in cloud optical property retrievals due to the inclusion of the smoke layer in the LUTs will be examined. In addition, the direct radiative forcing of this smoke layer will be investigated from the perspective of the cloud optical property retrieval differences.

Meyer, Kerry↗
NASA NTRS2018

Preparation for Pick-and-Eat Food Production on the International Space Station: Flight Definition for the VEG-04 and VEG-05 Missions

Growth of fresh, nutritious, palatable produce for crew consumption during spaceflight may provide health-promoting, bioavailable nutrients and enhance the dietary experience as we move toward longer-duration missions. Tending plants also may serve as a countermeasure for crew psychological stresses associated with long duration spaceflight. However, requirements to support consistent growth of a variety of high quality, nutritious crops under spaceflight environmental conditions is unknown. This study is exploring the potential to grow plants for food production on the International Space Station (ISS) using the Veggie vegetable production system. Ground testing is underway to compare the impacts of several fertilizer and lighting treatments on growth, quality, and nutritional composition of the leafy green crop mizuna, and the dwarf tomato crop Red Robin when subjected to Veggie ISS environmental conditions. Early testing focused on the leafy crop Tokyo Bekana Chinese cabbage, but ground tests indicated that this plant suffered from stress responses when grown under LEDs and the chronically elevated CO2 levels found on the ISS. Mizuna, a related leafy variety that grows well in the presence of high CO2, and has excellent organoleptic characteristics, was selected as an alternate crop. Tomato crops have been grown using two fertilizer formulations and two pollination techniques, and growth tests using different red:blue lighting environments are underway. Chemical analysis is also being conducted and these data, when coupled with the growth results, will be used to down-select to the two best lighting treatments and best fertilizer treatment for future testing of each crop on the ISS. Additionally, seed-source testing has become important, with mizuna seeds from two different vendors growing very differently. A seed source has been selected, and seed-surface-sanitizing methods have been confirmed for mizuna, but these remain under development for tomato. A crop-handling protocol is also being evaluated to support food safety. All harvests reserve a subset of samples for microbial analysis to determine baseline microbial levels and help establish critical control points for food safety. Testing was initially conducted in hardware analogs of the standard Veggie plant pillows. However, a new Veggie watering system, the Passive Orbital Nutrient Delivery System or PONDS, has been designed and is being prepared for future flight experiments. With the selection of this growth system, ground tests have shifted to analog PONDS systems. Crop tests on ISS, designated VEG-04 for mizuna and VEG-05 for tomato, are planned in 2018 to evaluate any additional impacts of spaceflight on the light and fertilizer conditions down-selected from ground tests. A set of Veggie-specific questions has been developed to characterize the psychological impacts of plant growth and plant-care activities during spaceflight. Organoleptic questionnaires have been developed to assess produce attributes in microgravity taste sessions. These tests for plants growing in the Veggie hardware on ISS will help to mitigate the risk of an inadequate food supply for long duration missions by developing methods and determining hardware requirements to integrate fresh vegetables as a dietary supplement. This research was co-funded by the Human Research Program and Space Biology (MTL1075) in the ILSRA 2015 NRA call.

Veggie↗
NASA NTRS2018

Preparation for Pick-and-Eat Food Production on the International Space Station: Flight Definition for the VEG-04 and VEG-05 Missions

