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The author has identified the following significant results. Analysis of soil temperature and water table data indicated that shallow aquifers appear to produce a heat sink effect when the depth to water table is approximately four meters or less.
A majority of the human population lives in urban areas and as such, the quality of urban environments is becoming increasingly important to the human population. Furthermore, these areas are major sources of environmental contaminants and sinks of energy and materials. Remote sensing provides an improved understanding of urban areas and their impacts by mapping urban extent, urban composition (vegetation and impervious cover fractions), and urban radiation balance through measures of albedo, emissivity and land surface temperature (LST). Recently, the National Research Council (NRC) completed an assessment of remote sensing needs for the next decade (NRC, 2007), proposing several missions suitable for urban studies, including a visible, near-infrared and shortwave infrared (VSWIR) imaging spectrometer and a multispectral thermal infrared (TIR) instrument called the Hyperspectral Infrared Imagery (HyspIRI). In this talk, we introduce the HyspIRI mission, focusing on potential synergies between VSWIR and TIR data in an urban area. We evaluate potential synergies using an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and MODIS-ASTER (MASTER) image pair acquired over Santa Barbara, United States. AVIRIS data were analyzed at their native spatial resolutions (7.5m VSWIR and 15m TIR), and aggregated 60 m spatial resolution similar to HyspIRI. Surface reflectance was calculated using ACORN and a ground reflectance target to remove atmospheric and sensor artifacts. MASTER data were processed to generate estimates of spectral emissivity and LST using Modtran radiative transfer code and the ASTER Temperature Emissivity Separation algorithm. A spectral library of common urban materials, including urban vegetation, roofs and roads was assembled from combined AVIRIS and field-measured reflectance spectra. LST and emissivity were also retrieved from MASTER and reflectance/emissivity spectra for a subset of urban materials were retrieved from co-located MASTER and AVIRIS pixels. Fractions of Impervious, Soil, Green Vegetation (GV) and Non-photosynthetic Vegetation (NPV), were estimated using Multiple Endmember Spectral Mixture Analysis (MESMA) applied to AVIRIS data at 7.5, 15 and 60 m spatial scales. Surface energy parameters, including albedo, vegetation cover fraction, broadband emissivity and LST were also determined for urban and natural land-cover classes in the region. Fractions were validated using 1m digital photography.
Potential interface compatibility problems associated with interfacing OFT payload elements with orbiter communications and data handling elements that would result from payload or orbit failure to meet interface requirements contained in the orbiter/cargo standard interface specification are identified. The potential interface compatibility problems can be associated with either attached payloads in the payload bay or detached payloads communicating with the orbiter via an RF link. Evaluation of the attached payload orbiter interfaces was made by investigating interface problem areas experienced between the IUS and the orbiter since similar problems could be expected for other payloads.
Neural networks have been successful in image classification and have shown potential for classifying remotely sensed data. This paper presents classifications of multitype Landsat Thematic Mapper (TM) data using neural networks. The Landsat TM Image for March 23, 1987 with accompanying ground observation data for a study area In Miami County, Indiana, U.S.A. was utilized to assess recognition of crop residues. Principal components and spectral ratio transformations were performed on the TM data. In addition, a layer of the geographic information system (GIS) for the study site was incorporated to generate GIS-enhanced TM data. This paper discusses (1) the performance of neuro-classification on each type of data, (2) how neural networks recognized each type of data as a new image and (3) comparisons of the results for each type of data obtained using neural networks, maximum likelihood, and minimum distance classifiers.
The City of Hutchinson, Minnesota, partnered with the Energy Department and the National Renewable Energy Laboratory (NREL) to demonstrate how data and analysis can inform more strategic energy decisions. NREL based its analysis in part on the City Energy Profiles on the State and Local Energy Data (SLED) website (eere.energy.gov/sled). The profiles contain data compiled by SLED and the Cities Leading through Energy Analysis and Planning (Cities-LEAP) program. Cities across the country can follow the same approach and use data-driven analysis in their own energy planning.
