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At least 469 records · Page 26

An optimal GPS data processing technique for precise positioning

A mathematical formula to optimally combine dual-frequency GPS pseudorange and carrier phase (integrated Doppler) data streams into a single data stream is derived in closed form. The data combination reduces the data volume and computing time in the filtering process for parameter estimation by a factor of 4 while preserving the full data strength for precise positioning. The resulting single data stream is that of carrier phase measurements with both data noise and bias uncertainty strictly defined. With this mathematical formula the single stream of optimally combined GPS measurements can be efficiently formed by simple numerical calculations. Carrier phase ambiguity resolution, when feasible, is strengthened due to the preserved full data strength with the optimally combined data and the resulting longer wavelength for the ambiguity to be resolved.

Wu, Sien-Chong↗

Image data processing of earth resources management

The Earth Resources Technology Satellite (ERTS-1) was launched on July 23, 1972. Since that date, the vehicle has been acquiring and transmitting to earth a vast amount of information relating to the earth's resources. Scientific investigators throughout the world have been analyzing photographic products produced from this data with significant results. Recently, there has been a major shift of emphasis from the visual analysis of photo products to the use of sophisticated digital information extraction techniques. Specialized equipment, such as the GE IMAGE 100 System, has been developed that operates directly from Computer Compatible Tapes, (CCT’s), which contain preprocessed digital data acquired from the ERTS spacecraft. Analysis of CCT data avoids the losses in image resolution and quality which are inherent to all photo processing techniques, thereby greatly increasing the utility of ERTS data. Future ground processing systems will turn out fully corrected (radiometric and geometric) digital tapes which will further increase the utility of ERTS data. This paper is presented in two parts: the first part deals with the subject of present and future generations of image processing and information extraction systems under development at the General Electric Company; the second part describes in more detail the design and operation of GE1s interactive multispectral information extraction systems, IMAGE 100, and discusses results of analyses of ERTS data over a number of U.S. sites.

A W DeSio↗

Next generation functional components for space telemetry data processing

The use of new design methodologies to continue the evolution of telemetry data systems to higher levels of integration is discussed. In particular, hardware description languages and automated logic synthesis tools are used to create very dense Application Specific Integrated Circuits (ASICs) that generically implement telemetry processing functions. The use of the ASICs will make it possible to develop a new generation of functional components, each of the components integrating several telemetry processing subsystems into a single card.

Bennett, Toby↗

GEOS 3 data processing for the recovery of geoid undulations and gravity anomalies

The paper discusses the analysis of GEOS 3 altimeter data for the determination of geoid heights and point and mean gravity anomalies. Methods are presented for determining the mean anomalies and mean undulations from the GEOS 3 altimeter data available by the end of September 1977 without having a complete set of precise orbits. The editing of the data is extensive to remove questionable data, although no filtering of the data is carried out. An adjustment process is carried out to eliminate orbit error and altimeter bias. Representative point anomaly values are computed to investigate anomaly behavior across the Bonin Trench and over the Patton seamounts.

Rapp, R. H.↗

The payload connection - Approaches to onboard data processing for scientific systems on the Space Shuttle

The integration of payload instruments into the Command and Data Management Subsystem (CDMS) of the Space Shuttle Spacelab is discussed. Specific emphasis is on the distributed (self-contained processor) vs centralized (Spacelab Computer) approach to science payload utilization of these control and data handling capabilities. An overview of the Spacelab CDMS is first given. A synopsis of the integration process for Spacelab Missions 1, 2, and 3 is discussed. Three different hardware approaches to payload command and data handling are then categorized from which Spacelab implementations to date are derived. The different types of Spacelab Mission 3 payload CDMS hardware and software being used are discussed, including examples of microprocessors and data acquisition systems. Preliminary costs for Spacelab application software vs other flight software approaches are compared. A standard RAU interface that would permit a range of ECOS services to be provided, yet be implemented as a mass-produceable unit for incorporation into payloads, is proposed, in keeping with the trend toward simplifying the integration effort, standardizing CDMS interfaces, and ultimately lowering cost.

