SEARCH · Search NASA

Results for “Open Source Mapping”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

NASA NTRS1995

The double oval UV auroral distribution. 1: Implications for the mapping of auroral arcs

During the later stages of the auroral substorm the luminosity distribution frequently resembles a double oval, one oval lying poleward of the normal or main UV auroral oval. We interpret the double oval morphology as being due to the plasma sheet boundary layer becoming active in the later stages of the substorm process. If the disturbance engulfs the nightside low-latitude boundary layers, then the double oval configuration extends into the dayside ionospheric region. The main UV oval is associated with the inner portion of the central plasma sheet and can rapidly change its auroral character from being diffuse to discrete. This transition is associated with the substorm process and is fundamental to understanding the near-Earth character of substorm onset. On the other hand, the poleward arc system in the nightside ionosphere occurs adjacent to or near the open-closed field line boundary. This system activates at the end of the optical expansion phase and is a part of the recovery phase configuration in substorms where it occurs. These two source regions for nightside discrete auroral arcs are important in resolving the controversy concerning the mapping of arcs to the magnetosphere. The dayside extension of this double oval configuration is also investigated and shows particle signatures which differ considerably from those on the nightside giving clues to the magnetospheric source regions of the aurora in the two local time sectors. Near-Earth substorm onsets are shown to be coupled to processes occurring much further tailward and indicate the importance of understanding the temporal development of features within the double oval. Using 'variance images,' a new technqiue for the investigation of these dynamics is outlined.

Elphinstone, R. D.↗

NASA NTRS2017

A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Nets convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign. Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

NeMO=NET↗

NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

NASA NTRS2006

Mapping Weathering and Alteration Minerals in Virginia City, Nevada with AVIRIS and HyperSpecTIR

Situated on the east side of the Virginia Range, Virginia City (Figure 1) is the home of the historic Comstock mining district and was mined as a source of Au and Ag between 1859 and the 1960's, with numerous underground workings and small open pit operations. The Virginia Range consists mostly of Oligocene to Miocene volcanic rocks that overlie Mesozoic metamorphic rocks (Mzvs) and Cretaceous granodiorite (Kgd). Andesite to dacite flows, breccias and intrusives of the Alta Formation (Ta) (18-15 Ma) (Hudson, 2003) are overlain by intermediate volcanic, volcaniclastic and locally intrusive rocks of the Kate Peak Formation (Tk) (14.7-12 Ma) (Vikre, 1998; Hudson, 2003). Contemporaneous with the Alta Formation was the intrusion of the Davidson diorite (1 5.2 Ma) (Castor et al., 2002), which forms the bulk of Mt. Davidson just west of the town site.

HyperSpecTIR (HST)↗

NASA NTRS1985

Focal plane optics in far-infrared and submillimeter astronomy

The construction of airborne observatories, high mountain-top observatories, and space observatories designed especially for infrared and submillimeter astronomy has opened fields of research requiring new optical techniques. A typical far-IR photometric study involves measurement of a continuum spectrum in several passbands between approx 30 microns and 1000 microns and diffraction-limited mapping of the source. At these wavelengths, diffraction effects strongly influence the design of the field optics systems which couple the incoming flux to the radiation sensors (cold bolometers). The Airy diffraction disk for a typical telescope at submillimeter wavelengths approx 100 microns-1000 microns is many millimeters in diameter; the size of the field stop must be comparable. The dilute radiation at the stop is fed through a Winston nonimaging concentrator to a small cavity containing the bolometer. The purpose of this paper is to review the principles and techniques of infrared field optics systems, including spectral filters, concentrators, cavities, and bolometers (as optical elements), with emphasis on photometric systems for wavelengths longer than 60 microns.

