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NASA NTRS2004

Velocity Structure and Plasma Properties in Halo CMES

We have identified a set of 23 Halo CMEs and 21 Partial Halo CMEs from the LASCO Halo CME Archive for which UVCS spectra exist through July 2002. For each event we have collected basic information such as the event speed, whether or not UVCS caught the bright front, lines detected, Doppler shift and associated flare class. We are currently analyzing the subset for which UVCS caught the CME front. We also obtained excellent observations of some of the spectacular events in November 2003, and we have made theoretical calculations pertaining to CME expansion at the heights observed by UVCS. In one event we were able to analyze the properties of the current sheet in detail.

Raymond, John C.↗

NASA NTRS2005

NASA Remote Sensing Data in Earth Sciences: Processing, Archiving, Distribution, Applications at the GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of the major Distributed Active Archive Centers (DAACs) archiving and distributing remote sensing data from the NASA's Earth Observing System. In addition to providing just data, the GES DISC/DAAC has developed various value-adding processing services. A particularly useful service is data processing a t the DISC (i.e., close to the input data) with the users' algorithms. This can take a number of different forms: as a configuration-managed algorithm within the main processing stream; as a stand-alone program next to the on-line data storage; as build-it-yourself code within the Near-Archive Data Mining (NADM) system; or as an on-the-fly analysis with simple algorithms embedded into the web-based tools (to avoid downloading unnecessary all the data). The existing data management infrastructure at the GES DISC supports a wide spectrum of options: from data subsetting data spatially and/or by parameter to sophisticated on-line analysis tools, producing economies of scale and rapid time-to-deploy. Shifting processing and data management burden from users to the GES DISC, allows scientists to concentrate on science, while the GES DISC handles the data management and data processing at a lower cost. Several examples of successful partnerships with scientists in the area of data processing and mining are presented.

Leptoukh, Gregory G.↗

NASA NTRS2011

Ares I-X Flight Data Evaluation: Executive Overview

NASA's Constellation Program (CxP) successfully launched the Ares I-X flight test vehicle on October 28, 2009. The Ares I-X flight was a developmental flight test to demonstrate that this very large, long, and slender vehicle could be controlled successfully. The flight offered a unique opportunity for early engineering data to influence the design and development of the Ares I crew launch vehicle. As the primary customer for flight data from the Ares I-X mission, the Ares Projects Office (APO) established a set of 33 flight evaluation tasks to correlate flight results with prospective design assumptions and models. The flight evaluation tasks used Ares I-X data to partially validate tools and methodologies in technical disciplines that will ultimately influence the design and development of Ares I and future launch vehicles. Included within these tasks were direct comparisons of flight data with preflight predictions and post-flight assessments utilizing models and processes being applied to design and develop Ares I. The benefits of early development flight testing were made evident by results from these flight evaluation tasks. This overview provides summary information from assessment of the Ares I-X flight test data and represents a small subset of the detailed technical results. The Ares Projects Office published a 1,600-plus-page detailed technical report that documents the full set of results. This detailed report is subject to the International Traffic in Arms Regulations (ITAR) and is available in the Ares Projects Office archives files.

Huebner, Lawrence D.↗

NASA NTRS2023

A Community Convention for Ecological Forecasting: Output Files and Metadata Version 1.0

This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe the convention conceptually in terms of global attributes, forecast dimensions, forecasted variables, and ancillary indicator variables. We then illustrate the application of this convention to the two file formats that are currently preferred by the EFI, netCDF (network common data form), and comma-separated values (CSV), but note that the convention is extensible to future formats. For metadata, EFI's convention identifies a subset of conventional metadata variables that are required (e.g., temporal resolution and output variables) but focuses on developing a framework for storing information about forecast uncertainty propagation, data assimilation, and model complexity, which aims to facilitate cross-forecast synthesis. The initial application of this convention expands upon the Ecological Metadata Language (EML), a commonly used metadata standard in ecology. To facilitate community adoption, we also provide a Github repository containing a metadata validator tool and several vignettes in R and Python on how to both write and read in the EFI standard. Lastly, we provide guidance on forecast archiving, making an important distinction between short-term dissemination and long-term forecast archiving, while also touching on the archiving of code and workflows. Overall, the EFI convention is a living document that can continue to evolve over time through an open community process.

