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At least 685 records · Page 38

Pancam Multispectral and APXS Chemical Examination of Rocks and Soils in Marathon Valley and Points South Along the Rim of Endeavour Crater

The Mars Exploration Rover Opportunity has concluded its exploration of Marathon Valley, a 100-meter-wide valley in the western rim of the 22-kilometer-diameter Endeavour crater. Orbital observations from CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) indicated the presence of Fe smectites in Marathon Valley. Since leaving the valley, Opportunity has been traversing along the inner rim of the crater, and currently towards the outer rim. This presentation describes the Pancam 430 to 1009 nanometer (VNIR - Visible and Near Infared) multispectral reflectance and APXS (Alpha Particle X-ray Spectrometer) chemical compositions of rock and soil units observed during the latter portions of the Marathon Valley campaign on the Knudson Ridge area and observations of those materi-als along the traverse to the south. Full Pancam spectral coverage of rock targets consists of 13 filter (13f) data collections with 11 spectrally unique channels with data processing. Data were examined using spectral parameters, decorrelation stretch composites, and spectral mixture analysis. Note that color terms used here refer to colors in various false-color renditions, not true colors. The APXS determines major and select trace element compositions of targets.

Farrand, W. H.↗

Total and Spectral Solar Irradiance Sensor (TSIS) Project Status

TSIS-1 studies the Sun's energy input to Earth and how solar variability affects climate. TSIS-1 will measure both the total amount of light that falls on Earth, known as the total solar irradiance (TSI), and how that light is distributed among ultraviolet, visible and infrared wavelengths, called solar spectral irradiance (SSI). TSIS-1 will provide the most accurate measurements of sunlight and continue the long-term climate data record. TSIS-1 includes two instruments: the Total Irradiance Monitor (TIM) and the Spectral Irradiance Monitor (SIM), integrated into a single payload on the International Space Station (ISS). The TSIS-1 TIM and SIM instruments are upgraded versions of the two instruments that are flying on the Solar Radiation and Climate Experiment (SORCE) mission launched in January 2003. NASA Goddard's TSIS project responsibilities include project management, system engineering, safety and mission assurance, and engineering oversight for TSIS-1. TSIS-1 was installed on the International Space Station in December 2017. At the end of the 90-day commissioning phase, responsibility for TSIS-1 operations transitions to the Earth Science Mission Operations (ESMO) project at Goddard for its 5-year operations. NASA contracts with the University of Colorado Laboratory for Atmospheric and Space Physics (LASP) for the design, development and testing of TSIS-1, support for ISS integration, science operations of the TSIS-1 instrument, data processing, data evaluation, calibration and delivery to the Goddard Earth Science Data and Information Services Center (GES DISC).

TSIS↗

Lessons Learned and Cost Analysis of Hosting a Full Stack Open Data Cube (ODC) Application on the Amazon Web Services (AWS)

The Open Data Cube (ODC) initiative, with support from the Committee on Earth Observation Satellites (CEOS) System Engineering Office (SEO) has developed a state-of-the-art suite of software tools and products to facilitate the analysis of Earth Observation data. This paper presents a short summary and cost analysis of our experience using Amazon Web Services (AWS) to host one such software product, the CEOS Data Cube (CDC) web-based User Interface (UI). In order to provide adaptability, flexibility, scalability, and robustness, we leverage widely-adopted and well-supported technologies such as the Django web framework and the AWS Cloud platform. The UI has empowered users by providing features that assist with streamlining data preparation, data processing, data visualization, and the sub-setting of Analysis Ready Data (ARD) products in order to achieve a wide variety of Earth imaging objectives.

