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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

The GLAS Standard Data Products Specification--Level 2, Version 9

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document defines the Level-2 GLAS standard data products. This document addresses the data flow, interfaces, record and data formats associated with the GLAS Level 2 standard data products. The term standard data products refers to those EOS instrument data that are routinely generated for public distribution. The National Snow and Ice Data Center (NSDIC) distribute these products. Each data product has a unique Product Identification code assigned by the Senior Project Scientist. The Level 2 Standard Data Products specifically include those derived geophysical data values (i.e., ice sheet elevation, cloud height, vegetation height, etc.). Additionally, the appropriate correction elements used to transform the Level 1A and Level 1B Data Products into Level 2 Data Products are included. The data are packaged with time tags, precision orbit location coordinates, and data quality and usage flags.

Lee, Jeffrey E.↗
NASA NTRS2019

Leveraging STARE for Co-aligned Data Locality with netCDF and Python MPI

We have leveraged STARE indexing to package partitioned data chunks from diverse datasets into netCDF files, distributed them on a cluster of 16 lightweight nodes with their placements spatiotemporally co-aligned, and demonstrated a few integrative analyses using netCDF parallel I/O and Python MPI, with single-user performance and scalability comparable to, or even better than, that of a parallel array database management system (ADBMS) such as SciDB. However, records of the node location and STARE index ranges for each data chunk, similar to the chunk maps of SciDB, must be maintained and consulted by the I/O and analysis code for coordinating the analytic operations in parallel, in order to achieve the good performance and scalability.

Kwo-Sen Kuo↗
NASA NTRS1998

Versatile Software Package For Near Real-Time Analysis of Experimental Data

This paper provides an overview of a versatile software package developed for time- and frequency-domain analyses of experimental wind-tunnel data. This package, originally developed for analyzing data in the NASA Langley Transonic Dynamics Tunnel (TDT), is applicable for analyzing any time-domain data. A Matlab-based software package, TDT-analyzer, provides a compendium of commonly-required dynamic analysis functions in a user-friendly interactive and batch processing environment. TDT-analyzer has been used extensively to provide on-line near real-time and post-test examination and reduction of measured data acquired during wind tunnel tests of aeroelastically-scaled models of aircraft and rotorcraft as well as a flight test of the NASA High Alpha Research Vehicle (HARV) F-18. The package provides near real-time results in an informative and timely manner far exceeding prior methods of data reduction at the TDT.

Wieseman, Carol D.↗
NASA NTRS1991

SEAPAK user's guide, version 2.0. Volume 1: System description

The SEAPAK is a user interactive satellite data analysis package that was developed for the processing and interpretation of Nimbus-7/Coastal Zone Color Scanner (CZCS) and the NOAA Advanced Very High Resolution Radiometer (AVHRR) data. Significant revisions were made to version 1.0 of the guide, and the ancillary environmental data analysis module was expanded. The package continues to emphasize user friendliness and user interactive data analyses. Additionally, because the scientific goals of the ocean color research being conducted have shifted to large space and time scales, batch processing capabilities for both satellite and ancillary environmental data analyses were enhanced, thus allowing large quantities of data to be ingested and analyzed in background.

Mcclain, Charles R.↗
NASA NTRS1988

Astrophysics from large databases - The example of IUE

Ways to access the IUE data base and methods for processing and analyzing the IUE data are discussed. The characteristics of the data base are described and the types of objects observed by the IUE are listed. The methods for searching the IUE catalogs and conducting multicatalog searches are considered. In addition, trends in the application of astronomical data bases are examined, including the prospects for future software packages for data processing and analysis.

Heap, Sara R.↗
NASA NTRS2001

ATIC Flight Data Processing

The first flight of the Advanced Thin Ionization Calorimeter (ATIC) experiment from McMurdo, Antarctica lasted for 16 days, starting on December 28, 2000. The ATIC instrument consists of a fully active 320-crystal, 960-channel Bismuth Germanate (BGO) calorimeter, 202 scintillator strips (808 channels) in 3 hodoscopes, interleaved with graphite target layers, and a 4480-pixel silicon matrix charge detector. We have developed an object-oriented data processing package based on ROOT. In this paper, we describe the data processing scheme used in handling the accumulated 45 GB of flight data. We discuss calibration issues, particularly the time-dependence of housekeeping information.

