Engineering topics

Strub, Richard

Publications and source records attributed to Strub, Richard.

At least 19 records

NASA NTRS2017

The Value of Data and Metadata Standardization for Interoperability in Giovanni Or: Why Your Product's Metadata Causes Us Headaches!

Giovanni is a data exploration and visualization tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC). It has been around in one form or another for more than 15 years. Giovanni calculates simple statistics and produces 22 different visualizations for more than 1600 geophysical parameters from more than 90 satellite and model products. Giovanni relies on external data format standards to ensure interoperability, including the NetCDF CF Metadata Conventions. Unfortunately, these standards were insufficient to make Giovanni's internal data representation truly simple to use. Finding and working with dimensions can be convoluted with the CF Conventions. Furthermore, the CF Conventions are silent on machine-friendly descriptive metadata such as the parameter's source product and product version. In order to simplify analyzing disparate earth science data parameters in a unified way, we developed Giovanni's internal standard. First, the format standardizes parameter dimensions and variables so they can be easily found. Second, the format adds all the machine-friendly metadata Giovanni needs to present our parameters to users in a consistent and clear manner. At a glance, users can grasp all the pertinent information about parameters both during parameter selection and after visualization.

interoperability↗

NASA NTRS2016

Optimal Reorganization of NASA Earth Science Data for Enhanced Accessibility and Usability for the Hydrology Community

A long-standing "Digital Divide" in data representation exists between the preferred way of data access by the hydrology community and the common way of data archival by earth science data centers. Typically, in hydrology, earth surface features are expressed as discrete spatial objects (e.g., watersheds), and time-varying data are contained in associated time series. Data in earth science archives, although stored as discrete values (of satellite swath pixels or geographical grids), represent continuous spatial fields, one file per time step. This Divide has been an obstacle, specifically, between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. and NASA earth science data systems. In essence, the way data are archived is conceptually orthogonal to the desired method of access. Our recent work has shown an optimal method of bridging the Divide, by enabling operational access to long-time series (e.g., 36 years of hourly data) of selected NASA datasets. These time series, which we have termed "data rods," are pre-generated or generated on-the-fly. This optimal solution was arrived at after extensive investigations of various approaches, including one based on "data curtains." The on-the-fly generation of data rods uses "data cubes," NASA Giovanni, and parallel processing. The optimal reorganization of NASA earth science data has significantly enhanced the access to and use of the data for the hydrology user community.

data rods↗

NASA NTRS2015

Between a Map and a Data Rod

A Digital Divide has long stood between how NASA and other satellite-derived data are typically archived (time-step arrays or maps) and how hydrology and other point-time series oriented communities prefer to access those data. In essence, the desired method of data access is orthogonal to the way the data are archived. Our approach to bridging the Divide is part of a larger NASA-supported data rods project to enhance access to and use of NASA and other data by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS) and the larger hydrology community. Our main objective was to determine a way to reorganize data that is optimal for these communities. Two related objectives were to optimally reorganize data in a way that (1) is operational and fits in and leverages the existing Goddard Earth Sciences Data and Information Services Center (GES DISC) operational environment and (2) addresses the scaling up of data sets available as time series from those archived at the GES DISC to potentially include those from other Earth Observing System Data and Information System (EOSDIS) data archives. Through several prototype efforts and lessons learned, we arrived at a non-database solution that satisfied our objectivesconstraints. We describe, in this presentation, how we implemented the operational production of pre-generated data rods and, considering the tradeoffs between length of time series (or number of time steps), resources needed, and performance, how we implemented the operational production of on-the-fly (virtual) data rods. For the virtual data rods, we leveraged a number of existing resources, including the NASA Giovanni Cache and NetCDF Operators (NCO) and used data cubes processed in parallel. Our current benchmark performance for virtual generation of data rods is about a years worth of time series for hourly data (9,000 time steps) in 90 seconds. Our approach is a specific implementation of the general optimal strategy of reorganizing data to match the desired means of access. Results from our project have already significantly extended NASA data to the large and important hydrology user community that has been, heretofore, mostly unable to easily access and use NASA data.

