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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.

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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Sequence, molecular properties, and chromosomal mapping of mouse lumican

PURPOSE. Lumican is a major proteoglycan of vertebrate cornea. This study characterizes mouse lumican, its molecular form, cDNA sequence, and chromosomal localization. METHODS. Lumican sequence was determined from cDNA clones selected from a mouse corneal cDNA expression library using a bovine lumican cDNA probe. Tissue expression and size of lumican mRNA were determined using Northern hybridization. Glycosidase digestion followed by Western blot analysis provided characterization of molecular properties of purified mouse corneal lumican. Chromosomal mapping of the lumican gene (Lcn) used Southern hybridization of a panel of genomic DNAs from an interspecific murine backcross. RESULTS. Mouse lumican is a 338-amino acid protein with high-sequence identity to bovine and chicken lumican proteins. The N-terminus of the lumican protein contains consensus sequences for tyrosine sulfation. A 1.9-kb lumican mRNA is present in cornea and several other tissues. Antibody against bovine lumican reacted with recombinant mouse lumican expressed in Escherichia coli and also detected high molecular weight proteoglycans in extracts of mouse cornea. Keratanase digestion of corneal proteoglycans released lumican protein, demonstrating the presence of sulfated keratan sulfate chains on mouse corneal lumican in vivo. The lumican gene (Lcn) was mapped to the distal region of mouse chromosome 10. The Lcn map site is in the region of a previously identified developmental mutant, eye blebs, affecting corneal morphology. CONCLUSIONS. This study demonstrates sulfated keratan sulfate proteoglycan in mouse cornea and describes the tools (antibodies and cDNA) necessary to investigate the functional role of this important corneal molecule using naturally occurring and induced mutants of the murine lumican gene.

NASA Discipline Cell Biology↗
NASA NTRS1995

An Example of Unsupervised Networks Kohonen's Self-Organizing Feature Map

Kohonen's self-organizing feature map belongs to a class of unsupervised artificial neural network commonly referred to as topographic maps. It serves two purposes, the quantization and dimensionality reduction of date. A short description of its history and its biological context is given. We show that the inherent classification properties of the feature map make it a suitable candidate for solving the classification task in power system areas like load forecasting, fault diagnosis and security assessment.

Kohonen Feature Map↗
NASA NTRS1996

The JERS-1 Amazon Multi-Season Mapping Study (JAMMS)

Regional mapping of the Amazon basin using imaging radar is described. Two 60-day periods of radar mapping will be conducted, one in 1995, and one in 1996. One period will view the low-water season, and the other will view during the high-flood season. The main objective of the JAMMS project is to generate a regional map showing inundation throughout the Amazon Basin by comparing the two data sets.

Amazon Radar Mapping Earth Satellite JAMMS flood p↗
NASA NTRS1995

(abstract) Mars Global Surveyor: A Global Mapping Mission

The Mars Global Surveyor Mission will launch a single spacecraft to Mars in November 1996. After arrival at the planet in September 1997 aerobraking will be used to lower the spacecraft into a low, sun-synchronous, polar-mapping orbit over several months. Early in 1998 mapping observations will begin and continue for a Mars year (687 days). Following completion of this first Mars year of mapping the spacecraft will continue to act as a relay orbiter for an additional three Earth years. The five instruments carried involve magnetometry, surface and atmosphere imaging, atmospheric sounding, laser altimetry, gravity and thermal emission spectroscopy. In addition, the spacecraft carries a Mars relay receiver/transmitter which will operate over the entire five year orbital mission ending in January of 2003. The Mars Global Surveyor mission is intended to accomplish a portion of the scientific objectives of the Mars Observer mission which was lost in 1993 three days before entering Mars orbit. The instrumentation to be used for the magnetometers, cameras, laser altimeter, emission spectrometer and radio science are very nearly the same as those carried by Mars Observer. The spacecraft design will be new but will use spare equipment from Mars Observer and has a mass about two and one-half time smaller. All experiments will be controlled remotely from their investigators home installation. The long planned period of observation supports the mission's global and seasonal objectives.

