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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

EOS MLS Science Data Processing System: A Description of Architecture and Capabilities

This paper describes the architecture and capabilities of the Science Data Processing System (SDPS) for the EOS MLS. The SDPS consists of two major components--the Science Computing Facility and the Science Investigator-led Processing System. The Science Computing Facility provides the facilities for the EOS MLS Science Team to perform the functions of scientific algorithm development, processing software development, quality control of data products, and scientific analyses. The Science Investigator-led Processing System processes and reprocesses the science data for the entire mission and delivers the data products to the Science Computing Facility and to the Goddard Space Flight Center Earth Science Distributed Active Archive Center, which archives and distributes the standard science products.

Microwave Limb Sounder (MLS)↗
NASA NTRS2006

Control of Technology Transfer at JPL

Controlled Technology: 1) Design: preliminary or critical design data, schematics, technical flow charts, SNV code/diagnostics, logic flow diagrams, wirelist, ICDs, detailed specifications or requirements. 2) Development: constraints, computations, configurations, technical analyses, acceptance criteria, anomaly resolution, detailed test plans, detailed technical proposals. 3) Production: process or how-to: assemble, operated, repair, maintain, modify. 4) Manufacturing: technical instructions, specific parts, specific materials, specific qualities, specific processes, specific flow. 5) Operations: how-to operate, contingency or standard operating plans, Ops handbooks. 6) Repair: repair instructions, troubleshooting schemes, detailed schematics. 7) Test: specific procedures, data, analysis, detailed test plan and retest plans, detailed anomaly resolutions, detailed failure causes and corrective actions, troubleshooting, trended test data, flight readiness data. 8) Maintenance: maintenance schedules and plans, methods for regular upkeep, overhaul instructions. 9) Modification: modification instructions, upgrades kit parts, including software

Jet Propulsion Laboratory (JPL)↗
NASA NTRS2001

ICESat (GLAS) Science Processing Software Document Series: GLAS Science Software Requirements Document - Volume 3

This document addresses the software requirements of the Geoscience Laser Altimeter System (GLAS) Standard Data Software (SDS) supporting the GLAS instrument on the EOS ICESat Spacecraft. This Software Requirements Document represents the initial collection of the technical engineering information for the GLAS SDS. This information is detailed within the second of four main volumes of the Standard documentation, the Product Specification volume. This document is a "roll-out" from the governing volume outline containing the Concept and Requirements sections.

Jester, Peggy L.↗
NASA NTRS2000

BOREAS HYD-4 Standard Snow Course Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-4 work was focused on collecting data during the winter focused field campaign (FFC-W) to improve the understanding of winter processes within the boreal forest. Knowledge of snow cover and its variability in the boreal forest is fundamental if BOREAS is to achieve its goals of understanding the processes and states involved in the exchange of energy and water. The development and validation of remote sensing algorithms will provide the means to extend the knowledge of these processes and states from the local to the regional scale. A specific thrust of the research is the development and validation of snow cover algorithms from airborne passive microwave measurements. Snow surveys were conducted at special snow courses throughout the 1993/94, 1994/95, 1995/96, and 1996/97 winter seasons. These snow courses were located in different boreal forest land cover types (i.e., old aspen, old black spruce, young jack pine, forest clearing, etc.) to document snow cover variations throughout the season as a function of different land cover. Measurements of snow depth, density, and water equivalent were acquired on or near the first and fifteenth of each month during the snow cover season. The data are provided in tabular ASCII files. The HYD-4 standard snow course data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Metcalfe, John R.↗
NASA NTRSDate not supplied

MISR Level 1B1 Radiance Data (MI1B1_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 meters - < 500 meters; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly, about 15 orbits/day, Daily - < Weekly].

EOSDIS↗
NASA NTRSDate not supplied

MISR Level 1B1 Radiance Data (MI1B1_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

AM-1↗
NASA NTRS1985

A report on the ST ScI optical disk workstation

The STScI optical disk project was designed to explore the options, opportunities and problems presented by the optical disk technology, and to see if optical disks are a viable, and inexpensive, means of storing the large amount of data which are found in astronomical digital imagery. A separate workstation was purchased on which the development can be done and serves as an astronomical image processing computer, incorporating the optical disks into the solution of standard image processing tasks. It is indicated that small workstations can be powerful tools for image processing, and that astronomical image processing may be more conveniently and cost-effectively performed on microcomputers than on the mainframe and super-minicomputers. The optical disks provide unique capabilities in data storage.