machine learning↗

NASA NTRS2014

Enhancement of Mutual Discovery, Search, and Access of Data for Users of NASA and GEOSS-Cataloged Data Systems

An ongoing NASA-funded Data Rods (time series) project has demonstrated the removal of a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series) for selected variables of the North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) and other NASA data sets. Data rods are pre-generated or generated on-the-fly (OTF), leveraging the NASA Simple Subset Wizard (SSW), a gateway to NASA data centers. Data rods Web services are accessible through the CUAHSI Hydrologic Information System (HIS) and the Goddard Earth Sciences Data and Information Services Center (GES DISC) but are not easily discoverable by users of other non-NASA data systems. An ongoing GEOSS Water Services project aims to develop a distributed, global registry of water data, map, and modeling services cataloged using the standards and procedures of the Open Geospatial Consortium and the World Meteorological Organization. Preliminary work has shown GEOSS can be leveraged to help provide access to data rods. A new NASA-funded project is extending this early work.

data access↗

NASA NTRS2013

Data Quality Screening Service

A report describes the Data Quality Screening Service (DQSS), which is designed to help automate the filtering of remote sensing data on behalf of science users. Whereas this process often involves much research through quality documents followed by laborious coding, the DQSS is a Web Service that provides data users with data pre-filtered to their particular criteria, while at the same time guiding the user with filtering recommendations of the cognizant data experts. The DQSS design is based on a formal semantic Web ontology that describes data fields and the quality fields for applying quality control within a data product. The accompanying code base handles several remote sensing datasets and quality control schemes for data products stored in Hierarchical Data Format (HDF), a common format for NASA remote sensing data. Together, the ontology and code support a variety of quality control schemes through the implementation of the Boolean expression with simple, reusable conditional expressions as operands. Additional datasets are added to the DQSS simply by registering instances in the ontology if they follow a quality scheme that is already modeled in the ontology. New quality schemes are added by extending the ontology and adding code for each new scheme.

Strub, Richard↗

NASA NTRS2008

Mirador: A Simple, Fast Search Interface for Remote Sensing Data

A major challenge for remote sensing science researchers is searching and acquiring relevant data files for their research projects based on content, space and time constraints. Several structured query (SQ) and hierarchical navigation (HN) search interfaces have been develop ed to satisfy this requirement, yet the dominant search engines in th e general domain are based on free-text search. The Goddard Earth Sci ences Data and Information Services Center has developed a free-text search interface named Mirador that supports space-time queries, inc luding a gazetteer and geophysical event gazetteer. In order to compe nsate for a slightly reduced search precision relative to SQ and HN t echniques, Mirador uses several search optimizations to return result s quickly. The quick response enables a more iterative search strateg y than is available with many SQ and HN techniques.

Lynnes, Christopher↗

NASA NTRS2000

Saskatchewan Forest Fire Control Centre Surface Meteorological Data

The Saskatchewan Forest Fire Control Centre (SFFCC) provided surface meteorological data to BOREAS from its archive. This data set contains hourly surface meteorological data from 18 of the Meteorological stations located across Saskatchewan. Included in these data are parameters of date, time, temperature, relative humidity, wind direction, wind speed, and precipitation. Temporally, the data cover the period of May through September of 1994 and 1995. The data are provided in comma-delimited ASCII files, and are classified as AFM-Staff data. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS2000

BOREAS AES Five-Day Averaged Surface Meteorological and Upper Air Data

The Canadian Atmospheric Environment Service (AES) provided BOREAS with hourly and daily surface meteorological data from 23 of the AES meteorological stations located across Canada and upper air data from 1 station at The Pas, Manitoba. Due to copyright restrictions on the full resolution surface meteorological data, this data set contains 5-day average values for the surface parameters. The upper air data are provided in their full resolution form. The 5-day averaging was performed in order to create a data set that could be publicly distributed at no cost. Temporally, the surface meteorological data cover the period of January 1975 to December 1996 and the upper air data cover the period of January 1961 to November 1996. The data are provided in tabular ASCII files, and are classified as AFM-staff data. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS2000