Attainment of magnetic order in nanoparticles at room temperature is an issue of critical importance for many different technologies. For ordinary ferromagnetic materials, a reduction in size leads to decreased magnetic anisotropy and results in superparamagnetic relaxations. If, instead, anisotropy could be enhanced at reduced particle sizes, then it would be possible to attain stable magnetic order at room temperature. Herein, we provide experimental evidence substantiating the synthesis of a cobalt iron carbide phase (CoFe{sub 2}C) of nanoparticles. Structural characterization of the CoFe{sub 2}C carbide phase was performed by transmission electron microscopy, electron diffraction and energy electron spectroscopy. X-ray diffraction was also performed as a complimentary analysis. Magnetic characterization of the carbide phase revealed a blocking temperature, T{sub B}, of 790 K for particles with a domain size as small as 5 ± 1 nm. The particles have magnetocrystalline anisotropy of 4.6 ± 2 × 10{sup 6 }J/m{sup 3}, which is ten times larger than that of Co nanoparticles. Such colossal anisotropy leads to thermally stable long range magnetic order. Moreover, the thermal stability constant is much larger than that of the commonly used FePt nanoparticles. With thermal stability and colossal anisotropy, the CoFe{sub 2}C nanoparticles have huge potential for enhanced magnetic data storage devices.
These datasets were used in the paper Gimenez et al., 2019 (Species-Specific Shifts in Diurnal Sap Velocity Dynamics and Hysteretic Behavior of Ecophysiological Variables During the 2015–2016 El Niño Event in the Amazon Forest) published in Frontiers in Plant Science, special issue: Water-Use Efficiency: Advances and Challenges in a Changing Climate. This data package contains data from ICT sap flow sensors, leaf temperature (Infrared Sensors), leaf gas exchange, leaf water potential and leaf thermocouple data used for some experiments of the NGEE-Tropics project in the Amazon Forest (sites: BR-Ma2 and BR-Sa1). The data package also includes environmental data (Relative humidity, air temperature, and VPD) collected using thermo-hygrometers installed in K-34 tower vertical profile (Manaus - BR-Ma2).
NASA and the Aviation Industry is looking into reduced crew operations (RCO) that would cut today's required two-person flight crews down to a single pilot with support from ground-based crews. Shared responsibility across air and ground personnel will require highly reliable and secure data communication and supporting automation, which will be safety-critical for passenger and cargo aircraft. This paper looks at the different types and degrees of authority delegation given from the air to the ground and the ramifications of each, including the safety and security hazards introduced, the mitigation mechanisms for these hazards, and other demands on an RCO system architecture which would be highly invasive into (almost) all safety-critical avionics. The adjacent fields of unmanned aerial systems and autonomous ground vehicles are viewed to find problems that RCO may face and related aviation accident scenarios are described. The paper explores possible data communication architectures to meet stringent performance and information security (INFOSEC) requirements of RCO. Subsequently, potential challenges for RCO data communication authentication, encryption and non-repudiation are identified.
NASA and the Aviation Industry is looking into reduced crew operations (RCO) that would cut today's required two-person flight crews down to a single pilot with support from ground-based crews. Shared responsibility across air and ground personnel will require highly reliable and secure data communication and supporting automation, which will be safety-critical for passenger and cargo aircraft. This paper looks at the different types and degrees of authority delegation given from the air to the ground and the ramifications of each, including the safety and security hazards introduced, the mitigation mechanisms for these hazards, and other demands on an RCO system architecture which would be highly invasive into (almost) all safety-critical avionics. The adjacent fields of unmanned aerial systems and autonomous ground vehicles are viewed to find problems that RCO may face and related aviation accident scenarios are described. The paper explores possible data communication architectures to meet stringent performance and information security (INFOSEC) requirements of RCO. Subsequently, potential challenges for RCO data communication authentication, encryption and non-repudiation are identified. The approach includes a comprehensive safety-hazard analysis of the RCO system to determine top level INFOSEC requirements for RCO and proposes an option for effective RCO implementation. This paper concludes with questioning the economic viability of RCO in light of the expense of overcoming the operational safety and security hazards it would introduce.