Konkel, C. R.↗

WFC3 Calibration and Data Processing

Wide Field Camera 3 (WFC3), a panchromatic imager being developed for the Hubble Space Telescope (HST), is now fully integrated and over the past year has completed first rounds of extensive ground testing at Goddard Space Flight Center (GSFC), in both ambient and thermal-vacuum test environments. This report summarizes the results of those tests and describes the pipeline processing methods that will be used to calibrate WFC3 data. WFC3 is designed to ensure that the superb imaging performance of HST is maintained through the end of the mission and takes advantage of recent developments in detector technology to provide new and unique capabilities for HST. WFC3 contains ultraviolet/visible (UVIS) and near-infrared (IR) imaging channels, offering high sensitivity and wide field of view over the broadest wavelength range of any HST instrument. It is slated to replace the current Wide Field and Planetary Camera 2 during Servicing Mission 4. The WFC3 UVIS channel is based on elements from the Advanced Camera for Surveys (ACS)Wide Field Camera (WFC), with a 4096x4096 pixel Marconi CCD covering a 160x160 arcsecond field of view. The WFC3 UVIS channel is optimized for maximum sensitivity in the near-UV and contains a complement of 48 spectral filters and a grism. The WFC3 IR channel uses a 1024x1024 pixel HgCdTe Hawaii-1R detector array covering a 135x135 arcsecond field of view. The array sensitivity is optimized in the 0.8-1.7micron spectral range. The IR channel accomodates 15 filters and 2 grisms for slitless spectroscopy.

Bushouse, H.↗

Data reduction complex analog-to-digital data processing requirements for onsite test facilities

The analog to digital processing requirements of onsite test facilities are described. The source and medium of all input data to the Data Reduction Complex (DRC) and the destination and medium of all output products of the analog-to-digital processing are identified. Additionally, preliminary input and output data formats are presented along with the planned use of the output products.

Debbrecht, J. D.↗

LANDSAT digital data processing: A near real-time application

An application of rapid generation of classed digital images from LANDSAT-1 was demonstrated and its feasibility evaluated by NASA in conjunction with the Environmental Protection Agency (EPA), Texas A and M University (TAMU), and the Cousteau Society. The primary purpose was to show that satellite data could be processed and transmitted to the Calypso, which was used as a research vessel, in time for use in directing it to specific locations of possible plankton upwellings, sediment, or other anomalies in the coastal water areas along the Gulf of Mexico.

Barker, J. L.↗

MAGSAT data processing: A report for investigators

The in-flight attitude and vector magnetometer data bias recovery techniques and results are described. The attitude bias recoveries are based on comparisons with a magnetic field model and are thought to be accurate to 20 arcsec. The vector magnetometer bias recoveries are based on comparisons with the scalar magnetometer data and are thought to be accurate to 3 nT or better. The MAGSAT position accuracy goals of 60 m radially and 300 m horizontally were achieved for all but the last 3 weeks of Magsat lifetime. This claim is supported by ephemeris overlap statistics and by comparisons with ephemerides computed with an independent orbit program using data from an independent tracking network. MAGSAT time determination accuracy is estimated at 1 ms. Several errors in prelaunch assumptions regarding data time tags, which escaped detection in prelaunch data tests, and were discovered and corrected postlaunch are described. Data formats and products, especially the Investigator-B tapes, which contain auxiliary parameters in addition to the basic magnetometer and ephemeris data, are described.