BOREAS Level-1B MAS Imagery At-sensor Radiance, Relative X and Y Coordinates

For BOReal Ecosystem-Atmosphere Study (BOREAS), the MODIS Airborne Simulator (MAS) images, along with the other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes detailed land cover and biophysical parameter maps such as fraction of Photosynthetically Active Radiation (fPAR) and Leaf Area Index (LAI). Collection of the MAS images occurred over the study areas during the 1994 field campaigns. The level-1b MAS data cover the dates of 21-Jul-1994, 24-Jul-1994, 04-Aug-1994, and 08-Aug-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C-130 INS data in a MAS scan model. The data are provided in binary image format files.

Strub, Richard↗

NASA NTRS2000

BOREAS Level-0 ER-2 Navigation Data

The BOREAS Staff Science effort covered those activities that were BOREAS community-level activities or required uniform data collection procedures across sites and time. These activities included the acquisition, processing, and archiving of aircraft navigation/attitude data to complement the digital image data. The level-0 ER-2 navigation data files contain aircraft attitude and position information acquired during the digital image and photographic data collection missions. Temporally, the data were acquired from April to September 1994. Data were recorded at intervals of 5 seconds. The data are stored in tabular ASCII files.

Strub, Richard↗

NASA NTRS2000

BOREAS ECMWF 6-Hour Analysis and Forecast Data

In cooperation with BOREAS atmospheric research efforts, the ECMWF agreed to provide BOREAS with a customized subset of its 6-hourly forecast data. This data set contains parameters from three ECMWF data products in GRIB format: Surface and Diagnostic Fields, Supplemental Fields, and Extension Data. Sample software and information are provided to assist in reading the data files. Temporally, the atmospheric parameters are available for the four main synoptic hours of 00, 06, 12, and 18 UTC from 1994 to 1996. Spatially, the data are stored in a 0.5- by 0.5-degree latitude/longitude grid. To cover the entire BOREAS study area, the grid extends from 48 to 62 degrees latitude and -92 to -114 degrees longitude. The data are stored in binary data representation known as FM 92 GRIB. Due to the complexity of the content and format of this data set, users are advised to read Sections 6, 7, 8, and 14 before using data. Based on agreements between BOREAS and ECMWF, users may legally obtain and use these data only by having a set of the BOREAS CD-ROMs that contain the data. Possession or use of these data under any other circumstance is prohibited. See Sections 11.3 and 20.4 for details.

Viterbo, Pedro↗

NASA NTRS2000

BOREAS Landsat MSS Imagery: Digital Counts

The Boreal Ecosystem-Atmospheric Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. The Earth Resources Technology Satellite (ERTS) Program launched the first of a series of satellites (ERTS-1) in 1972. Part of the NASA Earth Resources Survey Program, the ERTS Program and the ERTS satellites were later renamed Landsat to better represent the civil satellite program's prime emphasis on remote sensing of land resources. Landsat satellites 1 through 5 carry the Multispectral Scanner (MSS) sensor. Canada for Remote Sensing (CCRS) and BOREAS personnel gathered a set of MSS images of the BOREAS region from Landsat satellites 1, 2, 4, and 5 covering the dates of 21 Aug 1972 to 05 Sep 1988. The data are provided in binary image format files of various formats. The Landsat MSS imagery is available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS2000

BOREAS Level-1B TIMS Imagery: At-sensor Radiance in BSQ Format

The Boreal Ecosystem-Atmospheric Study (BOREAS) Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. For BOREAS, the Thermal Infrared Multispectral Scanner (TIMS) imagery, along with other aircraft images, was collected to provide spatially extensive information over the primary study areas. The Level-1b TIMS images cover the time periods of 16 to 20 Apr 1994 and 06 to 17 Sep 1994. The system calibrated images are stored in binary image format files. The TIMS images are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS2000

BOREAS Level-2 NS001 TMS Imagery: Reflectance and Temperature in BSQ Format

For BOREAS, the NS001 TMS images, along with the other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes detailed land cover and biophysical parameter maps such as fPAR and LAI. Collection of the NS001 images occurred over the study areas during the 1994 field campaigns. The level-2 NS001 data are atmospherically corrected versions of some of the best original NS001 imagery and cover the dates of 19-Apr-1994, 07-Jun-1994, 21-Jul-1994, 08-Aug-1994, and 16-Sep-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C130 INS data in an NS001 scan model. The data are provided in binary image format files.