Michael C. Dietze↗

NASA NTRS2011

Report on the Global Data Assembly Center (GDAC) to the 12th GHRSST Science Team Meeting

In 2010/2011 the Global Data Assembly Center (GDAC) at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) continued its role as the primary clearinghouse and access node for operational Group for High Resolution Sea Surface Temperature (GHRSST) datastreams, as well as its collaborative role with the NOAA Long Term Stewardship and Reanalysis Facility (LTSRF) for archiving. Here we report on our data management activities and infrastructure improvements since the last science team meeting in June 2010.These include the implementation of all GHRSST datastreams in the new PO.DAAC Data Management and Archive System (DMAS) for more reliable and timely data access. GHRSST dataset metadata are now stored in a new database that has made the maintenance and quality improvement of metadata fields more straightforward. A content management system for a revised suite of PO.DAAC web pages allows dynamic access to a subset of these metadata fields for enhanced dataset description as well as discovery through a faceted search mechanism from the perspective of the user. From the discovery and metadata standpoint the GDAC has also implemented the NASA version of the OpenSearch protocol for searching for GHRSST granules and developed a web service to generate ISO 19115-2 compliant metadata records. Furthermore, the GDAC has continued to implement a new suite of tools and services for GHRSST datastreams including a Level 2 subsetter known as Dataminer, a revised POET Level 3/4 subsetter and visualization tool, a Google Earth interface to selected daily global Level 2 and Level 4 data, and experimented with a THREDDS catalog of GHRSST data collections. Finally we will summarize the expanding user and data statistics, and other metrics that we have collected over the last year demonstrating the broad user community and applications that the GHRSST project continues to serve via the GDAC distribution mechanisms. This report also serves by extension to summarize the activities of the GHRSST Data Assembly and Systems Technical Advisory Group (DAS-TAG).

sea surface temperature (SST)↗

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 NTRS1991

The NASA Ocean Data System at the Jet Propulsion Laboratory

Global change studies require satellite oceanographic observations archived in an active data center. This paper describes the activities of an experimental active oceanographic data archive center specializing in distribution of high-level oceanographic data products produced by research oceanographers from satellite altimeter, scatterometer, and microwave and infrared radiometer measurements. Methods to encourage data sharing practices were developed. Services initiated to help oceanographers conduct research more effectively included rapid delivery of data, reprocessing data sets, subsetting of large data sets, and distribution of multiple data sets on a single medium.

Halpern, David↗

NASA NTRSDate not supplied

New Ways of Facilitating Improved Data Discovery and Access for NASA's Suborbital Earth Science Observations

NASA conducts field research in various Earth Science disciplines utilizing airborne and other non-satellite platforms to acquire in situ and remotely sensed observations indicative of physical processes across a range of scales. Field efforts are key in the development and validation of instruments and satellite algorithm refinements. The heterogeneous data, with a range of file formats, scales, and acquisition methods, support research in several science areas. NASA’s archive process assigns data products to discipline-oriented Distributed Active Archive Centers (DAACs) for stewardship. Over time, individual DAACs have developed tools for data browsing and serving disparate user bases. As science becomes more interdisciplinary, researchers need to incorporate observations from multiple campaigns, and multiple DAACs, into their work. Motivated in part by this shifting paradigm of needs, the Catalog of Archived Suborbital Earth Science Investigations (CASEI) was created. CASEI provides a single starting point to browse, search, and discover airborne and field data. Contextual metadata are organized and inter-linked allowing intuitive, integrated exploration across all NASA DAACs. Campaign science objectives, platform and instrument configurations, geographical details, geophysical concepts, and more are tracked in CASEI’s database, facilitating multi-parameter search, browse, and discovery of relevant data products. Researchers are able to directly access associated data products, via DOI links, regardless of the DAAC where they reside. Significant events, key time periods of high science interest within the longer-duration campaign effort, are also indicated and allow for a more efficient identification of critical data subsets. This presentation describes CASEI’s development, intensive metadata curation process, and demonstrates the web interface experience. Initial content metrics and plans for continued maintenance will also be discussed.

metadata↗

NASA NTRS2003

Data Access Tools And Services At The Goddard Distributed Active Archive Center (GDAAC)