Mars Global Surveyor Mars Observer mapping spectro↗
NASA NTRS1994

Generation of High Resolution Topographic Maps of the Galapagos Islands Using TOPSAR Data

Data collected over the Galapagos Islands using the JPL/NASA TOPSAR airborne interferometric radar covered an area in excess of 5000 km(sup 2). This paper presents the algorithms used to mosaic the data into a high resolution (10X10 m ground spacing) topographic map of the islands. Also described are the correlation and height maps which are generated as ancillary products to the topographic maps.

topsar interferometry galapagos algorithms error m↗
NASA NTRS2011

High Resolution Camera for Mapping Titan Surface

Titan, Saturn's largest moon, has a dense atmosphere and is the only object besides Earth to have stable liquids at its surface. The Cassini/Huygens mission has revealed the extraordinary breadth of geological processes shaping its surface. Further study requires high resolution imaging of the surface, which is restrained by light absorption by methane and scattering from aerosols. The Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini spacecraft has demonstrated that Titan's surface can be observed within several windows in the near infrared, allowing us to process several regions in order to create a geological map and to determine the morphology. Specular reflections monitored on the lakes of the North Pole show little scattering at 5 microns, which, combined with the present study of Titan's northern pole area, refutes the paradigm that only radar can achieve high resolution mapping of the surface. The present data allowed us to monitor the evolution of lakes, to identify additional lakes at the Northern Pole, to examine Titan's hypothesis of non-synchronous rotation and to analyze the albedo of the North Pole surface. Future missions to Titan could carry a camera with 5 micron detectors and a carbon fiber radiator for weight reduction.

Cassini↗
NASA NTRS2016

Incorporating Yearly Derived Winter Wheat Maps Into Winter Wheat Yield Forecasting Model

Wheat is one of the most important cereal crops in the world. Timely and accurate forecast of wheat yield and production at global scale is vital in implementing food security policy. Becker-Reshef et al. (2010) developed a generalized empirical model for forecasting winter wheat production using remote sensing data and official statistics. This model was implemented using static wheat maps. In this paper, we analyze the impact of incorporating yearly wheat masks into the forecasting model. We propose a new approach of producing in season winter wheat maps exploiting satellite data and official statistics on crop area only. Validation on independent data showed that the proposed approach reached 6% to 23% of omission error and 10% to 16% of commission error when mapping winter wheat 2-3 months before harvest. In general, we found a limited impact of using yearly winter wheat masks over a static mask for the study regions.

MODIS↗
NASA NTRS2016

Optical and Physical Methods for Mapping Flooding with Satellite Imagery

Flood and surface water mapping is becoming increasingly necessary, as extreme flooding events worldwide can damage crop yields and contribute to billions of dollars economic damages as well as social effects including fatalities and destroyed communities (Xaio et al. 2004; Kwak et al. 2015; Mueller et al. 2016).Utilizing earth observing satellite data to map standing water from space is indispensable to flood mapping for disaster response, mitigation, prevention, and warning (McFeeters 1996; Brakenridge and Anderson 2006). Since the early 1970s(Landsat, USGS 2013), researchers have been able to remotely sense surface processes such as extreme flood events to help offset some of these problems. Researchers have demonstrated countless methods and modifications of those methods to help increase knowledge of areas at risk and areas that are flooded using remote sensing data from optical and radar systems, as well as free publically available and costly commercial datasets.