Langel, R. A.↗

The Kepler Science Data Processing Pipeline Source Code Road Map

We give an overview of the operational concepts and architecture of the Kepler Science Processing Pipeline. Designed, developed, operated, and maintained by the Kepler Science Operations Center (SOC) at NASA Ames Research Center, the Science Processing Pipeline is a central element of the Kepler Ground Data System. The SOC consists of an office at Ames Research Center, software development and operations departments, and a data center which hosts the computers required to perform data analysis. The SOC's charter is to analyze stellar photometric data from the Kepler spacecraft and report results to the Kepler Science Office for further analysis. We describe how this is accomplished via the Kepler Science Processing Pipeline, including, the software algorithms. We present the high-performance, parallel computing software modules of the pipeline that perform transit photometry, pixel-level calibration, systematic error correction, attitude determination, stellar target management, and instrument characterization.

Kepler pipeline software↗

Spacelab data processing facility (SLDPF) Quality Assurance (QA)/Data Accounting (DA) expert systems: Transition from prototypes to operational systems

The SLDPF is responsible for the capture, quality monitoring processing, accounting, and shipment of Spacelab and/or Attached Shuttle Payloads (ASP) telemetry data to various user facilities. Expert systems will aid in the performance of the quality assurance and data accounting functions of the two SLDPF functional elements: the Spacelab Input Processing System (SIPS) and the Spacelab Output Processing System (SOPS). Prototypes were developed for each as independent efforts. The SIPS Knowledge System Prototype (KSP) used the commercial shell OPS5+ on an IBM PC/AT; the SOPS Expert System Prototype used the expert system shell CLIPS implemented on a Macintosh personal computer. Both prototypes emulate the duties of the respective QA/DA analysts based upon analyst input and predetermined mission criteria parameters, and recommended instructions and decisions governing the reprocessing, release, or holding for further analysis of data. These prototypes demonstrated feasibility and high potential for operational systems. Increase in productivity, decrease of tedium, consistency, concise historial records, and a training tool for new analyses were the principal advantages. An operational configuration, taking advantage of the SLDPF network capabilities, is under development with the expert systems being installed on SUN workstations. This new configuration in conjunction with the potential of the expert systems will enhance the efficiency, in both time and quality, of the SLDPF's release of Spacelab/AST data products.

Basile, Lisa↗

Spacelab data processing facility (SLDPF) quality assurance (QA)/data accounting (DA) expert systems - Transition from prototypes to operational systems

The SLDPF is responsible for the capture, quality monitoring processing, accounting, and shipment of Spacelab and/or Attached Shuttle Payloads (ASP) telemetry data to various user facilities. Expert systems will aid in the performance of the quality assurance and data accounting functions of the two SLDPF functional elements: the Spacelab Input Processing System (SIPS) and the Spacelab Output Processing System (SOPS). Prototypes were developed for each as independent efforts. The SIPS Knowledge System Prototype (KSP) used the commercial shell OPS5+ on an IBM PC/AT; the SOPS Expert System Prototype used the expert system shell CLIPS implemented on a Macintosh personal computer. Both prototypes emulate the duties of the respective QA/DA analysts based upon analyst input and predetermined mission criteria parameters, and recommended instructions and decisions governing the reprocessing, release, or holding for further analysis of data. These prototypes demonstrated feasibility and high potential for operational systems. Increase in productivity, decrease of tedium, consistency, concise historical records, and a training tool for new analyses were the principal advantages. An operational configuration, taking advantage of the SLDPF network capabilities, is under development with the expert systems being installed on SUN workstations. This new configuration in conjunction with the potential of the expert systems will enhance the efficiency, in both time and quality, of the SLDPF's release of Spacelab/AST data products.

Basile, Lisa↗

Using NASA's Reference Architecture: Comparing Polar and Geostationary Data Processing Systems

The JPSS and GOES-R programs are housed at NASA GSFC and jointly implemented by NASA and NOAA to NOAA requirements. NASA's role in the JPSS Ground System is to develop and deploy the system according to NOAA requirements. NASA's role in the GOES-R ground segment is to provide Systems Engineering expertise and oversight for NOAA's development and deployment of the system. NASA's Earth Science Data Systems Reference Architecture is a document developed by NASA's Earth Science Data Systems Standards Process Group that describes a NASA Earth Observing Mission Ground system as a generic abstraction. The authors work within the respective ground segment projects and are also separately contributors to the Reference Architecture document. Opinions expressed are the author's only and are not NOAA, NASA or the Ground Projects' official positions.

