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At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

The Magsat mission

The cesium-vapor scalar and fluxgate vector magnetometers aboard the Magsat spacecraft, which has a twilight, sun-synchronous orbit with a 96.76-deg inclination, have together measured the earth's magnetic field magnitude to accuracies better than 2 nT, and the magnitude of each field component to better than 6 nT. The magnetometers are located at the end of a boom to isolate them from the effects of spacecraft fields, and an optical system was used to measure the attitude of the vector magnetometer and sun sensor at the boom relative to the two star cameras of the main spacecraft structure. The data gathered is available from the National Space Science Data Center in several formats and is currently undergoing analysis. Scalar and vector error budget values are given for the spacecraft's five error sources, which include the instrument, position and time errors, digitization noise, attitude errors, and spacecraft fields.

Langel, R.↗
NASA NTRS1982

Data and data retrieval in space astronomy

To illustrate the range of storage and retrieval facilities and data products that are involved in space astronomy, the present situation on data from some instruments on the following missions is presented: Small Astronomy Satellite-B, Orbiting Astronomical Observatory 3, High Energy Astrophysics Observatory 2, International Ultraviolet Explorer, Viking Orbiter, and Solar Maximum Mission. In addition, the Coordinated Data Analysis Workshops conducted at the National Space Science Data Center are outlined to demonstrate the usefulness of building a problem-oriented on-line data base from instruments flown on a number of spacecraft and operating from ground-based facilities.

Vette, J. I.↗
NASA NTRS1984

In Situ Data

In-situ planetary data include all measurements made by a wide variety of instruments whose sensors are exposed directly to the planetry environment. Typical measurements include those of magnetic fields, energetic particle densities and energy distributions, plasma wave characteristics, ionospheric and neutral gas densities, temperatures, composition and motions. A large body of scientists in the United States, and the world, are involved in research using in-situ data. Many of these scientists are associated with Mission investigations groups which provide specific types of in-situ data. These groups, in the course of data analysis, use data provided by similar groups. The interdisciplinary nature of these investigations fosters exchange and reliance upon one another for data is heavy. To a lesser extent, correlative data sets are obtained from the National Space Science Data Center (NSSDC). However, the data entries often have limited temporal and spatial resolution, are of uncertain quality, and are usually available only for measurements that are several years old.

Source record↗
NASA NTRS1986

Catching the whispers from Uranus

Sophisticated telecommunications techniques are described that were used to acquire images of Uranus, its 14 moons and ten narrow rings darker than coal. The images, equal in quality to those transmitted from Saturn several years earlier despite the signal being weaker by 6 dB due to the increased distance, were received from Voyager 2 during its January 24, 1986 flyby of Uranus. Solutions to the problem of the weakening signal were found in modifications to Voyager's image processing system and NASA's ground tracking network. In April 1985, Voyager's prime flight data computer was reconfigured to accept only nonimaging science data, and its backup, only imaging data; the latter was reprogrammed to determine only arithmetic differences between adjacent pixel intensities rather than absolute intensities. By image compression, equivalent imaging information could be sent at lower bit rates. Instead of Golay coding, Reed-Solomon onboard encoding was used. These techniques gained the equivalent of 4-dB in imaging yield. Additional improvements were gained by using earth station antennas in pairs (the Parkes radio telescope and the Canberra ground station antenna). Moves under way to prepare for the Voyager encounter with Neptune in 1989 are described (using additional antennas and arrays, scaling up the Deep Space Network antennas from 64 m to 70 m, etc.) to assure almost Saturn-equivalent pictures despite a further 3.5-dB drop in signal strength.