Lobitz, Brad↗

NASA NTRS2000

BOREAS Level-2 MAS Surface Reflectance and Temperature Images in BSQ Format

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed aircraft data products they needed to compare and spatially extend point results. The MODIS Airborne Simulator (MAS) images, along with other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes biophysical parameter maps such as surface reflectance and temperature. Collection of the MAS images occurred over the study areas during the 1994 field campaigns. The level-2 MAS data cover the dates of 21-Jul-1994, 24-Jul-1994, 04-Aug-1994, and 08-Aug-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C130 navigation data in a MAS scan model. The data are provided in binary image format files.

Hall, Forrest G.↗

NASA NTRS2000

BOREAS Level-0 C-130 Navigation Data

The level-0 C-130 navigation data files contain aircraft attitude and position information acquired during the digital image and photographic data collection missions over the BOReal Ecosystem-Atmosphere Study (BOREAS) study areas. Various portions of the navigation data were collected at 1, 10, and 30 Hz. The level-0 C-130 navigation data collected for BOREAS in 1994 were improved over previous years in that the C-130 onboard navigation system was upgraded to output inertial navigation parameters every 1/30th of a second (i.e., 30 Hz). This upgrade was encouraged by users of the aircraft scanner data with the hope of improving the relative geometric positioning of the collected images.

Strub, Richard↗

NASA NTRS2000

BOREAS Level-3s SPOT Imagery: Scaled At-sensor Radiance in LGSOWG Format

For BOReal Ecosystem-Atmosphere Study (BOREAS), the level-3s Satellite Pour l'Observation de la Terre (SPOT) data, along with the other remotely sensed images, were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy, detailed land cover, and biophysical parameter maps such as Fraction of Photosynthetically Active Radiation (FPAR) and Leaf Area Index (LAI). The SPOT images acquired for the BOREAS project were selected primarily to fill temporal gaps in the Landsat Thematic Mapper (TM) image data collection. CCRS collected and supplied the level-3s images to BOREAS Information System (BORIS) for use in the remote sensing research activities. Spatially, the level-3s images cover 60- by 60-km portions of the BOREAS Northern Study Area (NSA) and Southern Study Area (SSA). Temporally, the images cover the period of 17-Apr-1994 to 30-Aug-1996. The images are available in binary image format files. Due to copyright issues, the SPOT images may not be publicly available.

Strub, Richard↗

NASA NTRS2000

BOREAS RSS-16 AIRSAR CM Images: Integrated Processor Version 6.1 Level-3b

The BOREAS RSS-16 team used satellite and aircraft SAR data in conjunction with various ground measurements to determine the moisture regime of the boreal forest. RSS-16 assisted with the acquisition and ordering of NASA JPL AIRSAR data collected from the NASA DC-8 aircraft. The NASA JPL AIRSAR is a side-looking imaging radar system that utilizes the SAR principle to obtain high resolution images that represent the radar backscatter of the imaged surface at different frequencies and polarizations. The information contained in each pixel of the AIRSAR data represents the radar backscatter for all possible combinations of horizontal and vertical transmit and receive polarizations (i.e., HH, HV, VH, and VV). Geographically, the data cover portions of the BOREAS SSA and NSA. Temporally, the data were acquired from 12-Aug-1993 to 31-Jul-1995. The level-3b AIRSAR CM data are in compressed Stokes matrix format, which has 10 bytes per pixel. From this data format, it is possible to synthesize a number of different radar backscatter measurements. The data are stored in binary image-format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