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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 NTRS1989

Head-mounted spatial instruments II: Synthetic reality or impossible dream

A spatial instrument is defined as a spatial display which has been either geometrically or symbolically enhanced to enable a user to accomplish a particular task. Research conducted over the past several years on 3-D spatial instruments has shown that perspective displays, even when viewed from the correct viewpoint, are subject to systematic viewer biases. These biases interfere with correct spatial judgements of the presented pictorial information. The design of spatial instruments may not only require the introduction of compensatory distortions to remove the naturally occurring biases but also may significantly benefit from the introduction of artificial distortions which enhance performance. However, these image manipulations can cause a loss of visual-vestibular coordination and induce motion sickness. Consequently, the design of head-mounted spatial instruments will require an understanding of the tolerable limits of visual-vestibular discord.

Ellis, Stephen R.↗
NASA NTRS1989

Performance of two texture-based classifiers of cloud fields using spatially averaged Landsat data

Using the gray-level difference vector approach, classification accuracies with 1/8-km spatial-resolution data are similar to those obtained using the full spatial-resolution features. Hence no advantage is to be gained in cloud classification accuracies by using even higher spatial resolutions obtained from Landsat TM or SPOT imagery. The optimum spatial resolution is 1/4 km. However, significant improvement in cloud-classification accuracy compared to that available from the 1-km resolution of AVHRR and GOES imagery is obtained using 1/2-km-resolution data. Cirrus-classification accuracy is especially compromised as spatial resolution is degraded. However, texture measures defined at the combination of pixel separations d = 1,4 improve classification accuracies by several percent, even for 1-km spatial-resolution data. Cirrus-classification accuracy is significantly improved by the use of multiple distance features.

Sengupta, S. K.↗
NASA NTRS1995

Spatial symmetry breaking in rapidly rotating convective spherical shells

Many problems in geophysical and astrophysical convection systems are characterized by fast rotation and spherical shell geometry. The combined effects of Coriolis forces and spherical shell geometry produce a unique spatial symmetry for the convection pattern in a rapidly rotating spherical shell. In this paper, we first discuss the general spatial symmetries for rotating spherical shell convection. A special model, a spherical shell heated from below, is then used to illustrate how and when the spatial symmetries are broken. Symmetry breaking occurs via a sequence of spatial transitions from the primary conducting state to the complex multiple-layered columnar structure. It is argued that, because of the dominant effects of rotation, the sequence of spatial transitions identified from this particular model is likely to be generally valid. Applications of the spatial symmetry breaking to planetary convection problems are also discussed.

Zhang, Keke↗
NASA NTRS2007

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Al-Hamdan, Mohammad Z.↗
NASA NTRS2000

Focal plane scanner with reciprocating spatial window

A focal plane scanner having a front objective lens, a spatial window for selectively passing a portion of the image therethrough, and a CCD array for receiving the passed portion of the image. All embodiments have a common feature whereby the spatial window and CCD array are mounted for simultaneous relative reciprocating movement with respect to the front objective lens, and the spatial window is mounted within the focal plane of the front objective. In a first embodiment, the spatial window is a slit and the CCD array is one-dimensional, and successive rows of the image in the focal plane of the front objective lens are passed to the CCD array by an image relay lens interposed between the slit and the CCD array. In a second embodiment, the spatial window is a slit, the CCD array is two-dimensional, and a prism-grating-prism optical spectrometer is interposed between the slit and the CCD array so as to cause the scanned row to be split into a plurality of spectral separations onto the CCD array. In a third embodiment, the CCD array is two-dimensional and the spatial window is a rectangular linear variable filter (LVF) window, so as to cause the scanned rows impinging on the LVF to be bandpass filtered into spectral components onto the CCD array through an image relay lens interposed between the LVF and the CCD array.