Rizvi, Syed R.↗

Vortex information display system program description manual

A vortex information display system is described which provides flexible control through system-user interaction for collecting wing-tip-trailing vortex data, processing this data in real time, displaying the processed data, storing raw data on magnetic tape, and post processing raw data. The data is received from two asynchronous laser Doppler velocimeters (LDV's) and includes position, velocity, and intensity information. The raw data is written onto magnetic tape for permanent storage and is also processed in real time to locate vortices and plot their positions as a function of time. The interactive capability enables the user to make real time adjustments in processing data and provides a better definition of vortex behavior. Displaying the vortex information in real time produces a feedback capability to the LDV system operator allowing adjustments to be made in the collection of raw data. Both raw data and processing can be continually upgraded during flyby testing to improve vortex behavior studies. The post-analysis capability permits the analyst to perform in-depth studies of test data and to modify vortex behavior models to improve transport predictions.

Conway, R.↗

The problem of the man-space data interface during computer processing of data

The necessity is shown for data output at different processing stages to man, taking into account the processing level, the output objective, and the user. The use of the phototelegraph I/O computer device for this purpose is considered in detail, and several examples are given. It is shown that the type of output (shaded of halftone graphs), the scales, the compression, and the mutual position of the data are selected on the basis of the character of the data displayed.

Mamotko, Z. N.↗

Laying The Foundations for FAIR-ER Science: ISA And LSDA Data Submission Process in NASA’s Evolving Data Management Environment

The Life Sciences Data Archive (LSDA) archives data resulting from research on the effects of spaceflight on humans and the development of countermeasures to mitigate spaceflight hazards. Archivists work with researchers to ensure that unique and high value data products and their metadata are preserved and managed to support current and future research. Currently, LSDA is updating its procedures and data submission requirements in response to the evolving data preservation environment at NASA. LSDA is implementing best practices for research data management through the establishment of clear data submission guidelines, integration of the FAIR (Findability, Accessibility, Interoperability, Reusability) principles, and use of the ISA (Investigation, Study, Assay) research metadata framework for data discoverability and transparency into the data management processes. These changes directly impact LSDA’s requirements for research data submissions. The newly revised Research Data Submission Agreement (RDSA), formerly the Data Submission Agreement (DSA), introduces ISA-compatible metadata collection standards to LSDA’s process. Adherence to LSDA’s data submission guidelines enhances the FAIR-ness of the repository’s collections for future users. This presentation will discuss (1) how submission of research data and associated metadata are impacted by current data management policies, (2) benefits of the adoption of FAIR principles and the ISA metadata framework for retrospective studies utilizing existing LSDA datasets and historic data collections, and (3) the support LSDA will provide to researchers during this transition.

Data submission↗

Laying the Foundations for FAIR-er Science: ISA and the LSDA Data Submission Process in NASA's Evolving Data Management Environment

The Life Sciences Data Archive (LSDA) archives data resulting from research on the effects of spaceflight on humans and the development of countermeasures to mitigate spaceflight hazards. Archivists work with researchers to ensure that unique and high value data products and their metadata are preserved and managed to support current and future research. Currently, LSDA is updating its procedures and data submission requirements in response to the evolving data preservation environment at NASA. LSDA is implementing best practices for research data management through the establishment of clear data submission guidelines, integration of the FAIR (Findability, Accessibility, Interoperability, Reusability) principles, and use of the ISA (Investigation, Study, Assay) research metadata framework for data discoverability and transparency into the data management processes. These changes directly impact LSDA’s requirements for research data submissions. The newly revised Research Data Submission Agreement (RDSA), formerly the Data Submission Agreement (DSA), introduces ISA-compatible metadata collection standards to LSDA’s process. Adherence to LSDA’s data submission guidelines enhances the FAIR-ness of the repository’s collections for future users. This presentation will discuss (1) how submission of research data and associated metadata are impacted by current data management policies, (2) benefits of the adoption of FAIR principles and the ISA metadata framework for retrospective studies utilizing existing LSDA datasets and historic data collections, and (3) the support LSDA will provide to researchers during this transition.