Communicating from Earth to any spacecraft is a complex challenge, largely due to the extreme distances involved. When data are transmitted and received across thousands and even millions of miles, the delay and potential for disruption or data loss is significant. Delay/Disruption Tolerant Networking (DTN) is NASA’s solution to reliable internet working for space missions.
In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrument data represent different data domains, and for an algorithm to work in both, domain-invariant learning is necessary. Here we employ domain adaptation techniques— Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)— and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies. Additionally, we explore the use of Fisher loss and entropy minimization to enforce better in-domain class discriminability. We show that the addition of each domain adaptation technique improves the performance of a classifier when compared to conventional deep learning algorithms. We demonstrate this on two examples: between two Illustris-1 simulated datasets of distant merging galaxies, and between Illustris-1 simulated data of nearby merging galaxies and observed data from the Sloan Digital Sky Survey. The use of domain adaptation techniques in our experiments leads to an increase of target domain classification accuracy of up to ~20%. With further development, these techniques will allow astronomers to successfully implement neural network models trained on simulation data to efficiently detect and study astrophysical objects in current and future large-scale astronomical surveys.
In this paper we discuss the potential and problems of soil moisture sensing using AMSR data that will become available in late 2000 or early 2001.
Optical potentials are a standard tool in the study of nuclear reactions, as they describe the interaction between a target nucleus and a projectile. The use of phenomenological optical potentials built using experimental data on stable isotopes is widespread. Although successful in their dedicated domain, it is unclear whether these phenomenological potentials can provide reliable predictions for unstable isotopes. To address this problem, optical potentials based on microscopic nuclear structure input calculations prove to be crucial and are an important current line of research. In this work we present an explicit implementation of the Feshbach formalism for the systematic derivation of optical potentials using input from nuclear structure models. Numerical tools for the derivation of Green's functions associated with nonlocal potentials are presented. In conclusion, the new optical potential, based on the valence shell model, is applied to the calculations of 𝑛 + 24 Mg elastic scattering and yields a close agreement with the experimental data.
Utah has a wealth of potential geological reservoirs for carbon dioxide storage (CS) and a long history of geologic research resulting in an abundance of available subsurface data to evaluate CS potential. Reservoirs may include sandstone, carbonate, and basalt; these rock types are plentiful in Utah’s subsurface and the complex Phanerozoic history throughout the state requires evaluating each geologic region individually for promising reservoir-seal pairs for CO2 storage. Classifying Utah by geologic provinces (or “geo-regions”) allows for customized thinking about suitable CS reservoir and seal distribution, CO2 point sources, land use, and existing infrastructure. Preliminary results from this study highlight the geologic CS potential across 15 geo-regions. Four regions stand out as having high CS potential: the Uinta Basin, San Rafael Swell, Paradox Basin, and the southern Basin and Range Province. The Uinta Basin and San Rafael Swell geo-regions are well suited for CS and have several projects ongoing to evaluate Cretaceous Frontier and Naturita Formations, Jurassic Navajo Sandstone and Entrada Sandstone, and Permian Weber Sandstone reservoir units that lie beneath robust sealing units like the ~5000-ft-thick Mancos Shale and Carmel Formation. Reservoirs such as the Navajo and Weber Sandstones have been demonstrated to be suitable reservoirs through a long history of oil and gas exploration in Utah. New areas of interest include the southern Basin and Range in southwest Utah, where the Jurassic Navajo Sandstone is overlain by the sealing Carmel Formation at suitable depths (>3000 ft), and has good porosities based on outcrop analogue data. Just to the north (e.g., central Basin and Range), legacy wells and 2D seismic data show possible salt and subsurface basalt flows that may provide additional possible CS reservoirs and seals. This geo-region also has the advantage of being coupled with geothermal energy resources that may be used to power burgeoning direct air capture technologies. In the Paradox Basin of southeastern Utah, the Leadville Limestone is a potential storage reservoir beneath the thick (4000–5000 ft), salt-bearing Pennsylvanian Paradox Formation. Although the northern and western parts of Utah offer CS potential, these areas typically contain less infrastructure and subsurface penetrations, creating geologic uncertainty associated with subsurface seals and reservoirs due to a lack of data. Overall, this statewide assessment and ranking is the first step to aid in evaluating CS potential across Utah and provides a foundation for future research in the most favorable locations.
