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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Airport Surface Delays and Causes: A Preliminary Analysis

This report summarizes FAA Program Analysis and Operations Research Service (ASD-400)/Lockheed Martin activities and findings related to airport surface delays and causes, in support of NASA Langley Research Center's Terminal Area Productivity (TAP) Program. The activities described in this report were initiated in June 1995. A preliminary report was published on September 30, 1995. The final report incorporates data collection forms filled out by traffic managers, other FAA staff, and an airline for the New York City area, some updates, data previously requested from various sources to support this analysis, and further quantification and documentation than in the preliminary report. This final report is based on data available as of April 12, 1996. This report incorporates data obtained from review and analysis of data bases and literature, discussions/interviews with engineers, air-traffic staff, other FAA technical personnel, and airline staff, site visits, and a survey on surface delays and causes. It includes analysis of delay statistics; preliminary findings and conclusions on surface movement, surface delay sources and causes, runway occupancy time (ROT), and airport characteristics impacting surface operations and delays; and site-specific data on the New York City area airports, which are the focus airports for this report.

Chin, David K.↗
NASA NTRS1998

Local Data Integration in East Central Florida Using the ARPS Data Analysis System

This paper describes the Applied Meteorology Unit's (AMU) efforts to configure, implement, and test a version of the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS; Brewster 1996) that assimilates all available data within 250 km of the Kennedy Space Center (KSC) and the Eastern Range at Cape Canaveral Air Station (CCAS). The objective for running a Local Data Integration System (LDIS) such as ADAS is to generate products which may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of ground and aerospace operations at KSC/CCAS. A LDIS such as ADAS has the potential to provide added value because it combines observational data to produce gridded analyses of temperature, wind, and moisture (including clouds) and diagnostic quantities such as vorticity, divergence, etc. at specified temporal and spatial resolutions. In this regard, a LDTS along with suitable visualization tools may provide users with a ignore complete and comprehensive understanding of evolving weather than could be developed by individually examining the disparate data sets over the same area and time. The AMU implemented a working prototype of the ADAS which does not run in real-time. Instead, the AMU is evaluating ADAS through post-analyses of weather events for a warm and cool season case. The case studies were chosen to investigate the capabilities and limitations of a LDIS such as ADAS including the impact of non-incorporation of specific data sources on the utility of the subsequent analyses.

Case, Jonathan↗
NASA NTRS2000

Photoionization and Recombination

Theoretically self-consistent calculations for photoionization and (e + ion) recombination are described. The same eigenfunction expansion for the ion is employed in coupled channel calculations for both processes, thus ensuring consistency between cross sections and rates. The theoretical treatment of (e + ion) recombination subsumes both the non-resonant recombination ("radiative recombination"), and the resonant recombination ("di-electronic recombination") processes in a unified scheme. In addition to the total, unified recombination rates, level-specific recombination rates and photoionization cross sections are obtained for a large number of atomic levels. Both relativistic Breit-Pauli, and non-relativistic LS coupling, calculations are carried out in the close coupling approximation using the R-matrix method. Although the calculations are computationally intensive, they yield nearly all photoionization and recombination parameters needed for astrophysical photoionization models with higher precision than hitherto possible, estimated at about 10-20% from comparison with experimentally available data (including experimentally derived DR rates). Results are electronically available for over 40 atoms and ions. Photoionization and recombination of He-, and Li-like C and Fe are described for X-ray modeling. The unified method yields total and complete (e+ion) recombination rate coefficients, that can not otherwise be obtained theoretically or experimentally.

Nahar, Sultana N.↗
NASA NTRS2003

An Analysis of the Automated Meteorological Profiling System Low Resolution Flight Element