As one of the largest providers of Earth Science data from the Earth Observing System, GDAAC provides the latest data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Solar Radiation and Climate Experiment (SORCE) data products via GDAAC's data pool (50TB of disk cache). In order to make this huge volume of data more accessible to the public and science communities, the GDAAC offers multiple data access tools and services: Open Source Project for Network Data Access Protocol (OPeNDAP), Grid Analysis and Display System (GrADS/DODS) (GDS), Live Access Server (LAS), OpenGlS Web Map Server (WMS) and Near Archive Data Mining (NADM). The objective is to assist users in retrieving electronically a smaller, usable portion of data for further analysis. The OPeNDAP server, formerly known as the Distributed Oceanographic Data System (DODS), allows the user to retrieve data without worrying about the data format. OPeNDAP is capable of server-side subsetting of HDF, HDF-EOS, netCDF, JGOFS, ASCII, DSP, FITS and binary data formats. The GrADS/DODS server is capable of serving the same data formats as OPeNDAP. GDS has an additional feature of server-side analysis. Users can analyze the data on the server there by decreasing the computational load on their client's system. The LAS is a flexible server that allows user to graphically visualize data on the fly, to request different file formats and to compare variables from distributed locations. Users of LAS have options to use other available graphics viewers such as IDL, Matlab or GrADS. WMS is based on the OPeNDAP for serving geospatial information. WMS supports OpenGlS protocol to provide data in GIs-friendly formats for analysis and visualization. NADM is another access to the GDAAC's data pool. NADM gives users the capability to use a browser to upload their C, FORTRAN or IDL algorithms, test the algorithms, and mine data in the data pool. With NADM, the GDAAC provides an environment physically close to the data source. NADM will benefit users with mining or offer data reduction algorithms by reducing large volumes of data before transmission over the network to the user.

Pham, Long↗

NASA NTRS2002

Burst Oscillation Periods from 4U 1636-53: A Constraint on the Binary Doppler Modulation

The burst oscillations seen during Type 1 X-ray bursts from low mass X-ray binaries (LMXB) typically evolve in period towards an asymptotic limit that likely reflects the spin of the underlying neutron star. If the underlying period is stable enough, measurement of it at different orbital phases may allow a detection of the Doppler modulation caused by the motion of the neutron star with respect to the center of mass of the binary system. Testing this hypothesis requires enough X-ray bursts and an accurate optical ephemeris to determine the binary phases at which they occurred. We present here a study of the distribution of asymptotic burst oscillation periods for a sample of 26 bursts from 4U 1636-53 observed with the Rossi X-ray Timing Explorer (RXTE). The burst sample includes both archival and proprietary data and spans more than 4.5 years. We also present new optical light curves of V801 Arae, the optical counterpart of 4U 1636-53, obtained during 1998-2001. We use these optical data to refine the binary period measured by Augusteijn et al. to 3.7931206(152) hours. We show that a subset of approx. 70% of the bursts form a tightly clustered distribution of asymptotic periods consistent with a period stability of approx. 1 x 10(exp -4). The tightness of this distribution, made up of bursts spanning more than 4 years in time, suggests that the underlying period is highly stable, with a time to change the period of approx. 3 x 10(exp 4) yr. This is comparable to similar numbers derived for X-ray pulsars. We investigate the period and orbital phase data for our burst sample and show that it is consistent with binary motion of the neutron star with v(sub ns) sin i < 38 and 50 km/s at 90 and 99% confidence, respectively. We use this limit as well as previous radial velocity data to constrain the binary geometry and component masses in 4U 1636-53. Our results suggest that unless the neutron star is significantly more massive than 1.4 solar masses the secondary is unlikely to have a mass as large as 0.36 solar masses, the mass estimated assuming it is a main sequence star which fills its Roche lobe. We show that a factor of 3 increase in the number of bursts with asymptotic period measurements should allow a detection of the neutron star velocity.

Giles, A. B.↗

DOE OSTI2026

QPatLib v1.0 — Measurement-based quantum simulation Pauli string unitary pattern collections

This Zenodo record accompanies the paper “Scalable Measurement-Based Quantum Simulation Patterns for Benchmarking” arXiv.2605.12502 and provides QPatLib v1.0 measurement-pattern datasets in human-readable JSONL together with a ZIP archive of OpenQASM 3.0 circuits used for validation and reproducibility. The patterns and circuits implement Pauli string unitaries for benchmark cases. Cases include all possible string combinations for less than 6 qubits and strings used in Hamiltonians for certain diatomic molecules for 6 or more qubits. Format: Each pattern_*.jsonl file is containins measurement patterns for all subsets for a given model/instance and subset strategy: it begins with a preamble containing model metadata, subset definitions, provenance, and (when feasible) full-pattern test results, followed by one pattern entry per subset. Each subset entry includes a required pattern_ascii field storing the measurement pattern in the measurement-calculus/Graphix standard with signal shifting, written left-to-right in the canonical order nodes → edges → measurements (with signal dependencies) → byproduct corrections (X/Z). The circuits are included as circuit_files.zip. Patterns in this record were validated against the corresponding circuits and checked for causal flow. Codes for generating these patterns can be found at QPatLib repository on Github