Source record↗
NASA NTRS1983

Effects of vegetation canopy on the radar backscattering coefficient

Airborne L- and C-band scatterometer data, taken over both vegetation-covered and bare fields, were systematically analyzed and theoretically reproduced, using a recently developed model for calculating radar backscattering coefficients of rough soil surfaces. The results show that the model can reproduce the observed angular variations of radar backscattering coefficient quite well via a least-squares fit method. Best fits to the data provide estimates of the statistical properties of the surface roughness, which is characterized by two parameters: the standard deviation of surface height, and the surface correlation length. In addition, the processes of vegetation attenuation and volume scattering require two canopy parameters, the canopy optical thickness and a volume scattering factor. Canopy parameter values for individual vegetation types, including alfalfa, milo and corn, were also determined from the best-fit results. The uncertainties in the scatterometer data were also explored.

Mo, T.↗
NASA NTRS2011

Wavelet Filter Banks for Super-Resolution SAR Imaging

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Sheybani, Ehsan O.↗
NASA NTRS1994

EDOS operations concept and development approach

The Earth Observing System (EOS) Data and Operations System (EDOS) is being developed by the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) for the capture, level zero processing, distribution, and backup archiving of high speed telemetry data received from EOS spacecraft. All data received will conform to the Consultative Committee for Space Data Standards (CCSDS) recommendations. The major EDOS goals are to: (1) minimize EOS program costs to implement and operate EDOS; (2) respond effectively to EOS growth requirements; and (3) maintain compatibility with existing and enhanced versions of NASA institutional systems required to support EOS spacecraft. In order to meet these goals, the following objectives have been defined for EDOS: (1) standardize EDOS interfaces to maximize utility for future requirements; (2) emphasize life-cycle cost (LCC) considerations (rather than procurement costs) in making design decisions and meeting reliability, maintainability, availability (RMA) and upgradability requirements; (3) implement data-driven operations to the maximum extent possible to minimize staffing requirements and to maximize system responsiveness; (4) provide a system capable of simultaneously supporting multiple spacecraft, each in different phases of their life-cycles; (5) provide for technology insertion features to accommodate growth and future LCC reductions during the operations phase; and (6) provide a system that is sufficiently robust to accommodate incremental performance upgrades while supporting operations. Operations concept working group meetings were facilitated to help develop the EDOS operations concept. This provided a cohesive concept that met with approval of responsible personnel from the start. This approach not only speeded up the development process by reducing review cycles, it also provided a medium for generating good ideas that were immediately molded into feasible concepts. The operations concept was then used as a basis for the EDOS specification. When it was felt that concept elements did not support detailed requirements, the facilitator process was used to resolve discrepancies or to add new concept elements to support the specification. This method provided an ongoing revisal of the operations concept and prevented large revisions at the end of the requirement analysis phase of system development.

Knoble, G.↗
NASA NTRS2018

Improving AIRS NRT Imagery for the Enhancement of Visualization Services in LANCE

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of processing, archiving, and distribution services for data from the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002. AIRS provides data enabling global observations of the atmospheric state. The GES DISC provides service to both AIRS standard products and Near Real-time (NRT) products. The AIRS NRT product is one important element in the Land, Atmosphere Near real-time Capability for EOS (LANCE). The LANCE processing of the AIRS NRT product and the generation of the imagery are performed at the GES DISC. The AIRS NRT imagery are generated by mosaicking and mapping the available AIRS 6-minute retrieval granules to a global cylindrical projection. The images are constantly refreshed when new granules are produced. The AIRS NRT Viewer and LANCE Worldview provide visualization services to online users for AIRS NRT imagery. The imagery include atmospheric temperature, humidity, precipitation, Dust Score, CO, and SO2. The AIRS Applications Development Team at NASA JPL developed a new orbit-based algorithm and software to improve the AIRS NRT imagery. The GES DISC is collaborating with the AIRS Applications Development Team for the implementation of the new algorithm and software. The improvements include image quality, new color palettes, and variable changes. In this presentation, we will detail the improvements and demonstrate visualization of the new imagery.