Bartok, C. D.↗
NASA NTRS1989

Integrating NASA's Land Analysis System (LAS) image processing software with an appropriate Geographic Information System (GIS): A review of candidates in the public domain

A user requirements analysis (URA) was undertaken to determine and appropriate public domain Geographic Information System (GIS) software package for potential integration with NASA's LAS (Land Analysis System) 5.0 image processing system. The necessity for a public domain system was underscored due to the perceived need for source code access and flexibility in tailoring the GIS system to the needs of a heterogenous group of end-users, and to specific constraints imposed by LAS and its user interface, Transportable Applications Executive (TAE). Subsequently, a review was conducted of a variety of public domain GIS candidates, including GRASS 3.0, MOSS, IEMIS, and two university-based packages, IDRISI and KBGIS. The review method was a modified version of the GIS evaluation process, development by the Federal Interagency Coordinating Committee on Digital Cartography. One IEMIS-derivative product, the ALBE (AirLand Battlefield Environment) GIS, emerged as the most promising candidate for integration with LAS. IEMIS (Integrated Emergency Management Information System) was developed by the Federal Emergency Management Agency (FEMA). ALBE GIS is currently under development at the Pacific Northwest Laboratory under contract with the U.S. Army Corps of Engineers' Engineering Topographic Laboratory (ETL). Accordingly, recommendations are offered with respect to a potential LAS/ALBE GIS linkage and with respect to further system enhancements, including coordination with the development of the Spatial Analysis and Modeling System (SAMS) GIS in Goddard's IDM (Intelligent Data Management) developments in Goddard's National Space Science Data Center.

Rochon, Gilbert L.↗
NASA NTRS1994

Dynamics Explorer 1, retarding ion mass spectrometer summary spectrograms: 81/280 to 81/365 spin-time spectrograms for H(+), He(+), O(+), N(+), O(++), M/Z=2, and molecular ions

The Retarding Ion Mass Spectrometer (RIMS) experiment onboard the Dynamics Explorer 1 (DE 1) satellite was designed to perform energy and mass-per-charge analysis on low-energy ions (less than 50 eV) with mass/charge ratios ranging from 1 to 40 amu/Z. The DE 1 satellite, carrying the RIMS experiment, was launched into an elliptical polar orbit on August 3, 1981. The approximately 7.5 hour orbit has perigee of 675 km altitude and apogee of 24,875 km altitude. This document, as well as those that follow in this series, contains summary RIMS data spectrograms for each orbit for which RIMS data are available. The RIMS instrument began returning science data on day 280 of 1981 and continued to return usable data until the end of the DE mission in March 1991. It should be noted that studies of the RIMS data set should be conducted only with a thorough awareness of the material described in the introduction section presented here, or in collaboration with a scientist familiar with RIMS data analysis.

Source record↗
NASA NTRS1994

Dynamics Explorer 1, retarding ion mass spectrometer summary spectrograms: 82/001 to 82/109 spin-time spectrograms for H(+), He(+), O(+), N(+), O(++), M/Z=2, and molecular ions

The Retarding Ion Mass Spectrometer (RIMS) experiment onboard the Dynamics Explorer 1 (DE 1) satellite was designed to perform energy and mass-per-change analysis on low-energy ions (less than 50 eV) with mass/charge ratios ranging from 1 to 40 amu/Z. The DE 1 satellite, carrying the RIMS experiment, was launched into an elliptical polar orbit on August 3, 1981. The approximate 7.5 hour orbit has perigee of 675 km altitude and apogee of 24,875 km altitude. This document, and those that follow in this series, contains summary RIMS data spectrograms for each orbit for which RIMS data are available. The RIMS instrument began returning science data on day 280 of 1981 and continued to return usable data until the end of the DE mission in March 1991. It should be noted that studies of the RIMS data set should be conducted only with a thorough awareness of the material described in the introduction section presented here, or in collaboration with a scientist familiar with RIMS data analysis.

Source record↗
NASA NTRS1995

Dynamics Explorer 1, retarding ion mass spectrometer summary spectrograms-82/110 to 82/229 spin-time spectrograms for H(+), He(+), O(+), N(+), O(++), M/Z = 2, and molecular ions

The retarding ion mass spectrometer (RIMS) experiment onboard the Dynamics Explorer 1 (DE 1) satellite was designed to perform energy and mass-per-charge analysis on low-energy ions (less than 50 eV) with mass/charge ratios ranging from 1 to 40 amu/Z. The DE 1 satellite, carrying the RIMS experiment, was launched into an elliptical polar orbit on August 3, 1981. The approximately 7.5 hour orbit has perigee of 675 km altitude and apogee of 24,875 km altitude. this document and those that following in this series, contains summary RIMS data spectrograms for each orbit for which RIMS data are available. The RIMS instrument began returning science data on day 280 of 1981 and continued to return usable data until the end of the DE mission in March 1991. It should be noted that studies of the RIMS data set should be conducted only with a thorough awareness of the material described in the introduction section presented here, or in collaboration with a scientist familiar with RIMS data analysis.