A study was conducted to determine the quality of thermodynamic and wind data measured by or derived from the Low Resolution Flight Element (LRFE) of the Automated Meteorological Profiling System (AMPS). The AMPS LRFE replaced the Meteorological Sounding System (MSS), which was used to provide vertical profiles of thermodynamic and low-resolution wind data in support of spacecraft launch operations at the Cape Canaveral Air Force Station (CCAFS) and NASA Kennedy Space Center (KSC), Florida. Air temperature, relative humidity, and height, which are directly measured by the LRFE, are used to derive air pressure and density. Test flights were conducted where an LRFE sonde and an MSS sonde were attached to the same balloon and the two profiles were compared. MSS data was used as the standard reference data. The objective of the thermodynamic testing was to determine a) if the LRFE met Space Shuttle Program (SSP) accuracy requirements outlined in the Space Shuttle Launch and Landing Program Requirements Document (PRD) and/or, b) if the LRFE met or exceeded MSS data quality. AMPS uses the Global Positioning System (GPS) to determine wind speed and direction. In order to provide a basis for comparison, either an AMPS High Resolution Flight Element (HRFE) or a radar tracked Jimsphere was released simultaneously with each AMPS LRFE at CCAFS. The goal of these tests was to determine if the LRFE wind data met the requirement for low-resolution wind data defined in the Shuttle PRD. Based on the available data, the LRFE is shown to produce more consistent thermodynamic measurements than the MSS. The LRFE is also shown to meet the Shuttle PRD requirements for low resolution wind data.

Leahy, Frank B.↗
NASA NTRS2013

Application of Statistically Derived CPAS Parachute Parameters

The Capsule Parachute Assembly System (CPAS) Analysis Team is responsible for determining parachute inflation parameters and dispersions that are ultimately used in verifying system requirements. A model memo is internally released semi-annually documenting parachute inflation and other key parameters reconstructed from flight test data. Dispersion probability distributions published in previous versions of the model memo were uniform because insufficient data were available for determination of statistical based distributions. Uniform distributions do not accurately represent the expected distributions since extreme parameter values are just as likely to occur as the nominal value. CPAS has taken incremental steps to move away from uniform distributions. Model Memo version 9 (MMv9) made the first use of non-uniform dispersions, but only for the reefing cutter timing, for which a large number of sample was available. In order to maximize the utility of the available flight test data, clusters of parachutes were reconstructed individually starting with Model Memo version 10. This allowed for statistical assessment for steady-state drag area (CDS) and parachute inflation parameters such as the canopy fill distance (n), profile shape exponent (expopen), over-inflation factor (C(sub k)), and ramp-down time (t(sub k)) distributions. Built-in MATLAB distributions were applied to the histograms, and parameters such as scale (sigma) and location (mu) were output. Engineering judgment was used to determine the "best fit" distribution based on the test data. Results include normal, log normal, and uniform (where available data remains insufficient) fits of nominal and failure (loss of parachute and skipped stage) cases for all CPAS parachutes. This paper discusses the uniform methodology that was previously used, the process and result of the statistical assessment, how the dispersions were incorporated into Monte Carlo analyses, and the application of the distributions in trajectory benchmark testing assessments with parachute inflation parameters, drag area, and reefing cutter timing used by CPAS.

Romero, Leah M.↗
NASA NTRSDate not supplied

High Flying Interns: NASA's Student Airborne Research Program

The NASA Student Airborne Research Program is an annual summer internship for upper-level undergraduate STEM majors. Each summer since 2009, we have competitively selected ~30 undergraduates from colleges and universities across the United States for this unique airborne research experience. In all past summers, students flew onboard a NASA research aircraft where they assisted in the operation of remote sensing and in situ instrumentation to study the Earth, ocean, and atmosphere. Students also participated in field trips where they acquired data to ground-truth and complement the airborne data. After their flights and field trips, students then spent the rest of summer developing individual research projects using the data they collected as well as data from previous year SARP flights, other NASA airborne campaigns, and NASA satellite data. This summer, we adapted the program to be entirely online. Each of the 28 undergraduate students still completed an individual research project using data from previous SARP flights as well as publicly available data from other airborne campaigns, satellites, and/or ground stations. Students were mentored remotely by five university faculty members, five graduate students, and several additional scientists and engineers from NASA. In order to preserve some aspects of the hands-on research experience, we also shipped each student a box of twenty-four Whole Air Sampling canisters identical to what they would have used to collect air samples onboard the NASA aircraft. Instead, each student collected ground samples near their home starting in mid-April through July. The goal of this sampling was to attempt to characterize the impacts of pandemic-related changes in emissions with time across the United States. The results of that ground sampling are being presented in scientific sessions in this meeting. In addition, students also measured PM2.5 and aerosol optical depth from June through August using sensors provided by the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) at Colorado State University. We will discuss strategies we employed to conduct research online, the unexpected opportunities that arose, and lessons learned.