LSDA↗

Processing Raw HST Data With Up-to-Date Calibration Data

On-the-Fly Reprocessing (OTFR) is a collection of data-processing routines that work within the context of the Hubble Space Telescope (HST) pipeline data-flow system. The purpose served by OTFR is to generate, on demand, scientifically useful data products from raw HST data stored in an archive. First, on the basis of the requested final data products, OTFR retrieves the corresponding sets of raw data from the archives. Next, OTFR processes the raw data sets to remove artifacts and to establish proper header and other template information. Finally, the calibration routines appropriate to the specific data sets are invoked to produce the requested data products, and the data products are released to an archive distribution system for transmission to the requesting party. OTFR offers two notable advantages: (1) Inasmuch as calibrated data occupy about 8 times as much storage space as do raw data, by obviating storage of calibrated data, OTFR reduces the storage capacity needed by the archive; and (2) the calibration routines can be updated to give requesters the benefit of the most recent calibrations.

Miller, Warren↗

NASA GeneLab: Open Science for Life in Space

The NASA GeneLab project (genelab.nasa.gov) seeks to get the most from space-relevant biology experiments by providing and maintaining a public database consisting of DNA, RNA, protein, and metabolite data from spaceflight experiments. Since these types of data, referred to as omics data, are difficult to understand for non-bioinformaticians, the GeneLab data processing team works with the scientific community to develop methods to process these data. The processed data found on GeneLab reveals information about which genes are turned on and turned off in the space environment, which helps us understand how space changes our biology and how we can best mitigate these effects to travel deeper into space.

Jonathan Oribello↗

Wind information display system user's manual

The Wind Information Display System (WINDS) provides flexible control through system-user interaction for collecting wind shear data, processing this data in real time, displaying the processed data, storing raw data on magnetic tapes, and post-processing raw data. The data are received from two asynchronous laser Doppler velocimeters (LDV's) and include position, velocity and intensity information. The raw data is written onto magnetic tape for permanent storage and is also processed in real time to depict wind velocities in a given spacial region.

Roe, J.↗

Investigations in adaptive processing of multispectral data

Adaptive data processing procedures are applied to the problem of classifying objects in a scene scanned by multispectral sensor. These procedures show a performance improvement over standard nonadaptive techniques. Some sources of error in classification are identified and those correctable by adaptive processing are discussed. Experiments in adaptation of signature means by decision-directed methods are described. Some of these methods assume correlation between the trajectories of different signature means; for others this assumption is not made.

Kriegler, F. J.↗

Earth Science System of the Future: Observing, Processing, and Delivering Data Products Directly to Users

Advancement of our predictive capabilities will require new scientific knowledge, improvement of our modeling capabilities, and new observation strategies to generate the complex data sets needed by coupled modeling networks. New observation strategies must support remote sensing from a variety of vantage points and will include "sensorwebs" of small satellites in low Earth orbit, large aperture sensors in Geostationary orbits, and sentinel satellites at L1 and L2 to provide day/night views of the entire globe. Onboard data processing and high speed computing and communications will enable near real-time tailoring and delivery of information products (i.e., predictions) directly to users.

Crisp, David↗

Simplifying NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user.

Liu, Zhong↗

Comprehensive analysis of Shuttle Orbiter leeside surface infrared imagery obtained during atmospheric entry

The thermographic analysis techniques developed for processing of data from the Shuttle Infrared Leeside Temperature Sensing (SILTS) experiment are discussed. The SILTS experiment will obtain high-spatial-resolution infrared images of the leeside of the Space Shuttle Orbiter during atmospheric entry by means of a scanning infrared radiometer located atop the orbiter's vertical stabilizer. Comprehensive analysis of the SILTS thermography requires accurate consideration of all those factors (such as geometry of the observed surfaces, local surface emissivity, solar radiation, and other potential sources of image degradation) which may potentially affect the output of the infrared radiometer. An overview of the entire data processing procedure and brief descriptions of the data processing algorithms are presented.