Hildebrand, R. H.↗

NASA NTRS1986

Focal plane optics in far-infrared and submillimeter astronomy

Hildebrand, R. H.↗

NASA NTRS2008

Science Activity Planner for the MER Mission

The Maestro Science Activity Planner is a computer program that assists human users in planning operations of the Mars Explorer Rover (MER) mission and visualizing scientific data returned from the MER rovers. Relative to its predecessors, this program is more powerful and easier to use. This program is built on the Java Eclipse open-source platform around a Web-browser-based user-interface paradigm to provide an intuitive user interface to Mars rovers and landers. This program affords a combination of advanced display and simulation capabilities. For example, a map view of terrain can be generated from images acquired by the High Resolution Imaging Science Explorer instrument aboard the Mars Reconnaissance Orbiter spacecraft and overlaid with images from a navigation camera (more precisely, a stereoscopic pair of cameras) aboard a rover, and an interactive, annotated rover traverse path can be incorporated into the overlay. It is also possible to construct an overhead perspective mosaic image of terrain from navigation-camera images. This program can be adapted to similar use on other outer-space missions and is potentially adaptable to numerous terrestrial applications involving analysis of data, operations of robots, and planning of such operations for acquisition of scientific data.

Norris, Jeffrey S.↗

NASA NTRS2009

A Comparative Study of a 1/4-Scale Gulfstream G550 Aircraft Nose Gear Model

A series of fluid dynamic and aeroacoustic wind tunnel experiments are performed at the University of Florida Aeroacoustic Flow Facility and the NASA-Langley Basic Aerodynamic Research Tunnel Facility on a high-fidelity -scale model of Gulfstream G550 aircraft nose gear. The primary objectives of this study are to obtain a comprehensive aeroacoustic dataset for a nose landing gear and to provide a clearer understanding of landing gear contributions to overall airframe noise of commercial aircraft during landing configurations. Data measurement and analysis consist of mean and fluctuating model surface pressure, noise source localization maps using a large-aperture microphone directional array, and the determination of far field noise level spectra using a linear array of free field microphones. A total of 24 test runs are performed, consisting of four model assembly configurations, each of which is subjected to three test section speeds, in two different test section orientations. The different model assembly configurations vary in complexity from a fully-dressed to a partially-dressed geometry. The two model orientations provide flyover and sideline views from the perspective of a phased acoustic array for noise source localization via beamforming. Results show that the torque arm section of the model exhibits the highest rms pressures for all model configurations, which is also evidenced in the sideline view noise source maps for the partially-dressed model geometries. Analysis of acoustic spectra data from the linear array microphones shows a slight decrease in sound pressure levels at mid to high frequencies for the partially-dressed cavity open model configuration. In addition, far field sound pressure level spectra scale approximately with the 6th power of velocity and do not exhibit traditional Strouhal number scaling behavior.

Khorrami, Mehdi R.↗

NASA NTRS2012

Global Network of Slow Solar Wind

The streamer belt region surrounding the heliospheric current sheet (HCS) is generally treated as the primary or sole source of the slow solar wind. Synoptic maps of solar wind speed predicted by the Wang-Sheeley-Arge model during selected periods of solar cycle 23, however, show many areas of slow wind displaced from the streamer belt. These areas commonly have the form of an arc that is connected to the streamer belt at both ends. The arcs mark the boundaries between fields emanating from different coronal holes of the same polarity and thus trace the paths of belts of pseudostreamers, i.e., unipolar streamers that form over double arcades and lack current sheets. The arc pattern is consistent with the predicted topological mapping of the narrow open corridor or singular separator line that must connect the holes and, thus, consistent with the separatrix-web model of the slow solar wind. Near solar maximum, pseudostreamer belts stray far from the HCS-associated streamer belt and, together with it, form a global-wide web of slow wind. Recognition of pseudostreamer belts as prominent sources of slow wind provides a new template for understanding solar wind stream structure, especially near solar maximum.