STEM disciplines↗
NASA NTRSDate not supplied

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗
NASA NTRSDate not supplied

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗
NASA NTRS2005

Fossil Groups in the Local Universe

The two galaxies observed as part of this project were originally selected as fossil group candidates because of their isolation from other galaxies and their apparent high X-ray luminosity and extended X-ray emission. However, the X-ray data available was minimal, being drawn from the ROSAT All-Sky Survey. We have performed an initial analysis of the XMM data from both galaxies and found that their gaseous halos are smaller, cooler, and less luminous than expected. In the case of NGC 57, the RASS estimate of extent and luminosity was biased because of a previously unidentified background group which is visible in the XMM data to one side of the galaxy. In the case of IC 153 1, the contribution from background point sources near the galaxy appears to be to blame. This suggests that both galaxies should be reclassified as isolated ellipticals. Such systems are very rare, and currently poorly understood; for comparison, there are now 6-10 known fossil groups, but only one isolated elliptical with useful X-ray data. We are currently re-analyzing the data for the two galaxies to take advantage of the calibration improvements of SAS 6.1, and to include calculations of the mass profiles of the two systems. A paper is currently in preparation dealing with the X-ray properties and environment of the galaxies, and we expect to submit this to the Astrophysical Journal within the next two months. Multi-band optical imaging of the field surrounding NGC 57 has been acquired to confirm its isolated status and provide more information on the background group. IC 1531 was accepted as a target in Chandra cycle 6 as part of a related proposal, and we intend to add this new observation to our XMM data when it becomes available. A second paper is planned to include the results of this combined analysis.

OSullivan, Ewan↗
DOE OSTI2025

Computed Tomography Scanning and Geophysical Measurements of the Clinton Formation in Ohio

Computed tomography and multi-sensor core logging of core material from twelve Ohio wells held by the Ohio Department of Natural Resources, Division of Geological Survey to make publicly available core information from the Early Silurian Clinton Formation in Eastern Ohio. Describes data available can be accessed from NETL’s Energy Data eXchange (EDX) online system, https://edx.netl.doe.gov/dataset/ct-and-geophysical-data-of-ohio-clinton-sands.

58 GEOSCIENCES↗
NASA NTRS1994

Software agents for the dissemination of remote terrestrial sensing data

Remote terrestrial sensing (RTS) data is constantly being collected from a variety of space-based and earth-based sensors. The collected data, and especially 'value-added' analyses of the data, are finding growing application for commercial, government, and scientific purposes. The scale of this data collection and analysis is truly enormous; e.g., by 1995, the amount of data available in just one sector, NASA space science, will reach 5 petabytes. Moreover, the amount of data, and the value of analyzing the data, are expected to increase dramatically as new satellites and sensors become available (e.g., NASA's Earth Observing System satellites). Lockheed and other companies are beginning to provide data and analysis commercially. A critical issue for the exploitation of collected data is the dissemination of data and value-added analyses to a diverse and widely distributed customer base. Customers must be able to use their computational environment (eventually the National Information Infrastructure) to obtain timely and complete information, without having to know the details of where the relevant data resides and how it is accessed. Customers must be able to routinely use standard, widely available (and, therefore, low cost) analyses, while also being able to readily create on demand highly customized analyses to make crucial decisions. The diversity of user needs creates a difficult software problem: how can users easily state their needs, while the computational environment assumes the responsibility of finding (or creating) relevant information, and then delivering the results in a form that users understand? A software agent is a self-contained, active software module that contains an explicit representation of its operational knowledge. This explicit representation allows agents to examine their own capabilities in order to modify their goals to meet changing needs and to take advantage of dynamic opportunities. In addition, the explicit representation allows agents to advertize their capabilities and results to other agents, thereby allowing the collection of agents to reuse each others work.

Toomey, Christopher N.↗
NASA NTRS1996

Evaluation of an Anthropometric Human Body Model for Simulated EVA Task Assessment