Graphix↗

NASA NTRS2004

Visualization, Analysis and Subsetting Tools for EOS Aura Data Products in HDF-EOS5

Aura data products are among the first to use the new version 5 of the Hierarchical Data Format for the Earth Observing System, or HDF-EOS5. This presentation discusses the common HDF-EOS5 file layout that is adopted for most of the EOS Aura standard data products. Details of the various tools that can be used to access, visualize and subset these data will also be provided. Aura, the NASA Earth Observing System's atmospheric chemistry mission, was successfully launched July 15, 2004. The Aura spacecraft includes four instruments: the High Resolution Dynamics Limb Sounder (HIRDLS), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Tropospheric Emission Spectrometer (TES). Data from the HIRDLS, MLS and OMI will be archived at the NASA Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC), while TES data will be archived at the NASA Langley Research Center DAAC. For more information see http://daac.gsfc.nasa.gov/.

Johnson, J.↗

NASA NTRS1996

Analysis of the access patterns at GSFC distributed active archive center

The Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) has been operational for more than two years. Its mission is to support existing and pre Earth Observing System (EOS) Earth science datasets, facilitate the scientific research, and test Earth Observing System Data and Information System (EOSDIS) concepts. Over 550,000 files and documents have been archived, and more than six Terabytes have been distributed to the scientific community. Information about user request and file access patterns, and their impact on system loading, is needed to optimize current operations and to plan for future archives. To facilitate the management of daily activities, the GSFC DAAC has developed a data base system to track correspondence, requests, ingestion and distribution. In addition, several log files which record transactions on Unitree are maintained and periodically examined. This study identifies some of the users' requests and file access patterns at the GSFC DAAC during 1995. The analysis is limited to the subset of orders for which the data files are under the control of the Hierarchical Storage Management (HSM) Unitree. The results show that most of the data volume ordered was for two data products. The volume was also mostly made up of level 3 and 4 data and most of the volume was distributed on 8 mm and 4 mm tapes. In addition, most of the volume ordered was for deliveries in North America although there was a significant world-wide use. There was a wide range of request sizes in terms of volume and number of files ordered. On an average 78.6 files were ordered per request. Using the data managed by Unitree, several caching algorithms have been evaluated for both hit rate and the overhead ('cost') associated with the movement of data from near-line devices to disks. The algorithm called LRU/2 bin was found to be the best for this workload, but the STbin algorithm also worked well.

Johnson, Theodore↗

NASA NTRS2010

The Atacama Cosmology Telescope: Physical Properties and Purity of a Galaxy Cluster Sample Selected Via the Sunyaev-Zel'Dovich Effect

We present optical and X-ray properties for the first confirmed galaxy cluster sample selected by the Sunyaev-Zel'dovich Effect from 148 GHz maps over 455 square degrees of sky made with the Atacama Cosmology Telescope. These maps. coupled with multi-band imaging on 4-meter-class optical telescopes, have yielded a sample of 23 galaxy clusters with redshifts between 0.118 and 1.066. Of these 23 clusters, 10 are newly discovered. The selection of this sample is approximately mass limited and essentially independent of redshift. We provide optical positions, images, redshifts and X-ray fluxes and luminosities for the full sample, and X-ray temperatures of an important subset. The mass limit of the full sample is around 8.0 x 10(exp 14) Stellar Mass. with a number distribution that peaks around a redshift of 0.4. For the 10 highest significance SZE-selected cluster candidates, all of which are optically confirmed, the mass threshold is 1 x 10(exp 15) Stellar Mass and the redshift range is 0.167 to 1.066. Archival observations from Chandra, XMM-Newton. and ROSAT provide X-ray luminosities and temperatures that are broadly consistent with this mass threshold. Our optical follow-up procedure also allowed us to assess the purity of the ACT cluster sample. Eighty (one hundred) percent of the 148 GHz candidates with signal-to-noise ratios greater than 5.1 (5.7) are confirmed as massive clusters. The reported sample represents one of the largest SZE-selected sample of massive clusters over all redshifts within a cosmologically-significant survey volume, which will enable cosmological studies as well as future studies on the evolution, morphology, and stellar populations in the most massive clusters in the Universe.