Mao, Chengye↗
NASA NTRS2006

The Spatial Standard Observer

The spatial standard observer is a computational model that provides a measure of the visibility of a target in a uniform background image or of the visual discriminability of two images. Standard observers have long been used in science and industry to quantify the discriminability of colors. Color standard observers address the spectral characteristics of visual stimuli, while the spatial standard observer (SSO), as its name indicates, addresses spatial characteristics. The SSO is based on a model of human vision. The SSO was developed in a process that included evaluation of a number of earlier mathematical models that address optical, physiological, and psychophysical aspects of spatial characteristics of human visual perception. Elements of the prior models are incorporated into the SSO, which is formulated as a compromise between accuracy and simplicity. The SSO operates on a digitized monochrome still image or on a pair of such images. The SSO consists of three submodels that operate sequentially on the input image(s): 1. A contrast model, which converts an input monochrome image to a luminance contrast image, wherein luminance values are expressed as excursions from, and normalized to, a mean; 2. A contrast-sensitivity-filter model that includes an oblique-effect filter (which accounts for the decline in contrast sensitivity at oblique viewing angles); and 3. A spatial summation model, in which responses are spatially pooled by raising each pixel to the power beta, adding the results, and raising the sum to the 1/b power. In this model, b=2.9 was found to be a suitable value. The net effect of the SSO is to compute a numerical measure of the perceptual strength of the single image, or of the visible difference (denoted the perceptual distance) between two images. The unit of a measure used in the SSO is the just noticeable difference (JND), which is a standard measure of perceptual discriminability. A target that is just visible has a measure of 1 JND.

Watson, Andrew B.↗
NASA NTRS2011

Effects of Spatial Resolution on the Simulated Dust Aerosol Lifecycle: Implications for Dust Event Magnitude and Timing in the NASA GEOS-5 AGCM

The NASA GEOS-5 atmospheric transport model simulates global aerosol distributions with an online aerosol module. GEOS-5 may be run at various horizontal spatial resolutions depending on the research application. For example, long integration climate simulations are typically run at 2 deg or 1 deg grid spacing, whereas aerosol reanalysis and forecasting applications may be performed at O.5 deg or 0.25 deg resolutions. In this study, we assess the implications of varying spatial resolution on the simulated aerosol fields, with a particular focus on dust. Dust emissions in GEOS-5 are calculated with one of two parameterizations, one based on the Goddard Chemistry, Aerosol, Radiation, and Transport (GO CART) model and another based on the Dust Entrainment and Deposition (DEAD) model. Emission fluxes are parameterized in terms of the surface wind speed, either the 10-m (GO CART) or friction (DEAD) wind speed. We consider how surface wind speeds and thus the dust emission rates are a function of the model spatial resolution. We find that spatial resolution has a significant effect on the magnitude of dust emissions, as higher resolution versions of the model have typically higher surface wind speeds. Utilizing space-borne observations from MISR, MODIS, and CALIOP, we find that simulated Aerosol Optical Thickness (AOT) distributions respond differently to spatial resolution over the African and Asian source regions, highlighting the need to regional dust emission tuning. When compared to ground-based observations from AERONET, we found improved timing of dust events with as spatial resolution was increased. In an attempt to improve the representation of the dust aerosol lifecycle at coarse resolutions, we found that incorporating the effects of sub-grid wind variability in a course resolution simulation led to improved agreement with observed AOT magnitudes, but did not impact the timing of simulated dust events.

Nowottnick, E.↗
NASA NTRS2012

Estimation of Orbital Neutron Detector Spatial Resolution by Systematic Shifting of Differential Topographic Masks

We present a method and preliminary results related to determining the spatial resolution of orbital neutron detectors using epithermal maps and differential topographic masks. Our technique is similar to coded aperture imaging methods for optimizing photonic signals in telescopes [I]. In that approach photon masks with known spatial patterns in a telescope aperature are used to systematically restrict incoming photons which minimizes interference and enhances photon signal to noise. Three orbital neutron detector systems with different stated spatial resolutions are evaluated. The differing spatial resolutions arise due different orbital altitudes and the use of neutron collimation techniques. 1) The uncollimated Lunar Prospector Neutron Spectrometer (LPNS) system has spatial resolution of 45km FWHM from approx. 30km altitude mission phase [2]. The Lunar Rennaissance Orbiter (LRO) Lunar Exploration Neutron Detector (LEND) with two detectors at 50km altitude evaluated here: 2) the collimated 10km FWHM spatial resolution detector CSETN and 3) LEND's collimated Sensor for Epithermal Neutrons (SETN). Thus providing two orbital altitudes to study factors of: uncollimated vs collimated and two average altitudes for their effect on fields-of-view.

