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NASA NTRS2010

JMISR INteractive eXplorer

MISR (Multi-angle Imaging SpectroRadiometer) INteractive eXplorer (MINX) is an interactive visualization program that allows a user to digitize smoke, dust, or volcanic plumes in MISR multiangle images, and automatically retrieve height and wind profiles associated with those plumes. This innovation can perform 9-camera animations of MISR level-1 radiance images to study the 3D relationships of clouds and plumes. MINX also enables archiving MISR aerosol properties and Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power along with the heights and winds. It can correct geometric misregistration between cameras by correlating off-nadir camera scenes with corresponding nadir scenes and then warping the images to minimize the misregistration offsets. Plots of BRF (bidirectional reflectance factor) vs. camera angle for points clicked in an image can be displayed. Users get rapid access to map views of MISR path and orbit locations and overflight dates, and past or future orbits can be identified that pass over a specified location at a specified time. Single-camera, level-1 radiance data at 1,100- or 275- meter resolution can be quickly displayed in color using a browse option. This software determines the heights and motion vectors of features above the terrain with greater precision and coverage than previous methods, based on an algorithm that takes wind direction into consideration. Human interpreters can precisely identify plumes and their extent, and wind direction. Overposting of MODIS thermal anomaly data aids in the identification of smoke plumes. The software has been used to preserve graphical and textural versions of the digitized data in a Web-based database.

Nelson, David L.↗
NASA NTRS1995

SPE (trademark) Oxygen Generator Assembly (OGA). (Refurbishment of the technology demonstrator LFSPE oxygen generation subsystem)

The SPE Oxygen Generator Assembly (OGA) has been modified to correct operational deficiencies present in the original system, and to effect changes to the system hardware and software such that its operating conditions are consistent with the latest configuration requirements for the International Space Station Alpha (ISSA). The effectiveness of these changes has recently been verified through a comprehensive test program which saw the SPE OGA operate for over 740 hours at various test conditions, including over 690 hours, or approximately 460 cycles, simulating the orbit of the space station. This report documents the changes made to the SPE OGA, presents and discusses the test results from the acceptance test program, and provides recommendations for additional development activities pertinent to evolution of the SPE OGA to a flight configuration. Copies of the test data from the acceptance test program are provided with this report on 3.5 inch diskettes in self-extracting archive files.

Roy, Robert J.↗
NASA NTRS2010

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss the science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

Twicken, Joseph D.↗
NASA NTRS2010

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) Science Processing Pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

photocenter↗
NASA NTRS1990

NAE Twin Otter operations in FIFE 1989

During the summer of 1989, the National Aeronautical Establishment (Canada) Twin Otter Atmospheric Research Aircraft was flow in support of the NASA sponsored First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment called FIFE-89. Airborne measurements of the fluxes of heat, momentum, water vapor and carbon dioxide were made during 16 flow-altitude flights over the FIFE project area in central Kansas. The Twin Otter operations in FIFE are documented and details are included on the instrumentation, software, flight procedures, atmospheric conditions and analysis methods. Comparisons of Twin Otter measured fluxes are made with those determined at several surface sites and with those made by other instrumented aircraft in the FIFE-87 measurements. Airborne flux measurements are related to run length, altitude, and environmental parameters such as vegetation type, temperature, and wind speed. One night flight was run in an attempt to measure the respiration component of the CO2 flux. The use of aircraft was studied for regional observations of fluxes and to relate these to satellite radiance measurements. Run average data are presented for all 285 flux runs flown by the Twin Otter in FIFE-89. This should serve as as a working reference for scientists utilizing Twin Otter data either directly of through the FIFE data archive.

Macpherson, J. I.↗
NASA NTRS2008

Displaying Composite and Archived Soundings in the Advanced Weather Interactive Processing System

This presentation describes work done by the Applied Meteorology Unit (AMU) to add composite soundings to the Advanced Weather Interactive Processing System (AWIPS). This allows National Weather Service (NWS) forecasters to compare the current atmospheric state with climatology. In a previous task, the AMU created composite soundings for four rawinsonde observation stations in Florida, for each of eight flow regimes. The composite soundings were delivered to the NWS Melbourne (MLB) office for display using the NSHARP software program. NWS MLB requested that the AMU make the composite soundings available for display in AWIPS. The AMU first created a procedure to customize AWIPS so composite soundings could be displayed. A unique four-character identifier was created for each of the 32 composite soundings. The AMIU wrote a Tool Command Language/Tool Kit (TclITk) software program to convert the composite soundings from NSHARP to Network Common Data Form (NetCDF) format. The NetCDF files were then displayable by AWIPS.