satellite imagery↗
NASA NTRS2017

Simulation-Based Height of Burst Map for Asteroid Airburst Damage Prediction

Entry and breakup models predict that airburst in the Earth's atmosphere is likely for asteroids up to approximately 200 meters in diameter. Objects of this size can deposit over 250 megatons of energy into the atmosphere. Fast-running ground damage prediction codes for such events rely heavily upon methods developed from nuclear weapons research to estimate the damage potential for an airburst at altitude. (Collins, 2005; Mathias, 2017; Hills and Goda, 1993). In particular, these tools rely upon the powerful yield scaling laws developed for point-source blasts that are used in conjunction with a Height of Burst (HOB) map to predict ground damage for an airburst of a specific energy at a given altitude. While this approach works extremely well for yields as large as tens of megatons, it becomes less accurate as yields increase to the hundreds of megatons potentially released by larger airburst events. This study revisits the assumptions underlying this approach and shows how atmospheric buoyancy becomes important as yield increases beyond a few megatons. We then use large-scale three-dimensional simulations to construct numerically generated height of burst maps that are appropriate at the higher energy levels associated with the entry of asteroids with diameters of hundreds of meters. These numerically generated HOB maps can then be incorporated into engineering methods for damage prediction, significantly improving their accuracy for asteroids with diameters greater than 80-100 m.

Burst Map↗
NASA NTRS2018

Smallholder Crop Area Mapped with Wall-To-Wall WorldView Sub-Meter Panchromatic Image Texture: A Test Case for Tigray, Ethiopia

Global food production in the developing world occurs within sub-hectare fields that are difficult to identify with moderate resolution satellite imagery. Knowledge about the distribution of these fields is critical in food security programs. We developed a semi-automated image segmentation approach using wall-to-wall sub-meter imagery with high-performance computing to map crop area (CA) throughout Tigray, Ethiopia that encompasses over 41,000 km (exp 2). Multiple processing streams were tested to minimize mapping error while applying five unique smoothing kernels to capture differences in land surface texture associated to CA. Typically, very-small fields (mean < 2 ha) have a smooth image roughness compared to natural scrub/shrub woody vegetation at the ~1m scale and these features can be segmented in panchromatic imagery with multi-level histogram thresholding. Multi-temporal very-high resolution (VHR) panchromatic imagery with multi-spectral VHR are sufficient in extracting critical CA information needed in food security programs. A 2011 to 2015 CA map was produced, using over 3000 WorldView-1 panchromatic images wall-to-wall in 1/2 deg mosaics for Tigray, Ethiopia. CA was evaluated with nearly 3000 WorldView-2 2m multispectral 250 X 250 m image subsets by seven expert interpretations, and with in-situ global positioning system photography. CA estimates ranged from 32 to 41% in sub regions of Tigray with median maximum per bin commission and omission errors of 11% and 1% respectively, with most of the error occurring in bins <15%. This empirical, simple, and low direct cost approach via U.S. government license agreement to access commercial VHR data, could be a viable big-data high-performance computing methodology to extract wall-to-wall CA for other regions of the world that have very-small agriculture fields with similar image texture."

Ethiopia↗
NASA NTRS2016

Challenges in Planetary Mapping and Surface Navigation

The presentation focuses on surface navigation and mapping challenges in planetary environments including Lunar and Martian surface. Imagery from precursor orbital missions are processed to provide a medium resolution, large coverage 2D and 3D maps used by the science and navigation teams. During the surface mission these mapping products together with the images captured from the on-board camera systems are used in rover localization and navigation.

planetary mapping↗
NASA NTRS2018

A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classification

A self-organizing map (SOM) is a type of competitive artificial neural network, which projects the high dimensional input space of the training samples into a low dimensional space with the topology relations preserved. This makes SOMs supportive of organizing and visualizing complex data sets and have been pervasively used among numerous disciplines with different applications. Notwithstanding its wide applications, the self-organizing map is perplexed by its inherent randomness, which produces dissimilar SOM patterns even when being trained on identical training samples with the same parameters every time, and thus causes usability concerns for other domain practitioners and precludes more potential users from exploring SOM based applications in a broader spectrum. Motivated by this practical concern, we propose a deterministic approach as a supplement to the standard self-organizing map. In accordance with the theoretical design, the experimental results with satellite cloud data demonstrate the effective and efficient organization as well as simplification capabilities of the proposed approach.