Growth of fresh, nutritious, palatable produce for crew consumption during spaceflight may provide health-promoting, bioavailable nutrients and enhance the dietary experience as we move toward longer-duration missions. Tending plants also may serve as a countermeasure for crew psychological stresses associated with long duration spaceflight. However, requirements to support consistent growth of a variety of high quality, nutritious crops under spaceflight environmental conditions is unknown. This study is exploring the potential to grow plants for food production on the International Space Station (ISS) using the Veggie vegetable production system. Ground testing is underway to compare the impacts of several fertilizer and lighting treatments on growth, quality, and nutritional composition of the leafy green crop mizuna, and the dwarf tomato crop "Red Robin" when subjected to Veggie ISS environmental conditions. Early testing focused on the leafy crop "Tokyo Bekana" Chinese cabbage, but ground tests indicated that this plant suffered from stress responses when grown under LEDs and the chronically elevated CO2 levels found on the ISS. Mizuna, a related leafy variety that grows well in the presence of high CO2, and has excellent organoleptic characteristics, was selected as an alternate crop. Tomato crops have been grown using two fertilizer formulations and two pollination techniques, and growth tests using different red:blue lighting environments are underway. Chemical analysis is also being conducted and these data, when coupled with the growth results, will be used to down-select to the two best lighting treatments and best fertilizer treatment for future testing of each crop on the ISS. Additionally, seed-source testing has become important, with mizuna seeds from two different vendors growing very differently. A seed source has been selected, and seed-surface-sanitizing methods have been confirmed for mizuna, but these remain under development for tomato. A crop-handling protocol is also being evaluated to support food safety. All harvests reserve a subset of samples for microbial analysis to determine baseline microbial levels and help establish critical control points for food safety. Testing was initially conducted in hardware analogs of the standard Veggie plant pillows. However, a new Veggie watering system, the Passive Orbital Nutrient Delivery System or PONDS, has been designed and is being prepared for future flight experiments. With the selection of this growth system, ground tests have shifted to analog PONDS systems. Crop tests on ISS, designated VEG-04 for mizuna and VEG-05 for tomato, are planned in 2018 to evaluate any additional impacts of spaceflight on the light and fertilizer conditions down-selected from ground tests. A set of Veggie-specific questions has been developed to characterize the psychological impacts of plant growth and plant-care activities during spaceflight. Organoleptic questionnaires have been developed to assess produce attributes in microgravity taste sessions. These tests for plants growing in the Veggie hardware on ISS will help to mitigate the risk of an inadequate food supply for long duration missions by developing methods and determining hardware requirements to integrate fresh vegetables as a dietary supplement. This research was co-funded by the Human Research Program and Space Biology (MTL#1075) in the ILSRA 2015 NRA call.

LED light↗
NASA NTRS1999

High-Resolution Spectroscopy of Auroras on Jupiter and Saturn/Earth Dayglow

The purpose of the grant was to allow the researcher to: (1) reduce and analyze Orbiting and Retrievable Far and Extreme Ultraviolet Spectrometers (ORFEUS) II observations of Jupiter (200s) and Saturn (1200s); (2) Reduce and analyze selected ORFEUS-II Earth Far Ultraviolet (FUV) airglow data; (3) Modify existing scripts for simulating Earth FUV airglow emissions to model a subset of the ORFEUS data.

Gladstone, G. Randall↗
NASA NTRS2012

CHARM: A CubeSat Water Vapor Radiometer for Earth Science

The Jet Propulsion Laboratory (JPL) and Ames Research Center (ARC) are partnering in the CubeSat Hydrometric Atmospheric Radiometer Mission (CHARM), a water vapor radiometer integrated on a 3U CubeSat platform, selected for implementation under NASA Hands-On Project Experience (HOPE-3). CHARM will measure 4 channels at 183 GHz water vapor line, subsets of measurements currently performed by larger and more costly spacecraft (e.g. ATMS, AMSU-B and SSMI/S). While flying a payload that supports SMD science objectives, CHARM provides a hands-on opportunity to develop technical, leadership, and project skills. CHARM will furthermore advance the technology readiness level (TRL) of the 183 GHz receiver subsystem from TRL 4 to TRL 6 and the CubeSat 183 GHz radiometer system from TRL 4 to TRL 7.