McClanahan, T. P.↗
NASA NTRS2013

10 Yr Spatial and Temporal Trends of PM2.5 Concentrations in the Southeastern US Estimated Using High-resolution Satellite Data

Long-term PM2.5 exposure has been reported to be associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of the true regional PM2.5 levels. To facilitate epidemiological studies, accurate estimates of spatiotemporally continuous distribution of PM2.5 concentrations are essential. Satellite-retrieved aerosol optical depth (AOD) has been widely used for PM2.5 concentration estimation due to its comprehensive spatial coverage. Nevertheless, an inherent disadvantage of current AOD products is their coarse spatial resolutions. For instance, the spatial resolutions of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) are 10 km and 17.6 km, respectively. In this paper, a new AOD product with 1 km spatial resolution retrieved by the multi-angle implementation of atmospheric correction (MAIAC) algorithm was used. A two-stage model was developed to account for both spatial and temporal variability in the PM2.5-AOD relationship by incorporating the MAIAC AOD, meteorological fields, and land use variables as predictors. Our study area is in the southeastern US, centered at the Atlanta Metro area, and data from 2001 to 2010 were collected from various sources. The model was fitted for each year individually, and we obtained model fitting R2 ranging from 0.71 to 0.85, MPE from 1.73 to 2.50 g m3, and RMSPE from 2.75 to 4.10 g m3. In addition, we found cross validation R2 ranging from 0.62 to 0.78, MPE from 2.00 to 3.01 g m3, and RMSPE from 3.12 to 5.00 g m3, indicating a good agreement between the estimated and observed values. Spatial trends show that high PM2.5 levels occurred in urban areas and along major highways, while low concentrations appeared in rural or mountainous areas. A time series analysis was conducted to examine temporal trends of PM2.5 concentrations in the study area from 2001 to 2010. The results showed that the PM2.5 levels in the study area followed a generally declining trend from 2001 to 2010 and decreased about 20 during the period. However, there was an exception of an increase in year 2005, which is attributed to elevated sulfate concentrations in the study area in warm months of 2005. An investigation of the impact of wild and prescribed fires on PM2.5 levels in 2007 suggests a positive relationship between them.

particulate matter (PM2.5)↗
DOE OSTI2025

Spatial top-down proteomics for the functional characterization of human kidney

Background: The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging. Results: Using healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions. Conclusions: We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) where discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

HexWeather: Hexagonal Spatial Data Aggregation for Weather-Driven Grid Resilience Analysis

Extreme weather accounts for over 8 0 % of major U.S. power outages since 2000, highlighting the need for spatial tools that align weather data with the irregular boundaries of electric infrastructure. This paper introduces HexWeather, a modular, resolution-aware framework for aggregating historical and forecasted weather data using Uber's H3 hexagonal spatial indexing system. Unlike traditional methods that rely on state or county-level grids, HexWeather enables weather analysis across custom geographies such as utility service areas where public datasets are often unavailable or misaligned. Using Open-Meteo data, we evaluate how H3 resolution affects anomaly detection, spatial variability, and forecast uncertainty across three scales: state, county, and utility. Results show that while coarse resolutions suffice for broad trend tracking, finer resolutions are essential for identifying localized variability and operational risks. By applying metrics like Z-score standard deviation and interquartile range, HexWeather quantifies the spatial spread of both historical anomalies and forecasted conditions, allowing users to assess resolution adequacy for each analysis. This framework supports rapid weather data reuse, reproducible anomaly detection, and predictive modeling for infrastructure resilience. By bridging spatial misalignment in traditional datasets and enabling retrospective and forward-looking analysis within the same pipeline, HexWeather lays the groundwork for better post event analysis, outage prediction, and resilience planning.

