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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Wavelet-Based Interpolation and Representation of Non-Uniformly Sampled Spacecraft Mission Data

A well-documented problem in the analysis of data collected by spacecraft instruments is the need for an accurate, efficient representation of the data set. The data may suffer from several problems, including additive noise, data dropouts, an irregularly-spaced sampling grid, and time-delayed sampling. These data irregularities render most traditional signal processing techniques unusable, and thus the data must be interpolated onto an even grid before scientific analysis techniques can be applied. In addition, the extremely large volume of data collected by scientific instrumentation presents many challenging problems in the area of compression, visualization, and analysis. Therefore, a representation of the data is needed which provides a structure which is conducive to these applications. Wavelet representations of data have already been shown to possess excellent characteristics for compression, data analysis, and imaging. The main goal of this project is to develop a new adaptive filtering algorithm for image restoration and compression. The algorithm should have low computational complexity and a fast convergence rate. This will make the algorithm suitable for real-time applications. The algorithm should be able to remove additive noise and reconstruct lost data samples from images.

Bose, Tamal↗
NASA NTRS1982

Data processing for a cosmic ray experiment onboard the solar probes Helios 1 and 2: Experiment 6

The data processing system for the Helios experiment 6, measuring energetic charged particles of solar, planetary and galactic origin in the inner solar system, is described. The aim of this experiment is to extend knowledge on origin and propagation of cosmic rays. The different programs for data reduction, analysis, presentation, and scientific evaluation are described as well as hardware and software of the data processing equipment. A chronological presentation of the data processing operation is given. Procedures and methods for data analysis which were developed can be used with minor modifications for analysis of other space research experiments.

Mueller-Mellin, R.↗
NASA NTRS2008

Hyperspectral Sun Photometer for Atmospheric Characterization and Vicarious Calibrations

A hyperspectral sun photometer and associated methods have been developed and demonstrated. Accurate sun photometer calibration is critical to properly measure the solar irradiance and characterize the atmosphere. Traditional sun photometer calibration requires solar observations over several hours. In contrast, the procedures for operating this photometer entail less data acquisition time and embody a more direct approach to calibration. The scientific value of the measurement data produced by this instrument is not adversely affected by atmospheric instability. In addition, this instrument yields hyperspectral data covering a large spectral range (350-2,500 nm) not available from most traditional sun photometers. The hyperspectral sun photometer components include (1) a commercially available spectroradiometer that has been laboratory-calibrated and (2) a commercially available reflectance standard panel that exhibits nearly Lambertian 99% reflectance. The spectroradiometer is positioned above, and aimed downward at, the panel. The procedure for operating this instrument calls for a series of measurements: one in which the panel is fully illuminated by the sun, one in which a shade is positioned between the panel and the sun, and two in which the shade is positioned to cast a shadow to either side of the panel. The total sequence of measurements can be performed in less than a minute. From these measurements, the total radiance, the diffuse radiance, and the direct solar radiance are calculated. The direct solar irradiance is calculated from the direct solar radiance and the known reflectance factor of the panel as a function of the solar zenith angle. Atmospheric characteristics are estimated from the optical depth at various wavelengths calculated from (1) the direct solar irradiance obtained as described above, (2) the air mass along a column from the measurement position to the Sun, and (3) the top-of-atmosphere solar irradiance. The instrumentation used to implement the sun photometer is the same as that used to characterize targets used in radiometric vicarious calibrations. Utilizing this type of sun photometer thus reduces the amount of instrumentation and labor required to perform these studies.