Ullman, Richard↗

Data Processing for Atmospheric Phase Interferometers

This paper presents a detailed discussion of calibration procedures used to analyze data recorded from a two-element atmospheric phase interferometer (API) deployed at Goldstone, California. In addition, we describe the data products derived from those measurements that can be used for site intercomparison and atmospheric modeling. Simulated data is used to demonstrate the effectiveness of the proposed algorithm and as a means for validating our procedure. A study of the effect of block size filtering is presented to justify our process for isolating atmospheric fluctuation phenomena from other system-induced effects (e.g., satellite motion, thermal drift). A simulated 24 hr interferometer phase data time series is analyzed to illustrate the step-by-step calibration procedure and desired data products.

Acosta, Roberto J.↗

Atmospheric phenomena data processing and display

Several related efforts which deal with the analysis and display of data pertaining to various atmospheric phenomena are reported. Spectrometer data analysis, with refinements to the preexisting programs, is discussed. A discussion of a Monte Carlo simulation of a photon transfer problem is presented. Raw data gathered in the field by a high-flying U2 aircraft is usually pulse code modulated (PCM). Techniques to reduce the data into a computer-amenable format are described. Several utility programs and other work are outlined.

Tatom, F. B.↗

Architecture and data processing alternatives for Tse computer. Volume 1: Tse logic design concepts and the development of image processing machine architectures

Digital computer components which perform two dimensional array logic operations (Tse logic) on binary data arrays are described. The properties of Golay transforms which make them useful in image processing are reviewed, and several architectures for Golay transform processors are presented with emphasis on the skeletonizing algorithm. Conventional logic control units developed for the Golay transform processors are described. One is a unique microprogrammable control unit that uses a microprocessor to control the Tse computer. The remaining control units are based on programmable logic arrays. Performance criteria are established and utilized to compare the various Golay transform machines developed. A critique of Tse logic is presented, and recommendations for additional research are included.

