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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 NTRS1992

Database activity in the Italian Astronet: DIRA 2

The development and utilization of informational archives and databases started, in the Italian Astronet Project, in the middle of 1983. In that year, a small group of astronomers and some more technical people met together in an Astronet working group, with a common, painful experience in managing astronomical catalogues and archives with computers. Nowadays, some years later, some software packages and the contents of both, a relative general database and several local databases represent the work and the effort of the group. The systems have been conceived and developed keeping in mind the original goal of the group: to allow the single atronomer to make a free use of original data. The main package (DIRA) was rewritten, after some years of use, to fully take advantage of the several suggestions of the astronomer that used it and gathered experiences in the astronomical catalog's management. A more technical goal was to install the whole system, born and developed in the vms environment, on unix and unix-like systems. This new version, DIRA2, has a new user interface, a query language with SQL style commands supporting numerical and character functions also and a set of commands to create new catalogues from existing data. The graphics commands are also more powerful with respect to the previous version. DIRA (and DIRA2 of course) philosophy and design are very simple and proved to be very appreciated by astronomers, namely, to normalize and homogenize, at minimum, astronomical catalogues, to collect satisfactory astronomical documentation on their contents and, finally, to allow an astronomical approach to the dialogue with the database. DIRA2 is currently used in most Italian astronomical institutes to retrieve data from a still growing database of about 140 well documented and controlled astronomical catalogues, for the identification of objects and the preparation of a 'medium size' survey, in astrometry and in the creation of new catalogues.

Benacchio, L.↗
NASA NTRS2019

TPSAS-NF1676L-32493-DND

The Committee on Earth Observation Satellites (CEOS) System Engineering Office (SEO) has supported the Open Data Cube (ODC) initiative to provide a data architecture solution that has value to its global users and increases the impact of EO satellite data. ODC is an open-source platform for processing satellite data. We have developed software products and tools around the core ODC that would help users perform machine learning on EO satellite data. The recent United Nations (UN) Sustainable Development Agenda provides a shared blueprint for peace and prosperity for people and for the planet, considering our current situation and helping to create a plan. The core of this agenda is a set of seventeen Sustainable Development Goals (SDGs), which represent an urgent call for action by all countries - both developed and developing - in a global partnership. The CEOS SEO team has recently developed and released a set of innovative Jupyter notebooks addressing UN SDGs 6.6.1 (spatial extents of water-related ecosystems), 11.3.1 (ratio of land consumption rate to population growth rate), and 15.3.1 (proportion of land that is degraded over total land area). These notebooks empower users by providing features that will assist with streamlining analysis ready data retrieval, processing, and visualization. We have recently incorporated several machine learning techniques in these notebooks. In this paper, we present the lessons learned from our experience on classifying land using supervised and unsupervised machine learning techniques using ODC framework for UN SDGs. We identify the current limitations of ODC to seamlessly support machine learning techniques. We propose features that would help machine learning, specifically within the ODC framework. We propose a thematic indexing/loading of data for both unsupervised learning as well as data annotation/labeling pipeline. Currently, ODC supports machine learning by separating data-management from the analysis process. It works as a mechanism to load cubes of data. ODC does not natively support features that are vital in machine learning such as validation splits, fair/balanced sampling, establishing load size constraints, etc. We believe that our proposed features will empower users by providing features that bring machine learning techniques closed to ODC. Enhancements to ODC to better accommodate machine learning techniques can assist in fulfilling UN SDGs such as 6.3.2, 6.4.2, 6.6.1, 11.3.1, 14.1.1, 15.1.1, 15.3.1, and 15.4.2.