Pagnutti, Mary↗
NASA NTRS2017

An Innovative Infrastructure with a Universal Geo-Spatiotemporal Data Representation Supporting Cost-Effective Integration of Diverse Earth Science Data

The SpatioTemporal Adaptive Resolution Encoding (STARE) is a unifying scheme encoding geospatial and temporal information for organizing data on scalable computing/storage resources, minimizing expensive data transfers. STARE provides a compact representation that turns set-logic functions into integer operations, e.g. conditional sub-setting, taking into account representative spatiotemporal resolutions of the data in the datasets. STARE geo-spatiotemporally aligns data placements of diverse data on massive parallel resources to maximize performance. Automating important scientific functions (e.g. regridding) and computational functions (e.g. data placement) allows scientists to focus on domain-specific questions instead of expending their efforts and expertise on data processing. With STARE-enabled automation, SciDB (Scientific Database) plus STARE provides a database interface, reducing costly data preparation, increasing the volume and variety of interoperable data, and easing result sharing. Using SciDB plus STARE as part of an integrated analysis infrastructure dramatically eases combining diametrically different datasets.

Rilee, Michael Lee↗
NASA NTRS2024

Effective Visualization of Radar Data for Users Impacted By Color Vision Deficiency

Color Vision Deficiency (CVD) is a decreased ability to discern between particular colors. Eight percent of genetic males and half a percent of genetic females have some form of CVD, with many in the radar community falling into this group. When presenting data on a two-dimensional plane, it is common to use colors to represent values via a colormap. Colormap choice in the radar community is influenced by the ability to highlight scientifically interesting features in data, institutional choices, and domain dominance of legacy colormaps. The problem with these current colormaps is that many do not project well for those with CVD (i.e., green next to red). In working with the CVD community to address this problem, multiple colormaps for moments such as equivalent reflectivity factor and Doppler velocity were created for users with forms of CVD such as deuteranomaly, protanomaly, protanopia, and deuteranopia using Python tools such as colorspacious and viscm. We show how these colormaps can improve interpretability for four cases: a mesoscale convective system, a pyrocumulonimbus storm, a wintertime mid-latitude cyclone, and widespread storms with a large bird migration. These new radar equivalent reflectivity factor, Doppler velocity, and polarization colormaps are designed to highlight rain, frozen precipitation, non-meteorological targets, velocity-based items, be perceptually uniform, and visually friendly for those with CVD.

Zachary Sherman↗
NASA NTRS1980

Data processing system for the Sneg-2MP experiment

The data processing system for scientific experiments on stations of the "Prognoz" type provides for the processing sequence to be broken down into a number of consecutive stages: preliminary processing, primary processing, secondary processing. The tasks of each data processing stage are examined for an experiment designed to study gamma flashes of galactic origin and solar flares lasting from several minutes to seconds in the 20 kev to 1000 kev energy range.

Gavrilova, Y. A.↗
NASA NTRS1972

Monitoring of solar far ultraviolet radiation from the OSO-5 satellite

A spectrophotometer for monitoring the solar EUV in three broad wavelength bands is described. The kind of data obtained, along with sources of error, are presented. The content of the tape library which contains the data is outlined. The scientific results are discussed. These include the following: solar flares in the EUV, solar eclipse observations in the EUV, SFD's and relationship to solar flares, and the application of satellite sunrise and sunset data for the study of model upper atmospheres for the earth.

Rense, W. A.↗
NASA NTRS2018

Overview of SAND-E: Semi-Autonomous Navigation for Detrital Environments

Rovers are the state of the art for the exploration and detection of past habitability and life on other worlds. One of the most basic functions of a rover is terrain navigation. Information collected by the rover is used autonomously to mitigate terrain hazards such large rocks, while humans qualitatively assess hazardous geologic terrain such as soil type and degree of rock cover. Planetary scientists use the same information to select targets such as drill sites, and for basic scientific analysis such as characterization of rock outcrops. Although the data is complementary, data from terrain analysis for navigation and terrain analysis for scientific investigations are poorly integrated. The lack of integration creates science and operation inefficiencies that limit exploration of habitable environments. As new modes of exploration come online, such as unmanned aerial systems (UAS) (e.g., the Mars Helicopter Scout and Titan Dragonfly), a need exists to integrate terrain data and science analysis to improve operational and scientific outcomes during exploration. We present an overview of a project aimed at evaluating the effectiveness and capability rover and UAS-based semi-automated terrain analysis using the Automated Soil Assessment Systems (ASAS) developed by Mission Control Space Services for navigating, selecting targets for sampling, and characterizing mafic detrital sediments along glacio-fluvial-aeolian sand transport pathways in Iceland. We describe recent advances in automated terrain analysis in sandy environments and scientific uses of terrain assessment from sandy environments. We assess fluvial and aeolian terrains in Iceland and show how terrain analysis data can inform scientific characterization of these environments.