Rickard, D. A.↗

Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins

This repository of global hydrogeologic datasets contains aquifer properties on 0.5° scale, including depth to groundwater (Fan et al., 2013), aquifer thickness (de Graaf et al., 2015), WHYMap aquifer classes (Richts et al., 2011), recharge (Döll and Fiedler, 2008; Gleeson et al., 2016), lakes (Messager et al., 2016), porosity and permeability (Gleeson et al., 2014), digitized and geo-processed from their respective sources. Globally gridded aquifer properties could be used independently to estimate global groundwater availability or used as critical inputs to the superwell model to simulate groundwater extraction and provide estimates of pumped volumes and unit costs under user-specific scenarios. Key resources related to this data are: Niazi, H., Ferencz, S. B., Graham, N. T., Yoon, J., Wild, T. B., Hejazi, M., Watson, D. J., & Vernon, C. R. (2025). Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1. Geoscientific Model Development, 18(5), 1737-1767. https://doi.org/10.5194/gmd-18-1737-2025 superwell model repository which uses this data to simulate groundwater extraction and provides estimates of the global extractable volumes and unit-costs ($/km3) of accessible groundwater production under user-specified extraction scenarios. Repository Overview Main output: aquifer_properties_rec.csv contains all processed outputs, including aquifer properties like porosity, permeability, recharge, lake areas, aquifer thickness, and depth to groundwater. shapefiles.zip: contains all digitized GIS databases and shapefile for all aquifer properties prep_inputs.R and prep_inputs_recharge_lakes.R: R scripts that process the shapefiles to produce the aquifer_properties_rec.csv file plot_inputs.R: R script for plotting the maps and conducting preliminary analysis on the available groundwater volume basin_to_country_mapping.csv, basin_country_region_mapping.csv and continent_county_mapping.csv provide the mapping between continents, 32 energy-economic macro regions, countries, and water basins for post-processing aquifer_properties_rec.csv Maps: Each map visualizes the spatial distribution of one of the aquifer properties across the globe map_in_Porosity.png map_in_Permeability.png map_in_Aquifer_thickness.png map_in_Depth_to_water.png map_in_Recharge.png map_in_Grid_area_km.png map_in_Lake_area_km.png map_in_WHYClass.png Sample inputs sample_inputs.py: this script samples inputs from the aquifer_properties_rec dataset, ensuring the sampled and original inputs maintain the same distributions sampled_data_100.csv contains 100 sampled data points and sampled_data_100.png compares their distributions Dataset Overview The main outputs are consolidated in a comprehensive aquifer_properties_rec.csv file and include the following fields: GridCellID: Unique identifier for each (roughly 0.5°) grid cell Continent: Continent name Country: Country name GCAM_basin_ID: Identifier for GCAM hydrologic basin Basin_long_name: Full name of the basin WHYClass: Hydrogeologic classification based on WHYMap aquifer classes (Richts et al., 2011) Porosity: Soil porosity (%) (Gleeson et al., 2014) Permeability: Soil permeability (in square meters; Gleeson et al., 2014) Aquifer_thickness: Thickness of the aquifer (in meters; de Graaf et al., 2015) Depth_to_water: Depth to groundwater (in meters; Fan et al., 2013) Recharge: long-term annual averaged recharge rates (in m/yr; Döll and Fiedler, 2008; Gleeson et al., 2016) Grid_area: Area of the grid cell (in square meters) Lakes_area: Area of inland lakes (in square meters; Messager et al., 2016) Key References The datasets are digitized versions of global hydrogeologic properties from the following key literature sources: Depth to Groundwater: Fan, Y., Li, H., & Miguez-Macho, G. (2013). Global Patterns of Groundwater Table Depth. Science, 339(6122), 940-943. https://doi.org/10.1126/science.1229881 Aquifer Thickness: de Graaf, I. E. M., Sutanudjaja, E. H., van Beek, L. P. H., & Bierkens, M. F. P. (2015). A high-resolution global-scale groundwater model. Hydrol. Earth Syst. Sci., 19(2), 823-837. https://doi.org/10.5194/hess-19-823-2015 Porosity and Permeability: Gleeson, T., Moosdorf, N., Hartmann, J., & van Beek, L. P. H. (2014). A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity. Geophysical Research Letters, 41(11), 3891-3898. https://doi.org/10.1002/2014GL059856 Aquifer classes: Richts, A., Struckmeier, W. F., & Zaepke, M. (2011). WHYMAP and the Groundwater Resources Map of the World 1:25,000,000. In J. A. A. Jones (Ed.), Sustaining Groundwater Resources: A Critical Element in the Global Water Crisis (pp. 159-173). Springer Netherlands. https://doi.org/10.1007/978-90-481-3426-7_10 Recharge: Döll, P., & Fiedler, K. (2008). Global-scale modeling of groundwater recharge. Hydrol. Earth Syst. Sci., 12(3), 863-885. https://doi.org/10.5194/hess-12-863-2008; Gleeson, T., Befus, K. M., Jasechko, S., Luijendijk, E., & Cardenas, M. B. (2016). The global volume and distribution of modern groundwater. Nature Geoscience, 9(2), 161-167. https://doi.org/10.1038/ngeo2590 Inland Lakes: Messager, M. L., Lehner, B., Grill, G., Nedeva, I., & Schmitt, O. (2016). Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nature Communications, 7(1), 13603. https://doi.org/10.1038/ncomms13603 Cite as Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MultiSector Dynamics-Living, Intuitive, Value-adding, Environment. https://doi.org/10.57931/2484226 Contact Reach out to Hassan Niazi or open an issue in the superwell repository for questions or suggestions.

aquifer thickness↗