Source record↗
NASA NTRS1995

Dynamics Explorer 1, retarding ion mass spectrometer summary spectrograms-82/230 to 82/265 spin-time spectrograms for H(+), He(+), O(+), N(+), O(++), M/Z = 2, and molecular ions

The retarding ion mass spectrometer (RIMS) experiment onboard the Dynamics Explorer 1 (DE 1) satellite was designed to perform energy and mass-per-charge analysis on low-energy ions (less than 50 eV) with mass/charge ratios ranging from 1 to 40 amu/Z. the DE 1 satellite, carrying the RIMS experiment, was launched into an elliptical polar orbit on August 3, 1981. The approximately 7.5 hour orbit has perigee of 675 km altitude and apogee of 24,875 km altitude. This document and those that follow in this series, contain summary RIMS data spectrograms for each orbit for which RIMS data are available. The RIMS instrument began returning science data on day 280 of 1981 and continued to return usable data until the end of the DE mission in March 1991. It should be noted that studies of the RIMS data set should be conducted only with a thorough awareness of the material described in the introduction section presented here, or in collaboration with a scientist familiar with RIMS data analysis.

Source record↗
NASA NTRS2005

Comparison of TRMM Ground Validation and Satellite Rain Intensity Estimates

The Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) Program began in the late 1980's and has provided a wealth of data and resources for validating TRMM satellite estimates. The TRMM GV program's main operational task is to provide rainfall products for four sites: Darwin, Australia (DARW); Houston, Texas (HSTN); Kwajalein, Republic of the Marshall Islands (KWAJ); and, Melbourne, Florida (MELB). A comparison between TRMM Ground Validation (Version 5) and Satellite (Version 6) rain intensity estimates is presented. The full suite of Version 6 satellite data is currently being generated by the TRMM Science Data and Information System (TSDIS) and should be completed some time near the end of 2005. The gridded satellite product (3G68) will be compared to GV Level II rain-intensity and -type maps (2A53 and 2A54, respectively). The 3G68 product represents a 0.5 deg x 0.5 deg data grid providing estimates of rain intensities from the TRMM Precipitation Radar (PR), Microwave Imager (TMI) and Combined (COM) algorithms. The comparisons will be sub-setted according to geographical type (land, coast and ocean). A bias statistic will be presented that provides quantification of the relative differences between the various estimators. Previous comparisons of an interim satellite product (Version 6a) showed that all of the estimates (GV and satellite) are converging, with some expected discrepancies. The convergence of the GV and satellite estimates bodes well for expectations for the proposed Global Precipitation Measurement (GPM) program and this study and others are being leveraged towards planning GV goals for GPM.

Wolff, David B.↗
NASA NTRS2005

Data Format Standardization of Space Weather Model Output at the Community Coordinated Modeling Center

The disparate nature of space weather model output provides many challenges with regards to the portability and reuse of not only the data itself, but also any tools that are developed for analysis and visualization. We are developing and implementing a comprehensive data format standardization methodology that allows heterogeneous model output data to be stored uniformly in any common science data format. We will discuss our approach to identifying core meta-data elements that can be used to supplement raw model output data, thus creating self-descriptive files. The meta-data should also contain information describing the simulation grid. This will ultimately assists in the development of efficient data access tools capable of extracting data at any given point and time. We will also discuss our experiences standardizing the output of two global magnetospheric models, and how we plan to apply similar procedures when standardizing the output of the solar, heliospheric, and ionospheric models that are also currently hosted at the Community Coordinated Modeling Center.