Morris, Jacob [ORNL]↗
DOE OSTI2026

Supervised Learning-Based Spatial Position Estimation with Vertical Displacement for Hovering UAV Wireless Power Transfer

This study presents a supervised learning-based spatial position estimation approach for wireless power transfer (WPT) systems supporting hovering unmanned aerial vehicle (UAV) charging. Unlike stationary charging scenarios, hovering UAVs introduce continuous lateral misalignment and vertical displacement, leading to variations in magnetic coupling and reduced power transfer efficiency. To address this challenge, the proposed method estimates the relative spatial position of the receiver coil using only electrical measurements obtained at the secondary side. A supervised learning model is trained to map output voltage and current features to spatial coordinates, enabling position awareness without requiring external sensors, vision systems, or communication links. The sensing functionality is inherently integrated into the WPT system, allowing simultaneous power transfer and localization through the same magnetic interface. Experimental validation is conducted on a laboratory-scale prototype under varying lateral offsets and air-gap conditions. In addition, spline-based interpolation is employed to increase spatial data density for training. The results demonstrate that the proposed framework can capture spatial variations associated with both lateral and vertical displacement, providing reliable position estimation under hovering conditions. This work establishes a hardware-efficient, sensorless solution for UAV wireless charging and serves as a baseline for advanced data-driven position estimation methods in dynamic WPT systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2026

Data from: Understanding the biogeochemical and spatial drivers of methane and carbon dioxide fluxes in a large temperate reservoir

This dataset contains spatially resolved measurements of CO₂ and CH₄ fluxes and associated environmental variables collected across 200 sites in Douglas Reservoir (Tennessee, USA) between July 29-August 2, 2024. Measurements include diffusive fluxes of CO₂ and CH₄, CH₄ ebullition, and biogeochemical and spatial variables such as dissolved oxygen, temperature, conductivity, chlorophyll-a, pH, water depth, and distance from the dam. Sampling was conducted using a spatially balanced design to capture longitudinal and depth-related gradients throughout the reservoir. The dataset is structured to support analyses of spatial variability, flux pathway comparisons, and modeling approaches (e.g., spatial statistics and machine learning) aimed at understanding controls on reservoir CO₂ and CH₄ fluxes and improving upscaling to whole-reservoir and regional estimates.

Neeper, Jamie [ORNL] (ORCID:0009000842342101)↗
NASA NTRS1976

Additional studies of forest classification accuracy as influenced by multispectral scanner spatial resolution

First, an analysis of forest feature signatures was used to help explain the large variation in classification accuracy that can occur among individual forest features for any one case of spatial resolution and the inconsistent changes in classification accuracy that were demonstrated among features as spatial resolution was degraded. Second, the classification rejection threshold was varied in an effort to reduce the large proportion of unclassified resolution elements that previously appeared in the processing of coarse resolution data when a constant rejection threshold was used for all cases of spatial resolution. For the signature analysis, two-channel ellipse plots showing the feature signature distributions for several cases of spatial resolution indicated that the capability of signatures to correctly identify their respective features is dependent on the amount of statistical overlap among signatures. Reductions in signature variance that occur in data of degraded spatial resolution may not necessarily decrease the amount of statistical overlap among signatures having large variance and small mean separations. Features classified by such signatures may thus continue to have similar amounts of misclassified elements in coarser resolution data, and thus, not necessarily improve in classification accuracy.

Sadowski, F. E.↗
NASA NTRS1988

Selecting a spatial resolution for estimation of per-field green leaf area index

For any application of multispectral scanner (MSS) data, a user is faced with a number of choices concerning the characteristics of the data; one of these is their spatial resolution. A pilot study was undertaken to determine the spatial resolution that would be optimal for the per-field estimation of green leaf area index (GLAI) in grassland. By reference to empirically-derived data from three areas of grassland, the suitable spatial resolution was hypothesized to lie in the lower portion of a 2-18 m range. To estimate per-field GLAI, airborne MSS data were collected at spatial resolutions of 2 m, 5 m and 10 m. The highest accuracies of per-field GLAI estimation were achieved using MSS data with spatial resolutions of 2 m and 5 m.

Curran, Paul J.↗
NASA NTRS1988

Head-mounted spatial instruments: Synthetic reality or impossible dream

A spatial instrument is defined as a display device which has been either geometrically or symbolically enhanced to better enable a user to accomplish a particular task. Research conducted over the past several years on 3-D spatial instruments has shown that perspective displays, even when viewed from the correct viewpoint, are subject to systematic viewer biases. These biases interfere with correct spatial judgements of the presented pictorial information. It is also found that deliberate, appropriate geometric distortion of the perspective projection of an image can improve user performance. These two findings raise intriguing questions concerning the design of head-mounted spatial instruments. The design of such instruments may not only require the introduction of compensatory distortions to remove the neutrally occurring biases but also may significantly benefit from the introduction of artificial distortions which enhance performance. These image manipulations, however, can cause a loss of visual-vestibular coordination and induce motion sickness. Additionally, adaptation to these manipulations is apt to be impaired by computational delays in the image display. Consequently, the design of head-mounted spatial instruments will require an understanding of the tolerable limits of visual-vestibular discord.