Syed R Rizvi↗
NASA NTRS2010

The Effect of Incident Light Polarization on Vegetation Bidirectional Reflectance Factor

The Laboratory-based Bidirectional Reflectance Factor (BRF) polarization study of vegetation is presented in this paper. The BRF was measured using a short-arc Xenon lamp/monochromator assembly producing an incoherent, tunable light source with a well-defined spectral bandpass at visible and near-infrared wavelengths of interest at 470 nm and 870 nm and coherent light source at 1.656 microns. All vegetation samples were measured using P and S linearly polarized incident light over a range of incident and scatter angles. By comparing these results, we quantitatively examine how the BRF of the samples depends on the polarization of the incident light. The differences are significant, depend strongly on the incident and scatter angles, and can be as high as 120% at 67 deg incident and 470nm. The global nature of Earth's processes requires consistent long-term calibration of all instruments involved in data retrieval. The BRF defines the reflection characteristics of Earth surface. It provides the reflectance of a target in a specific direction as a function of illumination and viewing geometry. The BRF is a function of wavelength and reflects the structural and optical properties of the surface. Various space and airborne radiometric and imaging remote sensing instruments are used in the remote sensing characterization of vegetation canopies and soils, oceans, or especially large pollution sources. The satellite data is validated through comparison with airborne, ground-based and laboratory-based data in an effort to fully understand the vegetation canopy reflectance, The Sun's light is assumed to be unpolarized at the top of the atmosphere; however it becomes polarized to some degree due to atmospheric effects by the time it reaches the vegetation canopy. Although there are numerous atmospheric correction models, laboratory data is needed for model verification and improvement.

Georgiev, Georgi T.↗
NASA NTRSDate not supplied

Data Cube Application Algorithms For The United Nations Sustainable Development Goals (UN-SDGS)

In 2015, all United Nations (UN) Member States adopted the 2030 Agenda for Sustainable Development. The Agenda provides a shared blueprint for peace and prosperity for people and for the planet, considering our current situation and helping to create a plan. The core of this agenda is a set of seventeen Sustainable Development Goals (SDGs), which represent an urgent call for action by all countries -both developed and developing - in a global partnership. The Committee on Earth Observation Satellites (CEOS) Systems Engineering Office (SEO) team has recently developed and released a set of innovative notebooks addressing UN SDGs 6.6.1 (spatial extents of water-related ecosystems), 11.3.1 (ratio of land consumption rate to population growth rate), and 15.3.1 (proportion of land that is degraded over total land area). These notebooks empower users by providing features that will assist with streamlining analysis ready data retrieval, processing, and visualization. The main contributions in this paper are: (1) briefly describing the framework of the UN SDG notebooks, (2) enumerating the notebooks’ salient features, and (3) discussing current limitations and proposing approaches to overcome these limitations.

Open Data Cube↗
NASA NTRS2025

On the Characterization and Mitigation of Noise in Space-borne Microwave Sounding Instruments

Space-borne microwave sounding instruments have become vital data sources for weather prediction and climate change studies. Among the various radiometer configurations, the total power microwave radiometer is particularly appealing for current and future operational satellites due to its superior sensitivity and simple design. However, its performance is vulnerable to degradation caused by receiver gain fluctuations, electronic 1/f noise, and other time varying receiver characteristics. For Numerical Weather Prediction (NWP) users, 1/f noise introduces inter-channel correlations, complicating the assimilation of affected observations and reducing their accuracy. Addressing this noise issue in ground data processing system is essential to enhance the utility of microwave sounding data. This paper focuses on the characterization and mitigation of noise in current and future microwave sounding instruments, with particular emphasis on the impact of 1/f noise. Various methods are applied to quantitatively characterize noise features in both frequency and time domains. Additionally, the influence of calibration parameters on 1/f noise are analyzed. Based on these findings, we propose a mitigation algorithm for reducing noise during the on-orbit calibration of microwave sounding instruments, aiming to improve the quality of retrieved data for operational use.

calibration↗
NASA NTRS2020

Evaluation and Validation of a High Spatial Resolution Satellite Soil Moisture Product over the Continental United States