One of the more mission-critical tasks performed in space is extravehicular activity (EVA) which requires the astronaut to be external to the station or spacecraft, and subsequently at risk from the many threats posed by space. These threats include, but are not limited to: no significant atmosphere, harmful electromagnetic radiation, micrometeoroids, and space debris. To protect the astronaut from this environment, a special EVA suit is worn which is designed to maintain a sustainable atmosphere (at 1/3 atmosphere) and provide protection against the hazards of space. While the EVA suit serves these functions well, it does impose limitations on the astronaut as a consequence of the safety it provides. Since the astronaut is in a virtual vacuum, any atmospheric pressure inside the suit serves to pressurize the suit and restricts mobility of flexible joints (such as fabric). Although some of the EVA suit joints are fixed, rotary-style joints, most of the mobility is achieved by the simple flexibility of the fabric. There are multiple layers of fabric, each of which serves a special purpose in the safety of the astronaut. These multiple layers add to the restriction of motion the astronaut experiences in the space environment. Ground-based testing is implemented to evaluate the capability of EVA-suited astronauts to perform the various tasks in space. In addition to the restriction of motion imposed by the EVA suit, most EVA activity is performed in a micro-gravity (weight less) environment. To simulate weightlessness EVA-suited testing is performed in a neutral buoyancy simulator (NBS). The NBS is composed of a large container of water (pool) in which a weightless environment can be simulated. A subject is normally buoyant in the pressurized suit; however he/she can be made neutrally buoyant with the addition of weights. In addition, most objects the astronaut must interface with in the NBS sink in water and flotation must be added to render them "weightless". The implementation of NBS testing has proven to invaluable in the assessment of EVA activities performed with the Orbiter and is considered to be a key step in the construction of the International Space Station (ISS). While the NBS testing is extremely valuable, it does require considerable overhead to maintain and operate. It has been estimated that the cost of utilizing the facility is approximately $10,000 per day. Therefore it is important to maximize the utility of NBS testing for optimal results. One important aspect to consider in any human/worksite interface is the considerable wealth of anthropometric and ergonomic data available. A subset of this information specific to EVA activity is available in NASA standard 3000. The difficulty in implementing this data is that most of the anthropometric information is represented in a two-dimensional format. This poses some limitations in complete evaluation of the astronaut's capabilities in a three-dimensional environment. Advances in computer hardware and software have provided for three-dimensional design and implementation of hardware with the advance of computer aided design (CAD) software. There are a number of CAD products available and most companies and agencies have adopted CAD as a fundamental aspect of the design process. Another factor which supports the use of CAD is the implementation of computer aided manufacturing (CAM) software and hardware which provides for rapid prototyping and decreases the time to product in the design process. It is probable that most hardware to be accessed by astronauts in EVA or IVA (intravehicular activity) has been designed by a CAD system, and is therefore represented in three-dimensional space for evaluation. Because of the implementation of CAD systems and the movement towards early prototyping, a need has arisen in industry and government for tools which facilitate the evaluation of ergonomic consideration in a three-dimensional environment where the hardware has been designed by the CAD tools. One such product is Jack which was developed by the University of Pennsylvania with funding from several government agencies, including NASA. While the primary purpose of Jack is to model human figures in a ground-based (gravity) environment, it can be utilized to evaluate EVA-suited activities as well. The effects of simulated gravity must be turned off by turning off "behaviors". Although Jack provides human figures for manipulation, the primary instrument to be evaluated for EVA mobility is the work envelope provided by the EVA suit. An EVA Jack suit model has been developed by NASA-JSC and was utilized in this study. This suit model provided a more restrictive motion environment as expected for an EVA suited subject. As part of this study, the anthropometric dimensions for a 50th percentile male were compared with basic anthropometric data and were found to be representative for the population group expected in the NASA flight program. The joints for the suit were created in a manner which provided consistent performance with EVA reach envelopes published in NASA standard #3000.

Etter, Brad↗
NASA NTRS1948

Summary of Section Data on Trailing-Edge High-Lift Devices

A summary has been made of available data on the characteristics of airfoil sections with trailing-edge high-lift devices. Data for plain, split, and slotted flaps are collected and analyzed. The effects of each of the variables involved in the design of the various types of flap are examined and, in cases where sufficient data are given, optimum configurations are deduced. Wherever possible, the effects of airfoil section, Reynolds number, and leading-edge roughness are shown. For single and double slotted flaps, where a great mass of unrelated date are available, maximum lift coefficients of a large number of configurations are presented in tables.