The cold ion density in the plasma trough region is an important fundamental parameter in the currently proposed mechanisms to describe magnetospheric dynamics. Direct in situ measurements of the cold ion density are generally difficult owing to uncertainties in vehicle potentials and ion temperatures. It is shown that the light ion mass spectrometer from Ogo 5 was very successful in acquiring these data and that vehicle potentials appear not to have been a prohibitive factor. The cold ion plasma trough data show a great deal of variability, indicating a strong dependence on the state of the convection electric field; consequently, average values of cold ion densities in the plasma trough may be significantly different from the actual time-dependent values. The local time plot of plasma trough densities at L = 7 for data acquired over a 1-year period shows the anticipated increase in cold ion density during the daytime and the expected decrease in cold ion density during dusk and early nighttime.
Abstract Sites where anthropogenic CO 2 captured from industrial sources is stored in deep geological formations for climate change mitigation are required to show secure retention of the injected CO 2 . Monitoring, reporting, and verification (MRV) plans are needed to indicate that no CO 2 release has occurred. We explored the degree to which direct comparison between a surface anomaly and reservoir geochemistry using various geochemical parameters can be used for attribution. We used data collected on light hydrocarbons and noble gases throughout the sedimentary column at three CO 2 enhanced oil recovery (EOR) sites to understand the processes that may cause fluid evolution. Light hydrocarbon and noble gases were sampled from reservoirs, gas‐bearing intervals above reservoirs, and groundwater. Vertical profiles indicated that lighter components are relatively enriched during migration (i.e. chromatographic separation). Static and numerical models were designed to simulate episodic gas migration and geochemical alteration of these geochemical parameters from solubility and sorption. The effects of hydrocarbon solubility were minimal (Bernard ratio changes within 5.2%) although field data were within the range of expected alterations from sorption. Forward models of CO 2 migration and noble gas interactions showed that CO 2 stripping causes an enrichment of crustal noble gases. In areas where natural fluxes of CO 2 from depth are non‐existent, the occurrence of crustal noble gas signature may distinguish fugitive CO 2 from the reservoir from natural near‐surface sources, and could be considered to explain apparent fluid anomalies. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.
This article undertakes to study a generalized block diagram of a data collection and processing system of a spacecraft in which a number of sensors or outputs of scientific instruments are cyclically interrogated by a commutator, methods of writing the supplementary information in a frame on the example of a certain hypothetical telemetry system, and the influence of statistics of number of active channels in a frame on frame compression factor. The separation of the data compression factor of the collection and processing system of spacecraft into two parts used in this work allows determination of the compression factor of an active frame depending not only on the statistics of activity of channels in the telemetry frame, but also on the method of introduction of the additional address and time information to each frame.
Data are presented verifying the compatibility of currently proposed rendezvous radar measurement accuracies with Mission 3B rendezvous requirements. In addition, data presented indicate a potential for increasing the acceptable time lag between termination of thrusting and availability of accurate measurement data. Additional investigation is recommended to define any acceptable time lag above the current proposed value. Finally, Mission 3B rendezvous performance is shown to be sensitive to variations in the relative downrange position dispersions at insertion. It is therefore recommended that insertion relative state dispersions used in studies of 3B rendezvous be reviewed when results of 3B ascent dispersion studies are available.