The soil moisture (SM) data retrieved from the Soil Moisture Active and Passive (SMAP) satellite are available at a 9 km grid spacing since April 2015. This product can provide valuable information for research and applications in hydrology and other related fields. However, the resolution may be too coarse for applications at catchment or field scale. In this study, an established downscaling methodology, which had a major modification regarding its application on the SMAP 33 km domain, was implemented to develop a 1 km soil moisture product based on the SMAP 9 km data. The algorithm proposed here is based on the thermal inertia principle and developed by modeling the relationship between surface temperature difference and SM for different Normalized Difference Vegetation Index (NDVI) classes. The model functions were established and tuned using data from the NASA’s Land Information System (LIS) North America Land Data Assimilation System (NLDAS) and remotely sensed VISible/InfRared (VIS/IR) reflectance data from Long Term Data Record (LTDR) AVHRR (Advanced Very High Resolution Radiometer) for the growing season months of April-September 1981–2018. These were then implemented using the MODIS (Moderate Resolution Imaging Spectroradiometer) data over the Continental United States (CONUS) domain. Validation activities were carried out using in situ measurements distributed through the International Soil Moisture Network (ISMN). The validation results computed using the 1 km SM data showed that the R2, unbiased RMSE (root mean square error) and bias were improved relative to the 9 km SMAP product by 0.045, 0.018m3/m3 and 0.001m3/m3, respectively. The 1 km SM also exhibited a strong time-series autocorrelation. Further accuracy assessment analyses indicated that precipitation might contribute to the uncertainties in both the 9 km SMAP and 1 km downscaled SMAP SM products.

SMAP↗
NASA NTRS2013

Wind Retrieval Algorithms for the IWRAP and HIWRAP Airborne Doppler Radars with Applications to Hurricanes

Algorithms for the retrieval of atmospheric winds in precipitating systems from downward-pointing, conically-scanning airborne Doppler radars are presented. The focus in the paper is on two radars: the Imaging Wind and Rain Airborne Profiler(IWRAP) and the High-altitude IWRAP (HIWRAP). The IWRAP is a dual-frequency (Cand Ku band), multi-beam (incidence angles of 30 50) system that flies on the NOAAWP-3D aircraft at altitudes of 2-4 km. The HIWRAP is a dual-frequency (Ku and Kaband), dual-beam (incidence angles of 30 and 40) system that flies on the NASA Global Hawk aircraft at altitudes of 18-20 km. Retrievals of the three Cartesian wind components over the entire radar sampling volume are described, which can be determined using either a traditional least squares or variational solution procedure. The random errors in the retrievals are evaluated using both an error propagation analysis and a numerical simulation of a hurricane. These analyses show that the vertical and along-track wind errors have strong across-track dependence with values of 0.25 m s-1 at nadir to 2.0 m s-1 and 1.0 m s-1 at the swath edges, respectively. The across-track wind errors also have across-track structure and are on average, 3.0 3.5 m s-1 or 10 of the hurricane wind speed. For typical rotated figure four flight patterns through hurricanes, the zonal and meridional wind speed errors are 2 3 m s-1.Examples of measured data retrievals from IWRAP during an eyewall replacement cycle in Hurricane Isabel (2003) and from HIWRAP during the development of Tropical Storm Matthew (2010) are shown.

atmospheric winds↗
NASA NTRS1972

Engineering study for the functional design of a multiprocessor system

The results are presented of a study to generate a functional system design of a multiprocessing computer system capable of satisfying the computational requirements of a space station. These data management system requirements were specified to include: (1) real time control, (2) data processing and storage, (3) data retrieval, and (4) remote terminal servicing.

Miller, J. S.↗
NASA NTRS1973

The Launch Processing System for Space Shuttle.

In order to reduce costs and accelerate vehicle turnaround, a single automated system will be developed to support shuttle launch site operations, replacing a multiplicity of systems used in previous programs. The Launch Processing System will provide real-time control, data analysis, and information display for the checkout, servicing, launch, landing, and refurbishment of the launch vehicles, payloads, and all ground support systems. It will also provide real-time and historical data retrieval for management and sustaining engineering (test records and procedures, logistics, configuration control, scheduling, etc.).