solar wind↗

NASA NTRS1985

The Einstein soft X-ray survey of the Pleiades

The results of a 0.1-4.5-keV X-ray survey of a 2 x 2-deg area centered on the Pleiades open cluster, performed using the imaging proportional counter and high-resolution imager of the Einstein Observatory on four days in 1980-1981, are presented in extensive tables, graphs, maps, histograms, and finding charts and characterized. A total of 61 sources are detected, and 44 of these are identified with cluster members of spectral types B-M. Findings discussed include Lx/Lbol of 10 the -7th for early-type stars; F-star mean Lx like that of F stars in the Hyades and in the field (denying time evolution of Lx); mean G-star Lx = 3.7 x 10 to the 29th erg/sec; G-star activity decay more gradual than 1/sq rt t, with sharp fall for t greater than 1 Gyr; and no evidence for X-ray-emissivity/rotational-velocity correlation in a homogeneous sample of K dwarfs or a sample of K and M stars with established V sin i data.

Caillault, J.-P.↗

NASA NTRS2004

Kronos: A Satellite for Astrotomography

Kronos, a Medium Explorer concept, is designed to initiate a new era in astrophysics, fully opening the domain of time by enabling extended simultaneous multiwavelength (X-ray, UV, and optical) spectroscopic monitoring of variable accretion-driven sources. The primary design goal of the mission is to obtain high-fidelity velocity-delay maps of the broad-line region in active galactic nuclei (AGNs) and thus determine the geometry and structure of AGNs on microarcsecond scales. Doppler tomography and eclipse mapping techniques will be used to characterize and map Galactic binary systems, revealing the details of the physics of accretion processes in black hole, neutron star, and white dwarf binary systems. The high-Earth orbit of Kronos enables well-sampled, high time-resolution observations, critical for the innovative and sophisticated methods that are used to understand the accretion flows, mass outflows, jets, and other phenomena found in accreting sources.

Peterson, B. M.↗

NASA NTRS2018

Using the cFS Command and Data Dictionary (CCDD) to Automate Software Development on Habulous

Final paper is attached. The NASA developed Core Flight System (cFS) is a reusable software architecture that has been used on multiple spaceflight missions. By using this framework, missions are able to reuse code from other missions, as well as leverage deployment onto similar computer architectures (i.e. not "reinvent the wheel" on each new mission). The success in the cFS concept can be seen in the large number of projects using cFS at FSW-2018. The Habulous project is an Earth-based testbed, used for hardware and software that may one day be used on a future space habitat unit, with many participating groups from various NASA centers and aerospace organizations around the country. The distributed nature of the various teams mean that defining (and following) an interface definition is critical on the project. Additionally, since various groups use various types of computer hardware (32/64-bit, big/little endian, Linux/VxWorks/Windows) many additional complications exist in interfacing all the various components into a final integrated system. cFS is used on the majority the flight software (FSW) in running in Habulous. But some subsystems have elected to not use cFS, and use a software bridge (called SBN_lib) to interact with the other cFS nodes in Habulous. In order to most efficiently develop the FSW, a central database is used to define and store each message sent by cFS. A Command and Data Dictionary (CDD) is something nearly universal on spacecraft, but as a team we worked to develop the CDD before the SW development was complete, and not treat it like "as built" documentation. To manage the CDD, the cFS Command and Data Dictionary (CCDD) tool was chosen (available from NASA as open source software). The CCDD tool has successfully been used to automate/autocode a large amount of software used on Habulous, as we are hoping to use it to define even more items in the future (time-triggered Ethernet (TTE) network maps, CPU scheduling). Additionally, Habulous has been exploring the use of cFS on wildly heterogeneous CPUs, and how to coordinate all those various machines using/extending the software bus â€“ network (SBN) application in cFS, as well as TTE to coordinate message passing between various synchronized machines. The major topics to be covered in the presentation are: (1) Updating to the CCSDS_v2 extended headers (and using CPU# as subsystem ID). (2) Managing all the message identification numbers for each cFS message sent/received on any of the various CPUs. (3) Using the CCDD information to automatically generate the C-header files that define the structure for all software bus (SB) commands/telemetry messages. (4) Using the CCDD to automatically generate XML Telemetry and Command Exchange (XTCE) files, which streams display production/integration/testing in a web based display architecture (5) Extending/customizing SBN to pass messages among computers on multiple networks. (6) Using "Protobetter" inside SBN to manage different endian-ness/architectures. (7) Using SBN_lib to allow non-cFS node to communicate with cFS nodes. (8) Developing TTE network and schedule tables for all the various CPUs to use.