Ewing, Ryan C.↗
NASA NTRS1973

On board satellite processing study

The use of satellite-based, world-wide data collection and location systems for scientific purposes is discussed. The configuration of satellite borne data handling equipment to prevent premature saturation and to provide maximum capacity without degradation of performance is described. An analysis of a data collection and location system based on random time and frequency access to the satellite was conducted. The subjects presented are: (1) a general description of the concept of a random access system, (2) the quantitative characteristics of random access systems, and (3) the development of a model for comparing the various types of digital communications systems.

Reed, D. L.↗
NASA NTRS1993

An ASIC memory buffer controller for a high speed disk system

The need for large capacity, high speed mass memory storage devices has become increasingly evident at NASA during the past decade. High performance mass storage systems are crucial to present and future NASA systems. Spaceborne data storage system requirements have grown in response to the increasing amounts of data generated and processed by orbiting scientific experiments. Predictions indicate increases in the volume of data by orders of magnitude during the next decade. Current predictions are for storage capacities on the order of terabits (Tb), with data rates exceeding one gigabit per second (Gbps). As part of the design effort for a state of the art mass storage system, NASA Langley has designed a 144 CMOS ASIC to support high speed data transfers. This paper discusses the system architecture, ASIC design and some of the lessons learned in the development process.

Hodson, Robert F.↗
NASA NTRS1994

Software agents for the dissemination of remote terrestrial sensing data

Remote terrestrial sensing (RTS) data is constantly being collected from a variety of space-based and earth-based sensors. The collected data, and especially 'value-added' analyses of the data, are finding growing application for commercial, government, and scientific purposes. The scale of this data collection and analysis is truly enormous; e.g., by 1995, the amount of data available in just one sector, NASA space science, will reach 5 petabytes. Moreover, the amount of data, and the value of analyzing the data, are expected to increase dramatically as new satellites and sensors become available (e.g., NASA's Earth Observing System satellites). Lockheed and other companies are beginning to provide data and analysis commercially. A critical issue for the exploitation of collected data is the dissemination of data and value-added analyses to a diverse and widely distributed customer base. Customers must be able to use their computational environment (eventually the National Information Infrastructure) to obtain timely and complete information, without having to know the details of where the relevant data resides and how it is accessed. Customers must be able to routinely use standard, widely available (and, therefore, low cost) analyses, while also being able to readily create on demand highly customized analyses to make crucial decisions. The diversity of user needs creates a difficult software problem: how can users easily state their needs, while the computational environment assumes the responsibility of finding (or creating) relevant information, and then delivering the results in a form that users understand? A software agent is a self-contained, active software module that contains an explicit representation of its operational knowledge. This explicit representation allows agents to examine their own capabilities in order to modify their goals to meet changing needs and to take advantage of dynamic opportunities. In addition, the explicit representation allows agents to advertize their capabilities and results to other agents, thereby allowing the collection of agents to reuse each others work.

