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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Effects of Spatial Gradients on Electron Runaway Acceleration

The runaway process is known to accelerate electrons in many laboratory plasmas and has been suggested as an acceleration mechanism in some astrophysical plasmas, including solar flares. Current calculations of the electron velocity distributions resulting from the runaway process are greatly restricted because they impose spatial homogeneity on the distribution. We have computed runaway distributions which include consistent development of spatial gradients in the energetic tail. Our solution for the electron velocity distribution is presented as a function of distance along a finite length acceleration region, and is compared with the equivalent distribution for the infinitely long homogenous system (i.e., no spatial gradients), as considered in the existing literature. All these results are for the weak field regime. We also discuss the severe restrictiveness of this weak field assumption.

MacNeice, Peter↗
NASA NTRS1983

Segmentation of remotely sensed data using parallel region growing

The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.

Tilton, J. C.↗
NASA NTRS2003

Estimation of Transpiration and Water Use Efficiency Using Satellite and Field Observations

Structure and function of terrestrial plant communities bring about intimate relations between water, energy, and carbon exchange between land surface and atmosphere. Total evaporation, which is the sum of transpiration, soil evaporation and evaporation of intercepted water, couples water and energy balance equations. The rate of transpiration, which is the major fraction of total evaporation over most of the terrestrial land surface, is linked to the rate of carbon accumulation because functioning of stomata is optimized by both of these processes. Thus, quantifying the spatial and temporal variations of the transpiration efficiency (which is defined as the ratio of the rate of carbon accumulation and transpiration), and water use efficiency (defined as the ratio of the rate of carbon accumulation and total evaporation), and evaluation of modeling results against observations, are of significant importance in developing a better understanding of land surface processes. An approach has been developed for quantifying spatial and temporal variations of transpiration, and water-use efficiency based on biophysical process-based models, satellite and field observations. Calculations have been done using concurrent meteorological data derived from satellite observations and four dimensional data assimilation for four consecutive years (1987-1990) over an agricultural area in the Northern Great Plains of the US, and compared with field observations within and outside the study area. The paper provides substantive new information about interannual variation, particularly the effect of drought, on the efficiency values at a regional scale.

Choudhury, Bhaskar J.↗
NASA NTRS1976

Forest Classification Accuracy as Influenced by Multispectral Scanner Spatial Resolution

The author has identified the following significant results. A supervised classification within two separate ground areas of the Sam Houston National Forest was carried out for two sq meters spatial resolution MSS data. Data were progressively coarsened to simulate five additional cases of spatial resolution ranging up to 64 sq meters. Similar processing and analysis of all spatial resolutions enabled evaluations of the effect of spatial resolution on classification accuracy for various levels of detail and the effects on area proportion estimation for very general forest features. For very coarse resolutions, a subset of spectral channels which simulated the proposed thematic mapper channels was used to study classification accuracy.

Nalepka, R. F.↗
NASA NTRS2005

Sub-pixel Spatial Resolution Micro-roughness Measurements with Interlaced Stitching

In this paper we describe a method to increase the spatial resolution of surface micro-roughness measurements. As the surface specifications for precision optics become more demanding, the metrology instruments must cover a broad spatial frequency range. Generally, multiple instruments are used to cover the full range of the specifications. For example, a Fizeau interferometer would be used to test low spatial frequency surface errors, a white light interferometer would be used for mid spatial frequency errors, and an AFM would be used for high spatial frequency errors. For some precision optics, three instruments would be necessary. However, in many applications, an increase in the spatial resolution of a metrology instrument could negate the need for multiple instruments. A solution to increase the spatial resolution of micro-roughness measurements obtained using white light interferometry with "interlaced stitching" will be presented. In "interlaced stitching", multiple interferometric measurements are made as the optic under test (or the CCD array) is laterally shifted at sub-pixel increments. The measurements are then combined to construct a measurement with higher spatial resolution. Initial results obtained while implementing a similar process used to increase the spatial resolution of measurements made with a commercially available Fizeau interferometer will be presented.

Mooney, James T.↗
NASA NTRS1994

Fiber Optic Switch For Broadband Emission Spectroscopy

Many high-temperature processes comprise large-scale phenomena. Studying spatial and temporal correlations of physical processes between several locations within characteristic scales provides desired information on macroscopic physical processes. Achieved with emission spectroscopy by use of multiple optical fibers. Simultaneous coupling of light from these fibers into single available spectrometer and/or monochromator not accomplished without added expense of two-dimensional array and increased complexity of calibration. Quasi-simultaneous coupling, while maintaining optimum alignment and maximum throughput of broadband emission, achieved by use of fiber optic multiscanner. Instrument used successfully in study of frozen-flow losses internal to flow of plasma inside nozzle of arc jet. Instrument includes two hollow disks of different sizes and stepping motor.