Ding, Feng↗
NASA NTRS1983

GSFC optical ozonesonde results during the Gap, France, intercomparisons, June 1981

O3 soundings made with balloon-borne optical sensors during the French Intercomparison Ozone Campaign in June, 1981, are reported. The GSFC four-channel UV-filter-photometer ozonesonde designed for the Super Loki rocket was attached to the gondola roof for redundant O3-density measurements at altitudes of 22-32 km, using the 300 and 303-nm filters. Sensor calibration, data processing, input constants, and vertical O3-distribution calculations are discussed. The density profiles for three legs of the flight, calculated using Bass or Vigroux cross sections, agreed within a standard error of 1.4 percent for each channel, but showed a consistent 4-5 percent (significant) difference between channels. Total average O3-column amounts determined by combining the GSFC data with ECC measurements for altitudes below 21 km were in good agreement with bias-corrected TOMS data from Nimbus-VII and with ground-based data from the Observatoire de Haute-Provence at Mt. Chiran, when the latter were computed using the pre-campaign calibration. A 9-percent discrepancy arose when the Chiran data were corrected for a post-campaign recalibration of the Dobson spectrophotometer.

Krueger, A. J.↗
NASA NTRS2002

Internet Data Delivery for Future Space Missions

This paper presents work being done at NASA/GSFC (Goddard Space Flight Center) on applying standard Internet applications and protocols to meet the technology challenge of future satellite missions. Internet protocols (IP) can provide seamless dynamic communication among heterogeneous instruments, spacecraft, ground stations, and constellations of spacecraft. A primary component of this work is to design and demonstrate automated end-to-end transport of files in a dynamic space environment using off-the-shelf, low-cost, commodity-level standard applications and protocols. These functions and capabilities will become increasingly significant in the years to come as both Earth and space science missions fly more sensors and the present labor-intensive, mission-specific techniques for processing and routing data become prohibitively expensive. This paper describes how an IP-based communication architecture can support existing operations concepts and how it will enable some new and complex communication and science concepts. The authors identify specific end-to-end file transfers all the way from instruments to control centers and scientists, and then describe how each data flow can be supported using standard Internet protocols and applications. The scenarios include normal data downlink and command uplink as well as recovery scenarios for both onboard and ground failures. The scenarios are based on an Earth orbiting spacecraft with data rates and downlink capabilities from 300 Kbps to 4 Mbps. Many examples are based on designs currently being investigated for the Global Precipitation Measurement (GPM) mission.

Rash, James↗
NASA NTRS1975

Landsat non-US standard catalog

The Non-U.S. Standard Catalog lists Non-U.S. imagery acquired by Landsat 1 and 2 which was processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found are also given.

Source record↗
NASA NTRS1976

Programmable data collection platform study

The results of a feasibility study incorporating microprocessors in data collection platforms in described. An introduction to microcomputer hardware and software concepts is provided. The influence of microprocessor technology on the design of programmable data collection platform hardware is discussed. A standard modular PDCP design capable of meeting the design goals is proposed, and the process of developing PDCP programs is examined. A description of design and construction of the UT PDCP development system is given.

Source record↗
NASA NTRS1980

Statistical Analysis of daily mean temperatures

Data of daily mean temperatures recorded at the Kennedy Center during the period of 1957-1977 were analyzed to forecast daily mean temperatures and their thirty-day moving averages for a period of ten to fifteen days in a given month. Since it is found that the standard deviation is linear in the mean, a logarithmic transformation of the data is used for finding an integrated moving average process IMA by the Box-Jenkins aproach. The first differences of the transformed data seem to fit a moving average model with parameter value 2, MA(2). The consideration of seasonality factor makes the fit worse.

Ross, D. C.↗
NASA NTRS1984

Data user's manual

The standard SIR-B data products will consist of both optical and digital output. The format of the unprocessed echo data, optically processed image data, and digital image data is described.

Source record↗
NASA NTRS1987

Preliminary simultaneous L/C-band images from the JPL aircraft synthetic aperture radar

A squint mode processor for the processing of JPL aircraft SAR data collected in L-band and C-band is described which meets the criteria of optimum SNR, polarization isolation, and resolution. A steerable prefilter maximizes SNR while reducing the amount of data for processing efficiency. The resolution of images produced from data recorded at nonzero drift angle is improved by range migration compensation. The standard output products include high resolution images (with a range resolution of 7.5 m and an azimuth resolution of 2.74 m), four-look images (produced by averaging every four pixels in the azimuth direction for speckle reduction), and magnitude/phase-difference images (produced by correlating images of similar polarizations).

Lou, Yunling↗