Initialization method↗
NASA NTRS2019

NIAC Phase I Final Report: On-Orbit, Collision-Free Mapping of Small Orbital Debris

Sub-centimeter orbital debris is currently undetectable using ground-based radar and optical methods. However, the pits in Space Shuttle windows produced by paint chips (e.g. the 3.8mm diameter pit produced by a 0.2mm paint chip on STS-7) demonstrate that small debris can cause serious damage to spacecraft. Recent analytical, computational and experimental work has shown that charged objects moving quickly through a plasma will cause the formation of solitons in the plasma density. Due to their exposure to the solar wind plasma environment, even the smallest space debris will be charged. Depending on the debris size, charge and velocity, the plasma signature of the solitons may be detected by simple instrumentation on spacecraft. We will describe the amplitude and velocity of solitons that may be produced by mm-cm scale orbital debris in LEO. We will discuss the feasibility of mapping sub-cm orbital debris using a fleet of CubeSats equipped with Langmuir probes. The time and fleet size required to map the debris will also be described. Plasma soliton detection would be the first collision-free method of mapping the small debris population.

Orbital Debris↗
NASA NTRSDate not supplied

Tutorial on LuNaMaps Developed Tools andProcesses for Mapping the Lunar Surface

The main contribution of this project is the combined knowledge of terrain relative navigation experts and lunar scientists who are familiar with both the lunar orbital imagery and the instruments that collected the data as well as how a TRN system utilizes map data. This knowledge comes in the form of published technical papers, benchmark map data sets, and software tools that can help others automate the process of creating the necessary maps for their own landing sites in the future. This presentation provides a brief overview of the tools and processes developed by the project.

optical navigation↗
NASA NTRSDate not supplied

Mobile Lidar as A Tool for Terrestrial and Planetary Cave Exploration and Mapping

The Kinematic Navigation and Cartography Knapsack (KNaCK) team at NASA’s Marshall Space Flight Center in Huntsville, Alabama is developing tools that enable ultra-high resolution terrain mapping and navigation using mobile LiDAR (Light Detection and Ranging) and SLAM (Simultaneous Localization and Mapping) algorithms in fully GPS-denied and unilluminated environments [1,2]. The backpack mounted LiDAR instrument under development by our team demonstrates the potential of mobile SLAM LiDAR for use in challenging lunar and planetary surface environments as well as for lunar, planetary, and terrestrial cave exploration, study, and utilization.

Lunar Skylight↗
NASA NTRSDate not supplied

Caves as Terrestrial Analogs for Mapping and Exploration in Planetary Surface and Subsurface Environments.

The Kinematic Navigation and Cartography Knapsack (KNaCK) team is developing tools that will enable ultra-high resolution terrain mapping and navigation at the lunar surface. KNaCK uses mobile light detection and ranging (LiDAR) and simultaneous localization and mapping (SLAM) algorithms to operate in fully GPS-denied and unilluminated environments. Testing in relevant analogs is key to perfecting this technology for planetary applications. After utilizing desert and volcanic environments for multiple tests, the team is now using caves as an additional proving ground. Tests in terrestrial caves have demonstrated the potential of mobile SLAM LiDAR for use in challenging surface environments such as steep walled craters and permanently shadowed regions as well as for lunar, planetary, and terrestrial cave exploration, study, and utilization.

LiDAR↗
NASA NTRS1970

Preprocessing of multispectral data and simulation of ERTS data channels to make computer terrain maps of a Yellowstone National Park test site

The possibility of improving the accuracy of terrain classification by preprocessing spectral data was investigated. Terrain maps were made using the following techniques: 1) preprocessing by scan angle function transformation, using the computer-selected best set of three channels; and 2) preprocessing by ratio transformation, using the specified ERTS data channels, simulated by fitting the spectral response of each of the 12 data channels to the ERTS channels by a set of weighting coefficients. By using a simple technique during printout, the maps were produced in color. The normalized scan angle function transformation resulted in the most accurate classification. The best ratio transformation for the Yellowstone Park data was the ratio of each channel to the sum of all channels. A supervised training program involving maximum likelihood decision for selecting the best spectrometer channels and similar techniques for digitizing the data of the analog magnetic tapes were used. Cloud shadows were recognized in addition to eight classes of terrain. Preprocessing of data resulted in more accurate maps, required fewer training areas (hence less preparation and computer time), and enabled much of the area formerly classified as shadow to be reclassified according to actual terrain type.

Smedes, H. W.↗