De Groot, Wim↗
NASA NTRS2000

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Emerson, Charles W.↗
NASA NTRS2007

Spatial Reorientation of Sensorimotor Balance Control in Altered Gravity

Sensorimotor coordination of body segments following space flight are more pronounced after landing when the head is actively tilted with respect to the trunk. This suggests that central vestibular processing shifts from a gravitational frame of reference to a head frame of reference in microgravity. A major effect of such changes is a significant postural instability documented by standard head-erect Sensory Organization Tests. Decrements in functional performance may still be underestimated when head and gravity reference frames remained aligned. The purpose of this study was to examine adaptive changes in spatial processing for balance control following space flight by incorporating static and dynamic tilts that dissociate head and gravity reference frames. A second aim of this study was to examine the feasibility of altering the re-adaptation process following space flight by providing discordant visual-vestibular-somatosensory stimuli using short-radius pitch centrifugation.

Paloski, W. H.↗
NASA NTRS1985

Quantitative analysis of geomorphic processes using satellite image data at different scales

When aerial and satellite photographs and images are used in the quantitative analysis of geomorphic processes, either through direct observation of active processes or by analysis of landforms resulting from inferred active or dormant processes, a number of limitations in the use of such data must be considered. Active geomorphic processes work at different scales and rates. Therefore, the capability of imaging an active or dormant process depends primarily on the scale of the process and the spatial-resolution characteristic of the imaging system. Scale is an important factor in recording continuous and discontinuous active geomorphic processes, because what is not recorded will not be considered or even suspected in the analysis of orbital images. If the geomorphic process of landform change caused by the process is less than 200 m in x to y dimension, then it will not be recorded. Although the scale factor is critical, in the recording of discontinuous active geomorphic processes, the repeat interval of orbital-image acquisition of a planetary surface also is a consideration in order to capture a recurring short-lived geomorphic process or to record changes caused by either a continuous or a discontinuous geomorphic process.

Williams, R. S., Jr.↗
NASA NTRS1997

Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

Engman, Edwin T.↗
NASA NTRSDate not supplied

AWP: NASA's Aerosol Wind Profiler Coherent Doppler Wind Lidar

A new airborne coherent Doppler Wind Lidar (DWL) instrument has been implemented leveraging NASA's development of the 2-micron Wind-Space Pathfinder (Wind-SP) lidar transceiver. A technology development project, Wind-SP refined and demonstrated numerous components required for a coherent-detection space wind lidar instrument. Aerosol Wind Profiler (AWP) transitioned this transceiver into an airborne wind lidar capable of providing full 3-D wind vector retrievals. AWP operates with laser pulse energy and repetition rate combination required for high spatial and vertical resolution wind profiling from space. Operation from aircraft platforms will yield very strong signal return required for detailed process studies at <2km spatial and <100m vertical resolution under most conditions. AWP will serve as NASA’s wind calibration and validation instrument for future space-based wind observations over the coming decades, while also providing data supporting space wind lidar simulation studies. The AWP instrument is introduced and preliminary results from recent AWP demonstration flights are presented.

AWP↗
NASA NTRS2021

An Operational Overview of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) Northeast Pacific Field Deployment

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with two ships: a Process Ship, focused on ecological rates, BGC fluxes, temporal changes in food web, and BGC and optical properties, that followed an instrumented Lagrangian float; and a Survey Ship that sampled BGC and optical properties in spatial patterns around the Process Ship. An array of autonomous underwater assets provided measurements over a range of spatial and temporal scales, and partnering programs and remote sensing observations provided additional observational context. The oceanographic setting was typical of late-summer conditions at Ocean Station Papa: a shallow mixed layer, strong vertical and weak horizontal gradients in hydrographic properties, sluggish sub-inertial currents, elevated macronutrient concentrations and low phytoplankton abundances. Although nutrient concentrations were consistent with previous observations, mixed layer chlorophyll was lower than typically observed, resulting in a deeper euphotic zone. Analyses of surface layer temperature and salinity found three distinct surface water types, allowing for diagnosis of whether observed changes were spatial or temporal.The 2018 EXPORTS field deployment is among the most comprehensive biological pump studies ever conducted. A second deployment to the North Atlantic Ocean occurred in spring 2021, which will be followed by focused work on data synthesis and modeling using the entire EXPORTS data set.

Biological pump↗
NASA NTRS1992

Measurement of the Relative and Absolute Microgravity Environment of Space Platforms, Recent Flight Results, and Determination of the Spatial Microgravity Field

Microgravity material processing in space, such as crystal growth, requires specific and accurate knowledge of the very low frequency, very low level microgravity. This means knowledge of absolute microgravity levels. Most acceleration measurement systems for space platforms only measure 'microvibrations,' the measurement of the absolute microgravity level being severely corrupted by bias errors, temperature hysteresis, nonlinearity by-products, and bias changes due to launch vibrations. An advanced system was developed incorporating a fixed 3-axis acceleration measurement system with improved signal conditioning and Invertible Accelerometers for absolute measurements. The higher sensitivity channels have lower frequency low pass filtering to meet crystal growers demands for recording of low level/low frequency disturbances. Also included is a pre-flight bias adjustment feature.