Myrick, D. L.↗

Standardizing Interfaces for External Access to Data and Processing for the NASA Ozone Product Evaluation and Test Element (PEATE)

NASA's traditional science data processing systems have focused on specific missions, and providing data access, processing and services to the funded science teams of those specific missions. Recently NASA has been modifying this stance, changing the focus from Missions to Measurements. Where a specific Mission has a discrete beginning and end, the Measurement considers long term data continuity across multiple missions. Total Column Ozone, a critical measurement of atmospheric composition, has been monitored for'decades on a series of Total Ozone Mapping Spectrometer (TOMS) instruments. Some important European missions also monitor ozone, including the Global Ozone Monitoring Experiment (GOME) and SCIAMACHY. With the U.S.IEuropean cooperative launch of the Dutch Ozone Monitoring Instrument (OMI) on NASA Aura satellite, and the GOME-2 instrumental on MetOp, the ozone monitoring record has been further extended. In conjunction with the U.S. Department of Defense (DoD) and the National Oceanic and Atmospheric Administration (NOAA), NASA is now preparing to evaluate data and algorithms for the next generation Ozone Mapping and Profiler Suite (OMPS) which will launch on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) in 2010. NASA is constructing the Science Data Segment (SDS) which is comprised of several elements to evaluate the various NPP data products and algorithms. The NPP SDS Ozone Product Evaluation and Test Element (PEATE) will build on the heritage of the TOMS and OM1 mission based processing systems. The overall measurement based system that will encompass these efforts is the Atmospheric Composition Processing System (ACPS). We have extended the system to include access to publically available data sets from other instruments where feasible, including non-NASA missions as appropriate. The heritage system was largely monolithic providing a very controlled processing flow from data.ingest of satellite data to the ultimate archive of specific operational data products. The ACPS allows more open access with standard protocols including HTTP, SOAPIXML, RSS and various REST incarnations. External entities can be granted access to various modules within the system, including an extended data archive, metadata searching, production planning and processing. Data access is provided with very fine grained access control. It is possible to easily designate certain datasets as being available to the public, or restricted to groups of researchers, or limited strictly to the originator. This can be used, for example, to release one's best validated data to the public, but restrict the "new version" of data processed with a new, unproven algorithm until it is ready. Similarly, the system can provide access to algorithms, both as modifiable source code (where possible) and fully integrated executable Algorithm Plugin Packages (APPs). This enables researchers to download publically released versions of the processing algorithms and easily reproduce the processing remotely, while interacting with the ACPS. The algorithms can be modified allowing better experimentation and rapid improvement. The modified algorithms can be easily integrated back into the production system for large scale bulk processing to evaluate improvements. The system includes complete provenance tracking of algorithms, data and the entire processing environment. The origin of any data or algorithms is recorded and the entire history of the processing chains are stored such that a researcher can understand the entire data flow. Provenance is captured in a form suitable for the system to guarantee scientific reproducability of any data product it distributes even in cases where the physical data products themselves have been deleted due to space constraints. We are currently working on Semantic Web ontologies for representing the various provenance information. A new web site focusing on consolidating informaon about the measurement, processing system, and data access has been established to encourage interaction with the overall scientific community. We will describe the system, its data processing capabilities, and the methods the community can use to interact with the standard interfaces of the system.

Tilmes, Curt A.↗

Onboard System Processes SAR Data

Aircraft Flight Correlator (AFC) computing system, mounted with AIRSAR synthetic-aperture-radar (SAR) system, supplements recording and postflight analysis, processing portion of data in real or nearly real time to provide imagery for rapid evaluation. Facilitates diagnosis of SAR equipment or adjustment of parameters of experiment. Operates in two modes: "quick-look" mode, data processed in 10 minutes into high-resolution image; and "real-time" mode, data processed in real time to reduced resolution. Also used as aid to navigation.

Carande, Richard E.↗