Ahn, H. S.↗
NASA NTRSDate not supplied

Bridging the Last Mile with Open-Source Advancements: Empowering Communities through Fusion of Aerosol Optical Depth (AOD) Products from Multi-Satellite Sensors

Aerosol Optical Depth (AOD) is a crucial parameter for understanding atmospheric aerosol distribution and their impact on climate and air quality. With the growing number of Earth observation satellites, there is an abundance of AOD products derived from various sensors onboard both geostationary and low-orbit satellites. The availability of multiple datasets provides an opportunity to harness the strengths of each sensor and create comprehensive and accurate AOD datasets for climate and air quality studies at different temporal and spatial scales. Our NASA aerosol MEaSURES project has made significant strides in recent years by undertaking the ambitious task of developing an open-source package tailored for fusing AOD products from different sources. The package is based on OOP (Object-Oriented Programming) design and is implemented in Python modules. Generic interfaces enable easy inclusion of large and heterogeneous data. The package may be utilized to produce harmonized AOD datasets with enhanced spatial and temporal coverage. The latest version of the package is able to process and integrate the dark-target AOD data from six different sensors: AHI Himawari-8, ABI GOES-West, ABI GOES-East, MODIS AQUA, MODIS TERRA, and VIIRS SNPP. Rigorous validation and intercomparison studies have been performed to assess the accuracy and reliability of the fused AOD product against ground-based measurements and reference datasets. The open-source nature of the developed package ensures transparency, reproducibility, and community engagement. The research community and stakeholders can access, contribute to, and further improve the fusion methodology, making it adaptable to other studies, or expanding it to include new satellite data as they become available. In this poster presentation, we will introduce the accomplishments and challenges faced during the development of the open-source package for AOD data fusion, and demonstrate the advantages of combining AOD products from the six aforementioned satellite sensors. The presentation aims to foster discussions, collaborations, and future directions in integrating Earth observation and remote sensing data, which may contribute to a better understanding of atmospheric aerosols and their impacts on our environment.

Zhaohui Zhang↗
NASA NTRS1978

Skylab EREP Investigations Summary

The problems in the areas of agriculture, range and forestry; land use and cartography; geology and hydrology; oceans atmosphere, and data analysis techniques were investigated and summarized using Earth Resources Experiment Package (EREP) data.

Pierson, W. J.↗
NASA NTRS2001

ATIC Flight Data Processing

The first flight of the Advanced Thin Ionization Calorimeter (ATIC) experiment from McMurdo, Antarctica lasted for 16 days, starting in December, 2000. The ATIC instrument consists of a fully active 320-crystal, 960-channel Bismuth Germanate (BGO) calorimeter, 202 scintillator strips in 3 hodoscopes interleaved with a graphite target, and a 4480-pixel silicon matrix charge detector. We have developed an Object Oriented data processing package based on ROOT. In this paper, we will describe the data processing scheme used in handling the accumulated 45 GB of flight data. We will also discuss trigger issues by comparing the measured energy-dependent trigger efficiency with its simulation and calibration issues by considering the time-dependence of housekeeping information, etc.

Ahn, H. S.↗
NASA NTRS2014

Reliability of CGA/LGA/HDI Package Board/Assembly (Final Report)