Bijvoet, J. A.↗
NASA NTRS2019

Simplifying NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user.

Liu, Zhong↗
NASA NTRS1989

Detection of edges using local geometry

Researchers described a new representation, the local geometry, for early visual processing which is motivated by results from biological vision. This representation is richer than is often used in image processing. It extracts more of the local structure available at each pixel in the image by using receptive fields that can be continuously rotated and that go to third order spatial variation. Early visual processing algorithms such as edge detectors and ridge detectors can be written in terms of various local geometries and are computationally tractable. For example, Canny's edge detector has been implemented in terms of a local geometry of order two, and a ridge detector in terms of a local geometry of order three. The edge detector in local geometry was applied to synthetic and real images and it was shown using simple interpolation schemes that sufficient information is available to locate edges with sub-pixel accuracy (to a resolution increase of at least a factor of five). This is reasonable even for noisy images because the local geometry fits a smooth surface - the Taylor series - to the discrete image data. Only local processing was used in the implementation so it can readily be implemented on parallel mesh machines such as the MPP. Researchers expect that other early visual algorithms, such as region growing, inflection point detection, and segmentation can also be implemented in terms of the local geometry and will provide sufficiently rich and robust representations for subsequent visual processing.

Gualtieri, J. A.↗
NASA NTRS1988

A mathematical model for spatial orientation from pictorial perspective displays

A previously formulated mathematical model, describing how observers reconstruct three-dimensional spatial layouts from perspective projections, has been extended to more complex situations. The model assumes that the observer has a priori knowledge of certain characteristics of the viewed objects, like size, shape, or parallelism or perpendicularity of lines or planes. These assumptions are used in a three-dimensional process to reconstruct a spatial layout that `best matches' the perceived lines of sight to the object coordinates. Sources of errors and biases in this process are specified and their effects on model outputs are discussed. An experiment, in which eight subjects judged the relative direction of one object with respect to another, has been conducted to validate the model. The model has been found to generally reproduce the systematic trends of the experimental results and also has provided an analytical explanation for them. The mathematical model is expected to be a useful tool in analyzing and developing pictorial perspective flight displays.

Grunwald, Arthur J.↗
NASA NTRS2003

The Bermuda BioOptics Project (BBOP) Years 9-11

The Bermuda BioOptics Project (BBOP) is a collaborative effort between the Institute for Computational Earth System Science (ICESS) at the University of California at Santa Barbara (UCSB) and the Bermuda Biological Station for Research (BBSR). This research program is designed to characterize light availability and utilization in the Sargasso Sea, and to provide an optical link by which biogeochemical observations may be used to evaluate bio-optical models for pigment concentration, primary production, and sinking particle fluxes from satellite-based ocean color sensors. The BBOP time-series was initiated in 1992, and is carried out in conjunction with the U.S. JGOFS Bermuda Atlantic Time-series Study (BATS) at the Bermuda Biological Station for Research. The BATS program itself has been observing biogeochemical processes (primary productivity, particle flux and elemental cycles) in the mesotrophic waters of the Sargasso Sea since 1988. Closely affiliated with BBOP and BATS is a separate NASA-funded study of the spatial variability of biogeochemical processes in the Sargasso Sea using high-resolution AVHRR and SeaWiFS data collected at Bermuda. The collaboration between BATS and BBOP measurements has resulted in a unique data set that addresses not only the SIMBIOS goals but also the broader issues of important factors controlling the carbon cycle. This final report addresses specific research activities, research results, and lists of presentations and papers submitted for publication.

Nelson, Norm↗
NASA NTRS2003

Bermuda Bio Optics Project

The Bermuda BioOptics Project (BBOP) is a collaborative effort between the Institute for Computational Earth System Science (ICESS) at the University of California at Santa Barbara (UCSB) and the Bermuda Biological Station for Research (BBSR). This research program is designed to characterize light availability and utilization in the Sargasso Sea, and to provide an optical link by which biogeochemical observations may be used to evaluate bio-optical models for pigment concentration, primary production, and sinking particle fluxes from satellite-based ocean color sensors. The BBOP time-series was initiated in 1992, and is carried out in conjunction with the U.S. JGOFS Bermuda Atlantic Time-series Study (BATS) at the Bermuda Biological Station for Research. The BATS program itself has been observing biogeochemical processes (primary productivity, particle flux and elemental cycles) in the mesotrophic waters of the Sargasso Sea since 1988. Closely affiliated with BBOP and BATS is a separate NASA-funded study of the spatial variability of biogeochemical processes in the Sargasso Sea using high-resolution AVHRR and SeaWiFS data collected at Bermuda (N. Nelson, P.I.). The collaboration between BATS and BBOP measurements has resulted in a unique data set that addresses not only the SIMBIOS goals but also the broader issues of important factors controlling the carbon cycle.

Nelson, Norm↗