Menanteau, Felipe↗

NASA NTRSDate not supplied

Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗

NASA NTRS1998

Detection of Polar Stratospheric Clouds Using AVHRR Imagery

In recent years, the role of PSCs in the ozone depletion process has become better understood. PSCs provide the surfaces upon which heterogeneous reactions take place that affect the gas phase partitioning between active and reservoir chlorine and nitrogen species. Present methods of PSC detection include in situ measurements by lidar and various satellite-borne instruments such as the Stratospheric Aerosol Measurement II (SAM II) on the Nimbus 7 spacecraft, which produced PSC measurements from 1978 to 1994 and several instruments onboard the Upper Atmospheric Research Satellite (UARS) such as the Cryogenic Limb Array Etalon Spectrometer (CLAES) which provided measurements for 1991-1993. All of the PSC-detection methods devised so far have been hampered by incomplete sampling of the places and times in which PSCs are likely to form. There is a need to understand the climatology of PSCS, in particular the timing of their onset and duration, their vertical distribution, geographic extent, annual variability and responses to volcanic aerosol forcing. Poole and Pitts [1994] assembled a PSC climatology based on SAM II data, but this climatology is incomplete, as it is limited to the edge of the polar night due to the limitations of the solar occultation scan geometry. The Advanced Very High Resolution Radiometer (AVHRR) five- channel sensors onboard the NOAA polar-orbiting satellites have been collecting data over the polar regions continuously since 1979. These operational satellites provide unmatched coverage in space and time of both polar regions, but were not designed for the detection of optically-thin PSCS. However, the AVHRR data archive would be an invaluable source for the construction of a long-term climatology of PSCs if techniques can be developed and tested to detect PSCs in AVHRR data. In the last few years, the members of our group at San Francisco State University and NASA Ames Research Center have been engaged in the development of various PSC detection methods using AVHRR data. There is strong evidence that a subset of PSCS, those that are optically thick, can be readily identified in the AVHRR data set. Our group has also made significant progress in the identification of optically thinner PSCs using a variety of techniques.

Garcia, Oswaldo↗

NASA NTRS2000

Technical Report Series on the Boreal Ecosystem-Atmosphere Study (BOREAS) RSS-19 1994 CASI At-Sensor Radiance and Reflectance Images

The Remote Sensing Science (RSS)-19 team collected Compact Airborne Spectrographic Imager (CASI) images from the Chieftain Navaho aircraft in order to observe the seasonal change in the radiometric reflectance properties of the boreal forest landscape. CASI was deployed as a site-specific optical sensor during Boreal Ecosystem-Atmosphere Study (BOREAS) field campaigns. Image data were collected with CASI on 36 days during five field campaigns between February and September 1994, primarily at flux tower sites located at study sites near Thompson, Manitoba, and Prince Albert, Saskatchewan. A variety of CASI data collection strategies were used to meet the following scientific objectives: 1) canopy bidirectional reflectance, 2) canopy biochemistry, 3) spatial variability, and 4) estimates of up and downwelling Photosynthetically Active Radiation (PAR) and spectral albedo, as well as changes along transects across lakes and transects the Northern Study Area (NSA) and Southern Study Area (SSA). The images are stored as binary image files. A subset of the 1994 CASI acquisitions have been compressed and included on the BOREAS CD-ROM set. This subset includes three images for the NSA-OBS (Old Black Spruce) site on 06 Jun 94, 08 Aug 94, and 06 Sep 94, one image for the SSA-OBS site on 24 Jul 94; and one image for the NSA-Fen site on 08 Aug 94. The CASI imagery on the BOREAS CD-ROMs have been compressed using the Gzip program. The rest of the 1994 BOREAS CASI archive are not contained on the BOREAS CD-ROM set. Inventory listing files are supplied on the CD-ROM to inform users of the data that were collected. The RSS-19 1994 CASI images 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).

Miller, John↗

NASA NTRS1988

The GONG Data Reduction and Analysis System

Each of the six GONG observing stations will produce three, 16-bit, 256X256 images of the Sun every 60 sec of sunlight. These data will be transferred from the observing sites to the GONG Data Management and Analysis Center (DMAC), in Tucson, on high-density tapes at a combined rate of over 1 gibabyte per day. The contemporaneous processing of these data will produce several standard data products and will require a sustained throughput in excess of 7 megaflops. Peak rates may exceed 50 megaflops. Archives will accumulate at the rate of approximately 1 terabyte per year, reaching nearly 3 terabytes in 3 yr of observing. Researchers will access the data products with a machine-independent GONG Reduction and Analysis Software Package (GRASP). Based on the Image Reduction and Analysis Facility, this package will include database facilities and helioseismic analysis tools. Users may access the data as visitors in Tucson, or may access DMAC remotely through networks, or may process subsets of the data at their local institutions using GRASP or other systems of their choice. Elements of the system will reach the prototype stage by the end of 1988. Full operation is expected in 1992 when data acquisition begins.

Pintar, James A.↗