Monolithic microwave integrated circuits (MMICs)↗
NASA NTRSDate not supplied

Laboratory Radar Measurements in Support of the NASA Orbital Debris Program Office’s Size Estimation Model

The NASA Orbital Debris Program Office (ODPO) relies on ground-based radar measurements from both the Haystack Ultrawideband Satellite Imaging Radar (HUSIR) and the Goldstone Solar System Radar (Goldstone) to characterize mm to cm debris population in low Earth orbit (LEO). Radar measurements help characterize the size of orbital debris objects, particularly fragmentation debris. However, debris size is not directly measured by radar but inferred from the measured radar cross section (RCS) which depends on several parameters in addition to physical size including electrical conductivity and polarization. To interpret the observed RCS of orbital debris objects detected by radar measurements as physical sizes, NASA uses an empirical size estimation model (SEM) based on laboratory RCS measurements of breakup fragments generated during hypervelocity impact tests as well as some pieces of non-impact-generated “artificial” debris-like objects expected to be representative of the debris population. Since the development of the ODPO SEM, many new materials have been introduced to spacecraft construction. Consequently, ODPO plans to update the radar SEM based on planned laboratory RCS measurements of debris fragments from DebriSat, a ground-based hypervelocity impact experiment conducted in 2014 that consisted of a high-fidelity spacecraft model characteristic of a modern LEO spacecraft. Prior to measuring DebriSat fragments, a set of calibration targets with well-defined geometries and material compositions were measured at The Ohio State University’s ElectroScience Laboratory (OSU-ESL) compact radar range. These calibration measurements help to validate, and understand any limitations of, laboratory measurements of RCS. Calibration targets include idealizations of typical shape categories seen in DebriSat fragments such as nuggets, flat plates, and cylinders. As with DebriSat, calibration target materials were chosen to represent typical modern-day spacecraft components and include stainless steel, aluminum, printed circuit board (PCB) substrate, and carbon fiber-reinforced polymer (CFRP). These materials also represent a wide range of electrical conductivities, which strongly influences measured RCS and inferred target size. The RCS calibration measurements were collected over a frequency sweep from 2 to 18 GHz and stepping through different azimuth angles from 0 to 360 degrees at an elevation of 0 degrees. A second set of calibration measurements is in work consisting of more complex shapes such as bent rods and plates as well as different mounting options including epoxy and a 3D printed holder. These further measurements along with our initial calibration set will inform selection of representative DebriSat fragments for laboratory RCS measurements that will contribute to the planned update to the ODPO radar SEM. An appropriate subset of both the radar calibration and DebriSat samples will also be measured in the ODPO Optical Measurements Center to cross-calibrate size estimates over these different wavelength regimes.

Radar↗
NASA NTRS2010

Fast Solution in Sparse LDA for Binary Classification

An algorithm that performs sparse linear discriminant analysis (Sparse-LDA) finds near-optimal solutions in far less time than the prior art when specialized to binary classification (of 2 classes). Sparse-LDA is a type of feature- or variable- selection problem with numerous applications in statistics, machine learning, computer vision, computational finance, operations research, and bio-informatics. Because of its combinatorial nature, feature- or variable-selection problems are NP-hard or computationally intractable in cases involving more than 30 variables or features. Therefore, one typically seeks approximate solutions by means of greedy search algorithms. The prior Sparse-LDA algorithm was a greedy algorithm that considered the best variable or feature to add/ delete to/ from its subsets in order to maximally discriminate between multiple classes of data. The present algorithm is designed for the special but prevalent case of 2-class or binary classification (e.g. 1 vs. 0, functioning vs. malfunctioning, or change versus no change). The present algorithm provides near-optimal solutions on large real-world datasets having hundreds or even thousands of variables or features (e.g. selecting the fewest wavelength bands in a hyperspectral sensor to do terrain classification) and does so in typical computation times of minutes as compared to days or weeks as taken by the prior art. Sparse LDA requires solving generalized eigenvalue problems for a large number of variable subsets (represented by the submatrices of the input within-class and between-class covariance matrices). In the general (fullrank) case, the amount of computation scales at least cubically with the number of variables and thus the size of the problems that can be solved is limited accordingly. However, in binary classification, the principal eigenvalues can be found using a special analytic formula, without resorting to costly iterative techniques. The present algorithm exploits this analytic form along with the inherent sequential nature of greedy search itself. Together this enables the use of highly-efficient partitioned-matrix-inverse techniques that result in large speedups of computation in both the forward-selection and backward-elimination stages of greedy algorithms in general.

