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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Spatial analysis of IRAS observations of nearby spirals

The unbiased survey of the infrared sky carried out by the Infrared Astronomy Satellite (IRAS) satellite has greatly accelerated advances in understanding the dust component of our own and external galaxies. However, most extragalactic studies to date have been based on the IRAS Point Source Catalog (PSC), which has two serious limitations. First, in sources where a significant fraction of the flux is extended, significant errors may result from using PSC fluxes in comparative studies, and these errors could be systematic if the tendency to be non-pointlike depends on physical properties of the galaxy. Additionally, use of PSC fluxes rules out any direct investigation of the spatial distribution of the IRAS emission from disks in external galaxies. Since work on the Galactic IRAS results has shown that very different physical processes can make varying contributions to the observed flux, it is important to look at a wide sample of galaxies with some spatial resolution to study the relative dominance of these processes under a variety of conditions. Here, researchers report on work they are doing to carry out this program for many nearby spirals, using an analysis package that was developed for this purpose. Researchers carried out analysis for a sample of 121 nearby spirals. The fraction of the flux contained in a point source varies from 0 to 1 across the sample, all of which are well resolved at their nominal optical diameters. There is no evidence that the galaxies of smaller angular size are less likely to be resolved by IRAS at this level. The program gives results which are quite repeatable from scan to scan; the fraction f (point source flux over total flux) at 60 microns has typical errors of 0.03 when different scans are combined. Approximately two-thirds of the sample have more flux in the extended than in the nuclear component. There is a tendency for earlier-type spirals to be less centrally concentrated, but this effect is slight and the degree of variation is large for all types. Barred spirals are also found across the spectrum of f, but are much more likely to have little or no nuclear emission.

Ball, Roger↗
NASA NTRS1986

Spatial analysis of storm depths from an Arizona raingage network

Eight years of summer rainstorm observations are analyzed by a dense network of 93 raingages operated by the U.S. Department of Agriculture, Agricultural Research Service, in the 150 km Walnut Gulch experimental catchment near Tucson, Arizona. Storms are defined by the total depths collected at each raingage during the noon-to-noon period for which there was depth recorded at any of the gages. For each of the resulting 428 storm days, the gage depths are interpolated onto a dense grid and the resulting random field analyzed to obtain moments, isohyetal plots, spatial correlation function, variance function, and the spatial distribution of storm depth.

Fennessey, N. M.↗
NASA NTRS1992

A Spatial Analysis and Modeling System (SAMS) for environment management

This is a proposal to develop a uniform global environmental data gathering and distribution system to support the calibration and validation of remotely sensed data. SAMS is based on an enhanced version of FE MA's Integrated Emergency Management Information Systems and the Department of Defense's Air Land Battlefield Environment Software Systems. This system consists of state-of-the-art graphics and visualization techniques, simulation models, database management and expert systems for conducting environmental and disaster preparedness studies. This software package will be integrated into various Landsat and UNEP-GRID stations which are planned to become direct readout stations during the EOS timeframe. This system would be implemented as a pilot program to support the Tropical Rainfall Measuring Mission (TRMM). This will be a joint NASA-FEMA-University-Industry project.

Vermillion, Charles H.↗
NASA NTRS1991

Spatial Analysis and Modeling Systems (SAMS)

The objective is to develop a uniform environmental data gathering and distribution system to support (1) emergency management for environmental disasters, and (2) the calibration and validation of remotely sensed data. Initial activities will be to select a data test site and to demonstrate multi-discipline applications using simulated or satellite data in a non real-time mode. Rainfall and flooding are chosen as the testbeds for the SAMS concept because of the abundance of data and the availability of models. The capability to display and process GOES data and analyze GOES generated rain-rate maps will be integrated into SAMS.

Vermillion, Charles↗
NASA NTRS1993

A Spatial Analysis and Modeling System (SAMS) for environment management

This is a proposal to develop a uniform global environmental data gathering and distribution system to support the calibration and validation of remotely sensed data. SAMS is based on an enhanced version of FEMA's Integrated Emergency Management Information Systems and the Department of Defense's Air land Battlefield Environment Software Systems. This system consists of state-of-the-art graphics and visualization techniques, simulation models, database management and expert systems for conducting environmental and disaster preparedness studies. This software package will be integrated into various Landsat and UNEP-GRID stations which are planned to become direct readout stations during the EOS (Earth Observing System) timeframe. This system would be implemented as a pilot program to support the Tropical Rainfall Measuring Mission (TRMM). This will be a joint NASA-FEMA-University-Industry project.

Stetina, Fran↗
NASA NTRS2009

Spatial Analysis of West Nile Virus: Predictive Risk Modeling of a Vector-borne Infectious Disease in Illinois by Means of NASA Earth Observation Systems

West Nile Virus is a mosquito-borne virus of the family Flaviviridae. It infects birds and various mammals, including humans, and can cause encephalitis that may prove fatal, notably among vulnerable populations. Since its identification in New York City in 1999, WNV has become established in a broad range of ecological settings throughout North America, infecting more than 25,300 people and killing 1133 as of 2008 (CDC,2009). WNV is transmitted by mosquitoes that feed on infected birds. As a result, the degree of human infection depends on local ecology and human exposure. This study hypothesizes that remote sensing and GIS can be used to analyze environmental determinants of WNV transmission, such as climate, elevation, land cover, and vegetation densities, to map areas of WNV risk for surveillance and intervention.