Barrett, Joe H., III↗
NASA NTRS1992

Managing an archive of weather satellite images

The author's experiences of building and maintaining an archive of hourly weather satellite pictures at NOAO are described. This archive has proven very popular with visiting and staff astronomers - especially on windy days and cloudy nights. Given access to a source of such pictures, a suite of simple shell and IRAF CL scripts can provide a great deal of robust functionality with little effort. These pictures and associated data products such as surface analysis (radar) maps and National Weather Service forecasts are updated hourly at anonymous ftp sites on the Internet, although your local Atsmospheric Sciences Department may prove to be a more reliable source. The raw image formats are unfamiliar to most astronomers, but reading them into IRAF is straightforward. Techniques for performing this format conversion at the host computer level are described which may prove useful for other chores. Pointers are given to sources of data and of software, including a package of example tools. These tools include shell and Perl scripts for downloading pictures, maps, and forecasts, as well as IRAF scripts and host level programs for translating the images into IRAF and GIF formats and for slicing & dicing the resulting images. Hints for displaying the images and for making hardcopies are given.

Seaman, R. L.↗
NASA NTRS2006

Earth Observing System Data Gateway

The Earth Observing System Data Gateway (EDG) software provides a "one-stop-shopping" standard interface for exploring and ordering Earth-science data stored at geographically distributed sites. EDG enables a user to do the following: 1) Search for data according to high-level criteria (e.g., geographic location, time, or satellite that acquired the data); 2) Browse the results of a search, viewing thumbnail sketches of data that satisfy the user s criteria; and 3) Order selected data for delivery to a specified address on a chosen medium (e.g., compact disk or magnetic tape). EDG consists of (1) a component that implements a high-level client/server protocol, and (2) a collection of C-language libraries that implement the passing of protocol messages between an EDG client and one or more EDG servers. EDG servers are located at sites usually called "Distributed Active Archive Centers" (DAACs). Each DAAC may allow access to many individual data items, called "granules" (e.g., single Landsat images). Related granules are grouped into collections called "data sets." EDG enables a user to send a search query to multiple DAACs simultaneously, inspect the resulting information, select browseable granules, and then order selected data from the different sites in a seamless fashion.

Pfister, Robin↗
NASA NTRSDate not supplied

Origami-based Composite Space Structures

The main objective of my internship was working on developing a new type of deployable composite for space structures and new method of deployment via use of origami, composites, UV curing resins, and shape memory polymers. My role in the project was to collect an initial literature survey on the subject including origami, the history of deployable space structures, previous issues and problems faced in the field, previous and current research being done on the structural aspect as well as the materials aspect of the subject. I presented this information to our team, where we discussed and determined our research focus and project design specs. We have been making or will make decisions on the project’s purpose, material, origami type, manufacturing method, and testing methods. I am now in charge of the protype design as we enter the design stage of our research. I am using PTC Creo software to design the structural aspects of the first protype so that we can begin small scale testing. I will perform data analysis in order to review the results with our team, so we can make the next design decisions regarding changes or iterations of the design. We hope to renew this project in the next fiscal year in order to increase the TRL of the project so that it can eventually be used in multiple functions in space such as the construction of lunar habitats. In just my brief time with NASA, I have gained so much personally and professionally. I developed my ability to search through and narrow down information when doing research. In the weekly meetings I practiced presenting information to my peers and superiors, and, just as importantly, discussing and adapting to what we were learning. I acquired experience in using technology to my advantage including remote work, new software like PTC Creo, NASA archives, and connecting with others beyond my team to gain help. I enjoyed the immense resource of knowledge that my mentors had to offer, and that they gave me a large amount of responsibility in this research. I truly felt like I was contributing to something bigger than myself and understood how directly I was involved in NASA’s work. This internship has further cemented my love for space and desire to continue in the field. I have a better understanding of the research and development process and am now considering joining a research lab with my university next year.

Composite↗
NASA NTRS2004

SAMZ: Satellite-Derived Management Zones

The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multi-year crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.

Source record↗
NASA NTRS2005

Satellite-Derived Management Zones

The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth-orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops, and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop-production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without the need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multiyear crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.