Ellis, Stephen R.↗
NASA NTRS1990

GRID2D/3D: A computer program for generating grid systems in complex-shaped two- and three-dimensional spatial domains. Part 2: User's manual and program listing

An efficient computer program, called GRID2D/3D, was developed to generate single and composite grid systems within geometrically complex two- and three-dimensional (2- and 3-D) spatial domains that can deform with time. GRID2D/3D generates single grid systems by using algebraic grid generation methods based on transfinite interpolation in which the distribution of grid points within the spatial domain is controlled by stretching functions. All single grid systems generated by GRID2D/3D can have grid lines that are continuous and differentiable everywhere up to the second-order. Also, grid lines can intersect boundaries of the spatial domain orthogonally. GRID2D/3D generates composite grid systems by patching together two or more single grid systems. The patching can be discontinuous or continuous. For continuous composite grid systems, the grid lines are continuous and differentiable everywhere up to the second-order except at interfaces where different single grid systems meet. At interfaces where different single grid systems meet, the grid lines are only differentiable up to the first-order. For 2-D spatial domains, the boundary curves are described by using either cubic or tension spline interpolation. For 3-D spatial domains, the boundary surfaces are described by using either linear Coon's interpolation, bi-hyperbolic spline interpolation, or a new technique referred to as 3-D bi-directional Hermite interpolation. Since grid systems generated by algebraic methods can have grid lines that overlap one another, GRID2D/3D contains a graphics package for evaluating the grid systems generated. With the graphics package, the user can generate grid systems in an interactive manner with the grid generation part of GRID2D/3D. GRID2D/3D is written in FORTRAN 77 and can be run on any IBM PC, XT, or AT compatible computer. In order to use GRID2D/3D on workstations or mainframe computers, some minor modifications must be made in the graphics part of the program; no modifications are needed in the grid generation part of the program. The theory and method used in GRID2D/3D is described.

Bailey, R. T.↗
NASA NTRS1990

GRID2D/3D: A computer program for generating grid systems in complex-shaped two- and three-dimensional spatial domains. Part 1: Theory and method

An efficient computer program, called GRID2D/3D was developed to generate single and composite grid systems within geometrically complex two- and three-dimensional (2- and 3-D) spatial domains that can deform with time. GRID2D/3D generates single grid systems by using algebraic grid generation methods based on transfinite interpolation in which the distribution of grid points within the spatial domain is controlled by stretching functions. All single grid systems generated by GRID2D/3D can have grid lines that are continuous and differentiable everywhere up to the second-order. Also, grid lines can intersect boundaries of the spatial domain orthogonally. GRID2D/3D generates composite grid systems by patching together two or more single grid systems. The patching can be discontinuous or continuous. For continuous composite grid systems, the grid lines are continuous and differentiable everywhere up to the second-order except at interfaces where different single grid systems meet. At interfaces where different single grid systems meet, the grid lines are only differentiable up to the first-order. For 2-D spatial domains, the boundary curves are described by using either cubic or tension spline interpolation. For 3-D spatial domains, the boundary surfaces are described by using either linear Coon's interpolation, bi-hyperbolic spline interpolation, or a new technique referred to as 3-D bi-directional Hermite interpolation. Since grid systems generated by algebraic methods can have grid lines that overlap one another, GRID2D/3D contains a graphics package for evaluating the grid systems generated. With the graphics package, the user can generate grid systems in an interactive manner with the grid generation part of GRID2D/3D. GRID2D/3D is written in FORTRAN 77 and can be run on any IBM PC, XT, or AT compatible computer. In order to use GRID2D/3D on workstations or mainframe computers, some minor modifications must be made in the graphics part of the program; no modifications are needed in the grid generation part of the program. This technical memorandum describes the theory and method used in GRID2D/3D.

Shih, T. I.-P.↗