Package manufacturers are now offering commercial-off-the-shelf column grid array (COTS CGA) packaging technologies in high-reliability versions. Understanding the process and quality assurance (QA) indicators for reliability are important for low-risk insertion of these advanced electronics packages. The previous reports, released in January of 2012 and January of 2013, presented package test data, assembly information, and reliability evaluation by thermal cycling for CGA packages with 1752, 1517, 1509, and 1272 inputs/outputs (I/Os) and 1-mm pitch. It presented the thermal cycling (-55C either 100C or 125C) test results for up to 200 cycles. This report presents up to 500 thermal cycles with quality assurance and failure analysis evaluation represented by optical photomicrographs, 2D real time X-ray images, dye-and-pry photomicrographs, and optical/scanning electron Microscopy (SEM) cross-sectional images. The report also presents assembly challenge using reflowing by either vapor phase or rework station of CGA and land grid array (LGA) versions of three high I/O packages both ceramic and plastic configuration. A new test vehicle was designed having high density interconnect (HDI) printed circuit board (PCB) with microvia-in-pad to accommodate both LGA packages as well as a large number of fine pitch ball grid arrays (BGAs). The LGAs either were assembled onto HDI PCB as an LGA or were solder paste print and reflow first to form solder dome on pads before assembly. Both plastic BGAs with 1156 I/O and ceramic LGAs were assembled. It also presented the X-ray inspection results as well as failures due to 200 thermal cycles. Lessons learned on assembly of ceramic LGAs are also presented.

Ghaffaroam. Reza↗
NASA NTRS1978

A geometry package for generation of input data for a three-dimensional potential-flow program

The preparation of geometric data for input to three-dimensional potential flow programs was automated and simplified by a geometry package incorporated into the NASA Langley version of the 3-D lifting potential flow program. Input to the computer program for the geometry package consists of a very sparse set of coordinate data, often with an order of magnitude of fewer points than required for the actual potential flow calculations. Isolated components, such as wings, fuselages, etc. are paneled automatically, using one of several possible element distribution algorithms. Curves of intersection between components are calculated, using a hybrid curve-fit/surface-fit approach. Intersecting components are repaneled so that adjacent elements on either side of the intersection curves line up in a satisfactory manner for the potential-flow calculations. Many cases may be run completely (from input, through the geometry package, and through the flow calculations) without interruption. Use of the package significantly reduces the time and expense involved in making three-dimensional potential flow calculations.

Halsey, N. D.↗
NASA NTRSDate not supplied

MLtool++ package for machine learning and its applications to materials data

We are developing Mltool++ package of software programs for machine learning (ML). Given the MLtool Python code, we create a faster C++ code with the potential for parallelization. We have extracted materials data from the literature. One dataset contains melting temperatures of stoichiometric 1:1 metallic compounds XZ, composed by elements X={Al, Ti, V, Cr, Zr, Nb, Mo, Hf, Ta, W} and Z={Co, Ni, Cu, Rh, Pd, Ag, Ir, Pt, Au}, and another contains solid-solid symmetry-breaking phase transition temperatures. We studied dependences of temperatures on composition, found several correlations, and parametrized them by analytical functions. Mltool++ package is generic and applicable to any tabulated numeric data.

Pierce M. Pettit↗
NASA NTRS1981

Recent developments with the ORSER system

Additions to the ORSER remote sensing data processing package are described. The ORSER package consists of about 35 individual programs that are grouped into preprocessing, data analysis, and display subsystems. Additional data formats and data management, data transformation, and geometric correlation programs were supplemented to the preprocessing subsystem. Enhancements to the data analysis techniques include a maximum likelihood classifier (MAXCLASS) and a new version of the STATS program which makes delineation of training areas easier and allows for detection of outlier points. Ongoing developments are also described.

Baumer, G. M.↗
NASA NTRS1992

Reformatting Data From X-Ray Photoelectron Spectroscopy

ASCITOVG program for IBM PC-series computers creates files in binary format from columns of numbers in American National Standard Code for Information Interchange (ASCII) format. Files suitable for DEC PDP-11/73 computer under Micro-RSX operating system running the VGS-5000 Enhanced Data Processing (EDP) software package which analyzes data with color graphics display, speeding up analysis compared with batch job processing. Written in FORTRAN.