Maddox, M.↗
NASA NTRS2003

The HYDROS Mission: Requirements and Baseline System Design

The HYDROS mission is under development by NASA as part of its Earth System Science Pathfinder (ESSP) program. HYDROS is designed to provide global maps of the Earth's soil moisture and freezel/thaw state every 2-3 days, for weather and climate prediction, water and carbon cycle studies, natural hazards monitoring, and national security applications. HYDROS uses a unique active and passive L-band microwave system that optimizes measurement accuracy, spatial resolution, and coverage. It provides measurements in nearly all weather conditions, regardless of solar illumination. The designs of the radar and radiometer electronics, antenna feedhorn and reflector, and science data system, are driven by specific mission and science objectives. These objectives impose requirements on the frequencies, polarizations, sampling, spatial resolution, and accuracy of the system. In this paper we describe the HYDROS mission requirements, baseline design, and measurement capabilities.

soil moisture↗
NASA NTRS2013

Cloud Absorption Radiometer Autonomous Navigation System - CANS

CAR (cloud absorption radiometer) acquires spatial reference data from host aircraft navigation systems. This poses various problems during CAR data reduction, including navigation data format, accuracy of position data, accuracy of airframe inertial data, and navigation data rate. Incorporating its own navigation system, which included GPS (Global Positioning System), roll axis inertia and rates, and three axis acceleration, CANS expedites data reduction and increases the accuracy of the CAR end data product. CANS provides a self-contained navigation system for the CAR, using inertial reference and GPS positional information. The intent of the software application was to correct the sensor with respect to aircraft roll in real time based upon inputs from a precision navigation sensor. In addition, the navigation information (including GPS position), attitude data, and sensor position details are all streamed to a remote system for recording and later analysis. CANS comprises a commercially available inertial navigation system with integral GPS capability (Attitude Heading Reference System AHRS) integrated into the CAR support structure and data system. The unit is attached to the bottom of the tripod support structure. The related GPS antenna is located on the P-3 radome immediately above the CAR. The AHRS unit provides a RS-232 data stream containing global position and inertial attitude and velocity data to the CAR, which is recorded concurrently with the CAR data. This independence from aircraft navigation input provides for position and inertial state data that accounts for very small changes in aircraft attitude and position, sensed at the CAR location as opposed to aircraft state sensors typically installed close to the aircraft center of gravity. More accurate positional data enables quicker CAR data reduction with better resolution. The CANS software operates in two modes: initialization/calibration and operational. In the initialization/calibration mode, the software aligns the precision navigation sensors and initializes the communications interfaces with the sensor and the remote computing system. It also monitors the navigation data state for quality and ensures that the system maintains the required fidelity for attitude and positional information. In the operational mode, the software runs at 12.5 Hz and gathers the required navigation/attitude data, computes the required sensor correction values, and then commands the sensor to the required roll correction. In this manner, the sensor will stay very near to vertical at all times, greatly improving the resulting collected data and imagery. CANS greatly improves quality of resulting imagery and data collected. In addition, the software component of the system outputs a concisely formatted, high-speed data stream that can be used for further science data processing. This precision, time-stamped data also can benefit other instruments on the same aircraft platform by providing extra information from the mission flight.

Kahle, Duncan↗
NASA NTRS2013

The Version 8.6 SBUV Ozone Data Record: An Overview

Under a NASA program to produce long-term data records from instruments on multiple satellites, data from a series of nine Solar Backscatter Ultraviolet (SBUV and SBUV2) instruments have been re-processed to create a coherent ozone time series. Data from the BUV instrument on Nimbus 4, SBUV on Nimbus 7, and SBUV2 instruments on NOAA 9, 11, 14, 16, 17, 18, and 19 covering the period 1970-1972 and 1979-2011 were used to create a long-term data set. The goal is an ozone Earth Science Data Record - a consistent, calibrated ozone time series that can be used for trend analyses and other studies. In order to create this ozone data set, the radiances were adjusted and used to re-process the entire data records for each of the nine instruments. Inter-instrument comparisons during periods of overlap as well as comparisons with data from other satellite and ground-based instruments were used to evaluate the consistency of the record and make calibration adjustments as needed. Additional improvements in this version 8.6 processing included the use of the Brion, Daumont, and Malicet ozone cross sections, and a cloud-height climatology derived from Aura OMI measurements. Validation of the re-processed ozone shows that total column ozone is consistent with the Brewer Dobson network to within about 1 for the new time series. Comparisons with MLS, SAGE, sondes, and lidar show that ozone at individual levels in the stratosphere is generally consistent to within 5 percent.