Moghaddam, Baback↗
NASA NTRS2015

A Data Exploration Tool for Large Sets of Spectra

We present an exploration tool for very large spectrum data sets such as the SDSS (Sloan Digital Sky Survey), LAMOST (Large Sky Area Multi-Object Fiber Spectroscopic Telescope), and 4MOST (4-meter Multi-Object Spectroscopic Telescope) data sets. The tool works in two stages: the first uses batch processing and the second runs interactively. The latter employs the NASA hyperwall, a configuration of 128 workstation displays (8 by 16 array) controlled by a parallelized software suite running on NASA's Pleiades supercomputer. The stellar subset of the Sloan Digital Sky Survey, DR10, was chosen to show how the our tool may be used. In stage one, SDSS files for 569,740 stars are processed through our data pipeline. The pipeline fits each spectrum using an iterative continuum algorithm, distinguishing emission from absorption and handling molecular absorption bands correctly. It then measures 1659 discrete atomic and molecular spectral features that were carefully preselected based on their likelihood of being visible at some spectral type. The depths relative to the local continuum at each feature wavelength are determined for each spectrum: these depths, the local S/N (signal to noise ratio) level, and DR10-supplied variables such as magnitudes, colors, positions, and radial velocities are the basic measured quantities used on the hyperwall. In stage two, each hyperwall panel is used to display a 2-D scatter plot showing the depth of feature A vs the depth of feature B for all of the stars. A and B change from panel to panel. The relationships between the various (A,B) strengths and any distinctive clustering are immediately apparent when examining and inter-comparing the different panels on the hyperwall. The interactive software allows the user to select the stars in any interesting region of any 2-D plot on the hyperwall, immediately rendering the same stars on all the other 2-D plots in a unique color. The process may be repeated multiple times, each selection displaying a distinctive color on all the plots. At any time, the spectra of the selected stars may be examined in detail on a connected workstation display. We illustrate how our approach allows us to quickly isolate and examine such interesting stellar subsets as EMP (Extremely Metal‐Poor) stars, CV (Cataclymic Variable) stars and C (Carbon)-rich stars.

Data Exploration↗
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 NTRS1987

A natural language query system for Hubble Space Telescope proposal selection

The proposal selection process for the Hubble Space Telescope is assisted by a robust and easy to use query program (TACOS). The system parses an English subset language sentence regardless of the order of the keyword phases, allowing the user a greater flexibility than a standard command query language. Capabilities for macro and procedure definition are also integrated. The system was designed for flexibility in both use and maintenance. In addition, TACOS can be applied to any knowledge domain that can be expressed in terms of a single reaction. The system was implemented mostly in Common LISP. The TACOS design is described in detail, with particular attention given to the implementation methods of sentence processing.

Hornick, Thomas↗
NASA NTRS2016

Characterize Aerosols from MODIS MISR OMI MERRA-2: Dynamic Image Browse Perspective

Among the known atmospheric constituents, aerosols still represent the greatest uncertainty in climate research. To understand the uncertainty is to bring altogether of observational (in-situ and remote sensing) and modeling datasets and inter-compare them synergistically for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if these earth science data (satellite and modeling) are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite-borne sensors routinely measure aerosols. There is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) have developed a new visualization service (NASA Level 2 Data Quality Visualization, DQViz)supporting various visualization and data accessing capabilities from satellite Level 2(MODISMISROMI) and long term assimilated aerosols from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2 displaying at their own native physical-retrieved spatial resolution. Functionality will include selecting data sources (e.g., multiple parameters under the same measurement), defining area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting and reformatting.

data quality↗