Source record↗
NASA NTRS2001

Gridded Hourly Text Products: A TRMM Data Reduction Approach

The quantity of precipitation data from satellite-based observations is a blessing and a curse. The sheer volume of the data makes it difficult for many researchers to use in targeted applications. This volume increases further as algorithm improvements lead to the reprocessing of mission data. In addition to the overall volume of data, the size and format complexity of orbital granules contribute to the difficulty in using all the available data. Finally, the number of different instruments available to measure rainfall and related parameters further contributes to the volume concerns. In summary, we have an embarrassment of riches. The science team of the Tropical Rainfall Measuring Mission (TRMM) recognized this dilemma and has developed a strategy to address it. The TRMM Science Data and Information System (TSDIS) produces, at the direction of the Joint TRMM Science Team, a number of instantaneous rainfall products. The TRMM Microwave Imager (TMI), the Precipitation Radar and a Combined TMI/PR are the key "instruments" used in this production. Each of these products contains an entire orbit of data. The algorithm code computes not just rain rates but a large number of other physical parameters as well as information needed for monitoring algorithm performance. That makes these products very large. For example, a single orbit of TMI rain rate product is 99 MB, a single orbit of the combined product yields a granule that is 158 MB, while the 80 vertical levels of rain information from the PR yields an orbital product of 253 MB. These are large products that are often difficult for science users to electronically transfer to their sites especially if they want a large period of time. Level 3 gridded products are much smaller, but their 5 or 30 day temporal resolution is insufficient for many researchers. In addition, TRMM standard products are produced in the HDF format. While a large number of user-friendly tools are available to hide the details of the format (including a toolkit developed at TSDIS for the TRMM science team), many potential users shy away

Stocker, Erich↗
DOE OSTI2026

Operating Experience Data Analysis for Digital Instrumentation and Control System Reliability and Risk Assessment in Nuclear Power Plants

The implementation of advanced digital instrumentation and control (DI&C) systems in U.S. nuclear power plants (NPPs) can bring significant advancements in reliability, monitoring, and control capabilities. However, these systems also introduce new challenges, particularly in assessing risks such as common-cause failures (CCFs) and establishing robust reliability estimates for DI&C components. Addressing these challenges is critical for ensuring the safe and efficient operation of NPPs. Recently, Idaho National Laboratory was tasked by the U.S. Nuclear Regulatory Commission (NRC) to conduct a DI&C reliability study using operating experience data from the nuclear industry. The two operating experience data sources for the study are the Institute of Nuclear Power Operations’ Industry Reporting and Information System (IRIS) and the NRC’s Licensee Event Report database which is hosted at Idaho National Laboratory at https://lersearch.inl.gov/LERSearchCriteria.aspx. This report provides a comprehensive examination of DI&C systems, including their architecture, operational advantages, and associated challenges. It reviews existing industry DI&C studies and failure mode taxonomies, along with reliability data from various industries. Through a detailed analysis of these databases, the study provides insights into DI&C system performance. Considerations should be given to incorporate DI&C failure data into the NRC's Integrated Data Collection and Coding System and updating the Reliability and Availability Data System to support ongoing DI&C reliability studies. Recommendations are also provided for modeling DI&C reliability and CCF in probabilistic risk assessment, thereby supporting risk-informed decision-making and enhancing the reliability and safety of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1974

Physical state of interstellar atoms

Brief survey of the physical conditions along the lines of sight to reddened and unreddened stars, as determined from Copernicus observation of interstellar lines between 95 and 300 nm. Differences in ionization structure and density between clouds and the local intercloud medium are discussed. Some new data for beta Centauri is used to supplement the previously available data.

York, D. G.↗
NASA NTRS1985

Evidence for long-term variability in the ultra high energy photon flux from Cygnus X-3

A time-correlation analysis of atmospheric Cerenkov pulses by a wide-angle photomultiplier system was previously shown to have present in it a nonrandom component which seemed associated with the Right Ascension (RA) range approx. 20+or-04h. A recent examination of multi-muon events recorded by a photon-decay detector shows a similar time-dependent effect, closely matching the previous results, supporting the suggestion that the effect is of cosmic origin. However, even though Cyg. X-3 lies well inside the region of peak intensity, it does not seem possible to ascribe to it the whole effect, for the implied photon flux appears too large to be reconciled to various gamma-ray measurements of Cyg. X-3. The original data were subjected to a phase-histogram analysis and it as found that only 2.5% of overall recorded data are compatible with a phase-dependent emission from Cyg. X-3. Assuming these events to be gamma rays yields a detected flux of (2.6 + or - 0.3) x 10 to the minus 12th power gamma cm -2s-1 above 5 x 10 to the 14th power eV. Comparing this value with more recent ultra high energy (UHE) photon data from the same source, it is suggested that the available data generally favor a long-term reduction in the Cyg. X-3 inferred luminosity ( 10 to the 13th power eV) by a factor of (1.8 + or - 0.3) per year.

Bhat, C. L.↗
NASA NTRS2001

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

VandeVen, C.↗