ozone↗
NASA NTRS2011

UAVSAR Instrument: Current Operations and Planned Upgrades

The Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument is a pod-based Lband polarimetric synthetic aperture radar (SAR), specifically designed to acquire airborne repeat track SAR data for differential interferometric measurements. This instrument is currently installed on the NASA Gulfstream- III (G-III) aircraft with precision real-time Global Positioning System (GPS) and a sensor-controlled flight management system for precision repeat-pass data acquisitions. UAVSAR has conducted engineering and preliminary science data flights since October 2007 on the G-III. We are porting the radar to the Global Hawk Unmanned Airborne Vehicle (UAV) to enable long duration/long range data campaigns. We plan to install two radar pods (each with its own active array antenna) under the wings of the Global Hawk to enable the generation of precision topographic maps and single pass polarimetric-interferometry (SPI) providing vertical structure of ice and vegetation. Global Hawk's range of ~ 8000 nm will enable regional surveys with far fewer sorties as well as measurements of remote locations without the need for long and complicated deployments. We are also developing P-band polarimetry and Ka-band single-pass interferometry capabilities on UAVSAR by replacing the radar antenna and front-end electronics to operate at these

Uninhabited Airborne Vehicle Synthetic Aperture Ra↗
NASA NTRS2016

Restoration of Apollo Data by the Lunar Data Project/PDS Lunar Data Node: An Update

The Apollo 11, 12, and 14 through 17 missions orbited and landed on the Moon, carrying scientific instruments that returned data from all phases of the missions, included long-lived Apollo Lunar Surface Experiments Packages (ALSEPs) deployed by the astronauts on the lunar surface. Much of these data were never archived, and some of the archived data were on media and in formats that are outmoded, or were deposited with little or no useful documentation to aid outside users. This is particularly true of the ALSEP data returned autonomously for many years after the Apollo missions ended. The purpose of the Lunar Data Project and the Planetary Data System (PDS) Lunar Data Node is to take data collections already archived at the NASA Space Science Data Coordinated Archive (NSSDCA) and prepare them for archiving through PDS, and to locate lunar data that were never archived, bring them into NSSDCA, and then archive them through PDS. Preparing these data for archiving involves reading the data from the original media, be it magnetic tape, microfilm, microfiche, or hard-copy document, converting the outmoded, often binary, formats when necessary, putting them into a standard digital form accepted by PDS, collecting the necessary ancillary data and documentation (metadata) to ensure that the data are usable and well-described, summarizing the metadata in documentation to be included in the data set, adding other information such as references, mission and instrument descriptions, contact information, and related documentation, and packaging the results in a PDS-compliant data set. The data set is then validated and reviewed by a group of external scientists as part of the PDS final archive process. We present a status report on some of the data sets that we are processing.

Lunar↗
NASA NTRS2017

Earthdata Login

An overview of NASA's Earth data Login system, how it integrates with Earth Science data distribution systems, and what it can do to help improve our understanding of user needs.

user metrics↗
NASA NTRS2017

Lessons Learned from Preparing OSIRIS-REx Spectral Analog Samples for Bennu

NASA's OSIRIS-REx sample return mission launched on September 8th, 2016 to rendezvous with B-type asteroid (101955) Bennu in 2018. Type C and B asteroids have been linked to carbonaceous chondrites because of their similar visible - to - near infrared (VIS-NIR) spectral properties [e.g., 1,2]. The OSIRIS-REx Visible and Infrared Spectrometer (OVIRS) and the Thermal Emission Spectrometer (OTES) will make spectroscopic observations of Bennu during the encounter. Constraining the presence or absence of hydrous minerals (e.g., Ca-carbonate, phyllosilicates) and organic molecules will be key to characterizing Bennu [3] prior to sample site selection. The goal of this study was to develop a suite of analog and meteorite samples and obtain their spectral properties over the wavelength ranges of OVIRS (0.4- 4.3 micrometer) and OTES (5.0-50 micrometer). These spectral data were used to validate the mission science-data processing system. We discuss the reasoning behind the study and share lessons learned.

Schrader, D. L.↗