Lepoutre, Damien↗
NASA NTRS2011

Telemetry and Science Data Software System

The Telemetry and Science Data Software System (TSDSS) was designed to validate the operational health of a spacecraft, ease test verification, assist in debugging system anomalies, and provide trending data and advanced science analysis. In doing so, the system parses, processes, and organizes raw data from the Aquarius instrument both on the ground and while in space. In addition, it provides a user-friendly telemetry viewer, and an instant pushbutton test report generator. Existing ground data systems can parse and provide simple data processing, but have limitations in advanced science analysis and instant report generation. The TSDSS functions as an offline data analysis system during I&T (integration and test) and mission operations phases. After raw data are downloaded from an instrument, TSDSS ingests the data files, parses, converts telemetry to engineering units, and applies advanced algorithms to produce science level 0, 1, and 2 data products. Meanwhile, it automatically schedules upload of the raw data to a remote server and archives all intermediate and final values in a MySQL database in time order. All data saved in the system can be straightforwardly retrieved, exported, and migrated. Using TSDSS s interactive data visualization tool, a user can conveniently choose any combination and mathematical computation of interesting telemetry points from a large range of time periods (life cycle of mission ground data and mission operations testing), and display a graphical and statistical view of the data. With this graphical user interface (GUI), the data queried graphs can be exported and saved in multiple formats. This GUI is especially useful in trending data analysis, debugging anomalies, and advanced data analysis. At the request of the user, mission-specific instrument performance assessment reports can be generated with a simple click of a button on the GUI. From instrument level to observatory level, the TSDSS has been operating supporting functional and performance tests and refining system calibration algorithms and coefficients, in sync with the Aquarius/SAC-D spacecraft. At the time of this reporting, it was prepared and set up to perform anomaly investigation for mission operations preceding the Aquarius/SAC-D spacecraft launch on June 10, 2011.

Bates, Lakesha↗
NASA NTRS2010

Presearch Data Conditioning in the Kepler Science Operations Center Pipeline

We describe the Presearch Data Conditioning (PDC) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this component are to correct systematic and other errors, remove excess flux due to aperture crowding, and condition the raw flux light curves for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) targets across the focal plane array. Long cadence corrected flux light curves are subjected to a transiting planet search in a subsequent pipeline module. We discuss the science algorithms for long and short cadence PDC: identification and correction of unexplained (i.e., unrelated to known anomalies) discontinuities; systematic error correction; and excess flux removal. We discuss the propagation of uncertainties from raw to corrected flux. Finally, we present examples of raw and corrected flux time series for flight data to illustrate PDC performance. Corrected flux light curves produced by PDC are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and will be made available to the general public in accordance with the NASA/Kepler data release policy.

Twicken, Joseph D.↗
NASA NTRS2005

Custom Sky-Image Mosaics from NASA's Information Power Grid

yourSkyG is the second generation of the software described in yourSky: Custom Sky-Image Mosaics via the Internet (NPO-30556), NASA Tech Briefs, Vol. 27, No. 6 (June 2003), page 45. Like its predecessor, yourSkyG supplies custom astronomical image mosaics of sky regions specified by requesters using client computers connected to the Internet. Whereas yourSky constructs mosaics on a local multiprocessor system, yourSkyG performs the computations on NASA s Information Power Grid (IPG), which is capable of performing much larger mosaicking tasks. (The IPG is high-performance computation and data grid that integrates geographically distributed 18 NASA Tech Briefs, September 2005 computers, databases, and instruments.) A user of yourSkyG can specify parameters describing a mosaic to be constructed. yourSkyG then constructs the mosaic on the IPG and makes it available for downloading by the user. The complexities of determining which input images are required to construct a mosaic, retrieving the required input images from remote sky-survey archives, uploading the images to the computers on the IPG, performing the computations remotely on the Grid, and downloading the resulting mosaic from the Grid are all transparent to the user

Jacob, Joseph↗
NASA NTRSDate not supplied

New developments in space radiation research at NASA: Annotating data using a novel radiation biology ontology

Like many interdisciplinary sciences, data producers and consumers in the field of radiation biology often use a wide variety of terminology to describe their experiments and data. Furthermore, space systems and technologies are rapidly evolving, and a shared understanding and common terminology for these is also lacking. The efficiency of research organizations can be enhanced by standardizing metadata through the use of knowledge resources like ontologies. Employing a sophisticated model such as a formal ontology to standardize metadata enables automated data acquisition processes and supports more complete, accurate meta-analysis through more efficient and complete data discovery and retrieval, particularly when using multiple data sources. Thus, we developed the Radiation Biology Ontology (RBO) in order to improved radiation biology metadata uniformity and transparency. We used open-source software (the Ontology Development Kit, Protégé and WebProtégé) and worked within the OBO Foundry framework, which includes a set of ontology development principles and practices for ontology consistency, uniformity, and accountability. The RBO has now been incorporated into two radiation research data repositories, NASA’s GeneLab omics database (https://genelab.nasa.gov), and the European Commission STORE database (https://www.storedb.org/). Continuous build integration tools allowed our international RBO collaboration to be more efficient and focus its efforts on semantic model design. Currently, the RBO contains over 300 annotated classes and individuals specific to the study of radiation on biological systems, as well as imports of many additional classes from other OBO Foundry ontologies that relate to and/or provide context for these RBO entities. We publish the RBO through the OBO Foundry, so that it is available for browsing, download, and querying through NCBI Bioportal web site and application programming interface. The NASA Ames Life Science Data Archive (ALSDA) is also in the process of adopting use of the RBO, taking NASA one step closer to a knowledge-based system for space biology data. It is our hope that the global communities of radiation research Investigators, data curators and data analysts can similarly leverage the RBO and will contribute to its further development.