Abel, P. B.↗
NASA NTRS1997

SimGraph: A Flight Simulation Data Visualization Workstation

Today's modern flight simulation research produces vast amounts of time sensitive data, making a qualitative analysis of the data difficult while it remains in a numerical representation. Therefore, a method of merging related data together and presenting it to the user in a more comprehensible format is necessary. Simulation Graphics (SimGraph) is an object-oriented data visualization software package that presents simulation data in animated graphical displays for easy interpretation. Data produced from a flight simulation is presented by SimGraph in several different formats, including: 3-Dimensional Views, Cockpit Control Views, Heads-Up Displays, Strip Charts, and Status Indicators. SimGraph can accommodate the addition of new graphical displays to allow the software to be customized to each user s particular environment. A new display can be developed and added to SimGraph without having to design a new application, allowing the graphics programmer to focus on the development of the graphical display. The SimGraph framework can be reused for a wide variety of visualization tasks. Although it was created for the flight simulation facilities at NASA Langley Research Center, SimGraph can be reconfigured to almost any data visualization environment. This paper describes the capabilities and operations of SimGraph.

Kaplan, Joseph A.↗
NASA NTRSDate not supplied

Providing Long-term Solar and Meteorological Resource Information from NASA Research through the GIS-Enabled POWER Web Services Portal

Solar and other renewable energy systems are optimized using geophysical parameters describing information about the solar resource and meteorological environments and how those environments may be changing in time. The Prediction of Worldwide Renewable Energy Resource (POWER) team at the NASA LaRC Research Center deployed its first version of the revitalized POWER geophysical parameter website that employs Esri Geographic Information System (GIS) tools. This web application provides access to both time series and climatological data sets spanning from a few days behind real-time back to the early 1980’s with a spatial resolution of 0.5 x 0.5 degree, thus extending over 30 years. The GIS tools enable, generate and store climatological averages using spatial queries and calculations in a spatial database resulting in greater accessibility to government agencies, industry and individuals. There is an API that provides data through a URL coding and can also invoked inside user software packages. Output data formats now include ASCII, CSV, geoTiff, JSON and .netCDF. Since May 2018, over 10.4 TB of data have been delivered to fulfill over 110 million data requests from 240,000 unique user IPs (https://power.larc.nasa.gov). This presentation provides an overview of this project and the current version of the new POWER web capabilities through to the end usage. Surface solar parameters are adapted from both the NASA/GEWEX (Global and Energy Water Cycle Exchange) SRB (Surface Radiation Budget) project and the CERES (Clouds and Earth’s Radiant Energy System) data products. The meteorological parameters are adapted from NASA’s MERRA-2 (Modern Era Retrospective-analysis for Research and Applications). We review uncertainty of various basic parameters using surface measurements. After the introduction, we specifically discuss various clusters of parameters for equator pointing tilted surfaces that provide for the estimation of optimal tilt angle by month and year. The discussion will emphasize a few examples of how solar and building engineers are using the data products. We will then preview the capabilities of Version 2 featuring examples of hourly solar and meteorological data products, customized user reports and expanded web mapping services from CERES data products. The web services provide a unique, expandable resource for renewable energy systems engineers to design, evaluate and optimize to environments worldwide.

Solar Resource↗
NASA NTRS1991

SEAPAK user's guide, version 2.0. Volume 2: Descriptions of programs

The SEAPAK is a user-interactive satellite data analysis package that was developed for the processing and interpretation of Nimbus-7/Coastal Zone Color Scanner (CZCS) and the NOAA Advanced Very High Resolution Radiometer (AVHRR) data. Significant revisions were made since version 1.0, and the ancillary environmental data analysis module was greatly expanded. The package continues to be user friendly and user interactive. Also, because the scientific goals of the ocean color research being conducted have shifted to large space and time scales, batch processing capabilities for both satellite and ancillary environmental data analyses were enhanced, thus allowing for large quantities of data to be ingested and analyzed.

Mcclain, Charles R.↗
NASA NTRS2020

Micron MT29F1T08CMHBBJ4 1Tb NAND Flash Memory Single Event Effect Characterization Test Report

The purpose of this testing is to characterize the Single-Event Effect (SEE) response of the Micron MT29F1T08CMHBBJ4 3D NAND Flash memory. The MT29F1T08CMHBBJ4 is a 1Tb NAND Flash memory, consisting of a four-die stack of 256Gb MLC dice packaged in a 132-ball VBGA package. All data presented is the result of testing only the top die (256Gb) of the package. Testing was performed at two heavy-ion cyclotron facilities with an identical test setup, over the course of four test trips from 2017-2019.

Single Event Effect (SEE)↗