Toomey, Christopher N.↗
NASA NTRS1995

Scientific visualization tools for the ISTP project: Mission planning, data analysis and model interpretation

Visualization tools are being developed to meet the challenges of mission planning and data analysis presented by the International Solar-Terrestrial Physics (ISTP) program. ISTP encompasses a large number of spacecraft, multiple ground-based observatories, and several theoretical investigations, with the goal of understanding the global behavior of the solar wind/magnetosphere/ionosphere system. The tools include three-dimensional displays of key boundaries in geospace along with spacecraft trajectories, which can be animated and synchronized to universal time. Magnetic field models and MHD simulation results can be invoked to reveal the magnetic topology or to identify magnetic conjunctions between spacecraft and/or ground-based facilities. Simultaneous displays of satellite trajectories, spacecraft-borne observations, and model predictions are available to facilitate data processing and interpretation efforts. The current status of these tools is described, and their implementation at the ISTP Science Planning and Operations Facility and distribution to the entire ISTP community are discussed.

Peredo, M.↗
NASA NTRS2016

Climate Analytics as a Service

Exascale computing, big data, and cloud computing are driving the evolution of large-scale information systems toward a model of data-proximal analysis. In response, we are developing a concept of climate analytics as a service (CAaaS) that represents a convergence of data analytics and archive management. With this approach, high-performance compute-storage implemented as an analytic system is part of a dynamic archive comprising both static and computationally realized objects. It is a system whose capabilities are framed as behaviors over a static data collection, but where queries cause results to be created, not found and retrieved. Those results can be the product of a complex analysis, but, importantly, they also can be tailored responses to the simplest of requests. NASA's MERRA Analytic Service and associated Climate Data Services API provide a real-world example of climate analytics delivered as a service in this way. Our experiences reveal several advantages to this approach, not the least of which is orders-of-magnitude time reduction in the data assembly task common to many scientific workflows.

big data↗
NASA NTRSDate not supplied

Entwine Point Tiles for 3D Visualization and Querying of ICESat-2

Point Cloud data from non-optical sensors present challenges in scientific computing in both volume of data and files, even for cloud services environments. As part of the Multi-Mission Algorithm and Analysis Platform (MAAP), a joint open science platform for global biomass modelling, we’ve developed a cloud optimized workflow for using ATL08 (ICESat-2) data as a point cloud. For MAAP, the ATL08 data product is published as Entwine Point Tiles (EPT), allowing users to visualize and query the full extent of this collection interactively without pre-downloading, or preprocessing. The EPT format is a cloud-optimized point cloud data format which re-organizes points into a cloud friendly spatially indexed data structure. MAAP uses AWS S3 to store these point clouds and serves them over OGC specified APIs, 3DTiles for visualization, and WFS for querying. This workflow allows for interactive 3D visualizations in a web browser, including notebook environments and facilitates on the fly subsetting for interactive data exploration, all of which can be applied to other similar sensors.

Alex Mandel↗
NASA NTRS1984

Solar-terrestrial data access distribution and archiving

It is recommended that a central data catalog and data access network (CDC/DAN) for solar-terrestrial research be established, initially as a NASA pilot program. The system is envisioned to be flexible and to evolve as funds permit, starting from a catalog to an access network for high-resolution data. The report describes the various functional requirements for the CDC/DAN, but does not specify the hardware and software architectures as these are constantly evolving. The importance of a steering committee, working with the CDC/DAN organization, to provide scientific guidelines for the data catalog and for data storage, access, and distribution is also stressed.

Source record↗
NASA NTRS2003

TDRS-1 Going Strong at 20

This video presents an overview of the first Tracking and Data Relay Satellite (TDRS-1) in the form of text, computer animations, footage, and an interview with its program manager. Launched by the Space Shuttle Challenger in 1983, TDRS-1 was the first of a network of satellites used for relaying data to and from scientific spacecraft. Most of this short video is silent, and consists of footage and animation of the deployment of TDRS-1, written and animated explanations of what TDRS satellites do, and samples of the astronomical and Earth science data they transmit. The program manager explains in the final segment of the video the improvement TDRS satellites brought to communication with manned space missions, including alleviation of blackout during reentry, and also the role TDRS-1 played in providing telemedicine for a breast cancer patient in Antarctica.

Source record↗
NASA NTRS1999

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Larson, J. W.↗