radiation↗
NASA NTRS2002

MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring

Development and evaluation of Intensive Care Unit (ICU) decision-support systems would be greatly facilitated by the availability of a large-scale ICU patient database. Following our previous efforts with the MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database, we have leveraged advances in networking and storage technologies to develop a far more massive temporal database, MIMIC II. MIMIC II is an ongoing effort: data is continuously and prospectively archived from all ICU patients in our hospital. MIMIC II now consists of over 800 ICU patient records including over 120 gigabytes of data and is growing. A customized archiving system was used to store continuously up to four waveforms and 30 different parameters from ICU patient monitors. An integrated user-friendly relational database was developed for browsing of patients' clinical information (lab results, fluid balance, medications, nurses' progress notes). Based upon its unprecedented size and scope, MIMIC II will prove to be an important resource for intelligent patient monitoring research, and will support efforts in medical data mining and knowledge-discovery.

NASA Discipline Cardiopulmonary↗
NASA NTRS1994

Windshear certification data base for forward-look detection systems

Described is an introduction to a comprehensive database that is to be used for certification testing of airborne forward-look windshear detection systems. The database was developed by NASA Langley Research Center, at the request of the Federal Aviation Administration (FAA), to support the industry initiative to certify and produce forward-looking windshear detection equipment. The database contains high-resolution three-dimensional fields for meteorological variables that may be sensed by forward-looking systems. The database is made up of seven case studies that are generated by the Terminal Area Simulation System, a state-of-the-art numerical system for the realistic modeling of windshear phenomena. The selected cases contained in the certification documentation represent a wide spectrum of windshear events. The database will be used with vendor-developed sensor simulation software and vendor-collected ground-clutter data to demonstrate detection performance in a variety of meteorological conditions using NASA/FAA pre-defined path scenarios for each of the certification cases. A brief outline of the contents and sample plots from the database documentation are included. These plots show fields of hazard factor, or F-factor (Bowles 1990), radar reflectivity, and velocity vectors on a horizontal plane overlayed with the applicable certification paths. For the plot of the F-factor field the region of 0.105 and above signify an area of hazardous, performance decreasing windshear, while negative values indicate regions of performance increasing windshear. The values of F-factor are based on 1-Km averaged segments along horizontal flight paths, assuming an air speed of 150 knots (approx. 75 m/s). The database has been released to vendors participating in the certification process. The database and associated document have been transferred to the FAA for archival storage and distribution.

Switzer, George F.↗
NASA NTRS2015

When the Sky Falls: Performing Initial Assessments of Bright Atmospheric Events

The 2013 Chelyabinsk super bolide was the first "significant" impact event to occur in the age of social media and 24 hour news. Scientists, used to taking many days or weeks to analyze fireball events, were hard pressed to meet the immediate demands (within hours) for answers from the media, general public, and government officials. Fulfilling these requests forced many researchers to exploit information available from various Internet sources - videos were downloaded from sites like Youtube, geolocated via Google Street View, and quickly analyzed with improvised software; Twitter and Facebook were scoured for eyewitness accounts of the fireball and reports of meteorites. These data, combined with infrasound analyses, enabled a fairly accurate description of the Chelyabinsk event to be formed within a few hours; in particular, any relationship to 2012 DA14 (which passed near Earth later that same day) was eliminated. Results of these analyses were quickly disseminated to members of the NEO community for press conferences and media interviews. Despite a few minor glitches, the rapid initial assessment of Chelyabinsk was a triumph, permitting the timely conveyance of accurate information to the public and the incorporation of social media into fireball analyses. Beginning in 2008, the NASA Meteoroid Environments Office, working in cooperation with Western's Meteor Physics Group, developed processes and software that permit quick characterization - mass, trajectory, and orbital properties - of fireball events. These tools include automated monitoring of Twitter to establish the time of events (the first tweet is usually no more than a few seconds after the fireball), mining of Youtube and all sky camera web archives to locate videos suitable for analyses, use of Google Earth and Street View to geolocate the video locations, and software to determine the fireball trajectory and object orbital parameters, including generation of animations suitable for popular media and presentations. This presentation will give a short description of the characterization procedure and show applications of the tools, which have become vital to answering the question of "What was that bright light in the sky?" in the post-Chelyabinsk, 24/7 news world.

Cooke, William J.↗