Renneboog, Nathan↗
NASA NTRS2009

Spatial Analysis of Environmental Factors Related to Lyme Disease in Alabama by Means of NASA Earth Observation Systems

This slide presentation reviews the epidemiology of Lyme Disease that accounts for more than 95% or vector borne diseases in the United States. The history, symptoms and the life cycle of the tick, the transmitting agent of Lyme Disease, a map that shows the cases reported to the CDC between1990 and 2006 and the number of cases in Alabama by year from 1986 to 2007. A NASA project is described, the goals of which are to (1) Demonstrate the presence of the chain of infection of Lyme disease in Alabama (2) Identify areas with environmental factors that support tick population using NASA Earth Observation Systems data in selected areas of Alabama and (3) Increase community awareness of Lyme disease and recommend primary and secondary prevention strategies. The remote sensing methods included: Analyzed Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and DigitalGlobe Quickbird satellite imagery from summer months and Performed image analyses in ER Mapper 7.1. Views from the ASTER and Quickbird land cover are shown, the Normalized Difference Vegetation Index (NDVI) algorithm was applied to all ASTER and Quickbird imagery. The use of the images to obtain the level of soil moisture is reviewed, and this analysis was used along with the NDVI, was used to identify the areas that support the tick population.

Renneboog, Nathan↗
NASA NTRS2010

Reducing Tick-Borne Disease in Alabama: Linking Health Risk Perception with Spatial Analysis Using the NASA Earth Observing System

Lyme disease (LD) accounts for most vector-borne disease reports in the U.S., and although its existence in Alabama remains controversial, other tick-borne illnesses (TBI) such as Southern Tick-Associated Rash Illness (STARI) pose a health concern in the state. Phase One of the Marshall Space Flight Center-UAB DEVELOP study of TBI identified the presence of the chain of infection for LD (Ixodes scapularis ticks carrying Borrelia burgdorferi bacteria) and STARI (Amblyomma americanum ticks and an as-yet-unconfirmed agent) in Alabama. Both LD and STARI are associated with the development of erythema migrans rashes around an infected tick bite, and while treatable with oral antibiotics, a review of educational resources available to state residents revealed low levels of prevention information. To improve prevention, recognition, and treatment of TBI in Alabama, Phase Two builds a health communication campaign based on vector habitat mapping and risk perception assessment. NASA Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery identified likely tick habitats using remotely sensed measurements of vegetation vigor (Normalized Difference Vegetation Index) and soil moisture. Likely tick habitats, identified as those containing both high vegetation density and soil moisture, included Oak Mountain State Park, Bankhead National Forest, and Talladega National Forest. To target a high-risk group -- outdoor recreation program participants at Alabama universities -- the study developed a behavior survey instrument based on existing studies of LD risk factors and theoretical constructs from the Social Ecological Model and Health Belief Model. The survey instrument was amended to include geographic variables in the assessment of TBI knowledge, attitudes, and prevention behaviors, and the vector habitat model will be expanded to incorporate additional environmental variables and in situ data. Remotely sensed environmental data combined with risk perception assessments inform an ongoing outreach campaign consisting of stakeholder meetings and educational seminars.

Hemmings, S.↗
NASA NTRS2003

NGC7009: Testing the Wind-Wind Interaction Formation of Planetary Nebulae

We have successfully obtained the XMM-Newton observations of NGC 7009. X-ray emission is detected from the interior of NGC 7009, and it is definite resolved, indicating a plasma emission. We have carried out both a spatial analysis and a spectral analysis. The spatial analysis is limited by the angular resolution of the telescope. It is possible to confirm the existence of diffuse emission from hot gas, but the detailed distribution of the hot gas and the amount of stellar emission cannot be determined. The spectral analysis shows that the plasma temperature is only about 2 x 10(exp 6) K. This is the coolest PN interior ever detected. A mixing of shocked fast stellar wind and the cool nebular material is needed. The results of our analysis have been reported in a paper published in the Astronomy and Astrophysics Letters, as given below.

Chu, You-Hua↗
NASA NTRS2006

Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis

Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns.

displacement↗
DOE OSTI2022

spopt: a python package for solving spatial optimization problems in PySAL

Spatial optimization is a major spatial analytical tool in management and planning, the significance of which cannot be overstated. Spatial optimization models play an important role in designing and managing effective and efficient service systems such as transportation, education, public health, environmental protection, and commercial investment among others. To this end, spopt (spatial optimization) is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions (Feng et al., 2021). Spopt is a submodule in the open-source spatial analysis library PySAL (Python Spatial Analysis Library) founded by Dr. Sergio J. Rey and Dr. Luc Anselin in 2005 (Rey et al., 2015, 2021; Rey & Anselin, 2007). The goal of developing spopt is to provide management and decision-making support to all relevant practitioners and to further promote the appropriate and meaningful application of spatial optimization models in practice.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Niche-DE: niche-differential gene expression analysis in spatial transcriptomics data identifies context-dependent cell-cell interactions

Existing methods for analysis of spatial transcriptomic data focus on delineating the global gene expression variations of cell types across the tissue, rather than local gene expression changes driven by cell-cell interactions. We propose a new statistical procedure called niche-differential expression (niche-DE) analysis that identifies cell-type-specific niche-associated genes, which are differentially expressed within a specific cell type in the context of specific spatial niches. We further develop niche-LR, a method to reveal ligand-receptor signaling mechanisms that underlie niche-differential gene expression patterns. Niche-DE and niche-LR are applicable to low-resolution spot-based spatial transcriptomics data and data that is single-cell or subcellular in resolution.

59 BASIC BIOLOGICAL SCIENCES↗