Springer, D. A.↗
NASA NTRS1974

Management and control of Skylab missions

The flight operations task, as developed in support of the Skylab Program, was evolutionary in nature and, to a great extent, was an orderly extension of the flight control concepts used in the Apollo Program, tempered by the nature of the Skylab Program. During the terminal portion of the Apollo Program, many of the operating concepts proposed for Skylab were tested and used for Apollo support to obtain a realistic evaluation of these new techniques. The principal concept developed in the Apollo Program and augmented in support of the Skylab Program was one wherein a professional operations team would provide support to the scientists in the areas of mission integration, experiment, and experiment support systems, monitoring and control, and data retrieval.

Roach, J. W.↗
NASA NTRS1974

Mars penetrator: Subsurface science mission

A penetrator system to emplace subsurface science on the planet Mars is described. The need for subsurface science is discussed, and the technologies for achieving successful atmospheric entry, Mars penetration, and data retrieval are presented.

Lumpkin, C. K.↗
NASA NTRS1975

Mapping of the wildland fuel characteristics of the Santa Monica mountains of Southern California

LANDSAT digital data was successfully used to map and evaluate the wildland fuels of the Santa Monica Mountains in Southern California. A mixed classification scheme was used where training areas of known vegetation types were entered and the maximum likelihood classifier run, followed by an evaluation of the results and an unsupervised retraining of the classifier using an image of the probability of misclassification. Estimation of maturity class and crown closure percents of the major cover types were assigned to each computer class by associating the photointerpretation of 159 large scale photo samples with the resultant computer classes using analysis of variance and analysis of categorized data. The result of the computer classification and statistical analysis were then transformed from the LANDSAT Coordinate California State Plane Coordinate system for use in a digital format in the FIRESCOPE data retrieval and fire modeling system.

Nichols, J. D.↗
NASA NTRS1976

Nuclear emulsion measurements of the astronauts' radiation exposure on the Apollo-Soyuz mission

On the Apollo-Soyuz mission each astronaut carried one passive dosimeter containing nuclear photographic emulsions, plastic foils, TLD chips, and neutron-activation foils for recording radiation exposure. This report is limited to the presentation of data retrieved from nuclear emulsions. Protons, most of them trapped particles encountered in numerous passes through the South Atlantic Anomaly, contributed by far the largest share to the mission dose. Their linear energy transfer (LET) spectrum was established from track and grain counts in a G.5 emulsion which is used for medium and high energies, and from ender counts in a K.2 emulsion which is used for low energies. The total mission fluence of protons was found to be equivalent to a unidirectional beam of 448,500 square centimeters. The broad spectrum was broken down into small LET intervals, which allowed for the computation of absorbed doses and dose equivalents. The totals are 51 millirad and 74 millirem. Counts of disintegration stars in K.2 emulsion are incomplete at present. While a total of 467 stars were identified, counting their prong numbers is still in progress. It was concluded that the Apollo-Soyuz astronauts' radiation exposure as such did not contain anything out of the ordinary that would seem to require special attention.

Schaefer, H. J.↗
NASA NTRS1976

Crew safety

Crew safety in the manned spaceflight is usually associated with a small group for safety and quality assurance. Crew safety is actually an integral part of all program phases from conception through final implementation. Factors associated with improving safety at each phase of development are discussed. Topics discussed include design, manufacture, hardware/software checkout, management reviews, training and simulation, and data retrieval and analysis. Crew safety is best accomplished by flying a successful mission.

Slayton, D. K.↗
NASA NTRS1976

Radar systems for the water resources mission, volume 3

Recent work was reviewed in the field of remote sensing relative to soil moisture. The target parameters were recognized that are necessary if optimum data retrieval is to be realized, and proper sensor instrumentation was recommended to achieve this goal.

Moore, R. K.↗