Hirsh, Robert L.↗

NASA NTRS1998

[Cosmic Microwave Background (CMB) Anisotropies]

One of the main areas of research is the theory of cosmic microwave background (CMB) anisotropies and analysis of CMB data. Using the four year COBE data we were able to improve existing constraints on global shear and vorticity. We found that, in the flat case (which allows for greatest anisotropy), (omega/H)0 less than 10(exp -7), where omega is the vorticity and H is the Hubble constant. This is two orders of magnitude lower than the tightest, previous constraint. We have defined a new set of statistics which quantify the amount of non-Gaussianity in small field cosmic microwave background maps. By looking at the distribution of power around rings in Fourier space, and at the correlations between adjacent rings, one can identify non-Gaussian features which are masked by large scale Gaussian fluctuations. This may be particularly useful for identifying unresolved localized sources and line-like discontinuities. Levin and collaborators devised a method to determine the global geometry of the universe through observations of patterns in the hot and cold spots of the CMB. We have derived properties of the peaks (maxima) of the CMB anisotropies expected in flat and open CDM models. We represent results for angular resolutions ranging from 5 arcmin to 20 arcmin (antenna FWHM), scales that are relevant for the MAP and COBRA/SAMBA space missions and the ground-based interferometer. Results related to galaxy formation and evolution are also discussed.

Silk, Joseph↗

NASA NTRS2017

Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.

Gentry, Diana↗

NASA NTRS2016

The NASA Severe Thunderstorm Observations and Regional Modeling (NASA STORM) Project

The NASA Severe Storm Thunderstorm Observations and Regional Modeling(NASA STORM) project enhanced NASA’s severe weather research capabilities, building upon existing Earth Science expertise at NASA Marshall Space Flight Center (MSFC). During this project, MSFC extended NASA’s ground-based lightning detection capacity to include a readily deployable lightning mapping array (LMA). NASA STORM also enabled NASA’s Short-term Prediction and Research Transition (SPoRT) to add convection allowing ensemble modeling to its portfolio of regional numerical weather prediction (NWP) capabilities. As a part of NASA STORM, MSFC developed new open-source capabilities for analyzing and displaying weather radar observations integrated from both research and operational networks. These accomplishments enabled by NASA STORM are a step towards enhancing NASA’s capabilities for studying severe weather and positions them for any future NASA related severe storm field campaigns.

modeling↗

NASA NTRSDate not supplied

A Cloud-Based Operational Surface Water Extent Mapping Service from Sentinel-1 SAR

With its weather independence and day-and-night capabilities, SAR has long been known as a useful data set for flood monitoring. The recently launched Sentinel-1 (S1) C-band sensors, with their regularly acquired, free-and-open data, have finally elevated SAR to a relevant data source in operational hazard response. Leveraging these capabilities of S1, this poster introduces the HYDRO30 product, a 30-m resolution surface water extent product derived from dual-pol S1 SAR data. To enable automatic and near real-time product generation, HYDRO30 is embedded in the HydroSAR service, a cloud-based production pipeline developed by the University of Alaska Fairbanks in collaboration with the NASA Alaska Satellite Facility DAAC and the NASA Marshall and Goddard Space Flight Centers.

Franz J Meyer↗

NASA NTRS1979

Seismic vibration source

A system for vibrating the earth in a location where seismic mapping is to take place is described. A relatively shallow hole formed in the earth, such as a hole 10 feet deep, placing a solid propellant in the hole, sealing a portion of the hole above the solid propellant with a device that can rapidly open and close to allow a repeatedly interrupted escape of gas. The propellant is ignited so that high pressure gas is created which escapes in pulses to vibrate the earth.

Dowler, W. L.↗