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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

BOREAS Level-4b AVHRR-LAC Ten-Day Composite Images: At-sensor Radiance

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Manitoba Remote Sensing Center (MRSC) and BOREAS Information System (BORIS) personnel acquired, processed, and archived data from the Advanced Very High Resolution Radiometer (AVHRR) instruments on the National Oceanic and Atmospheric Administration (NOAA-11) and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4b data are gridded, 10-day composites of at-sensor radiance values produced from sets of single-day images. Temporally, the 10- day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files.

Cihlar, Josef↗
NASA NTRS2019

Forcing Factors Affecting Sea Level Changes at the Coast

We review the characteristics of sea level variability at the coast focussing on how it differs from the variability in the nearby deep ocean. Sea level variability occurs on all timescales, with processes at higher frequencies tending to have a larger magnitude at the coast due to resonance and other dynamics. In the case of some processes, such as the tides, the presence of the coast and the shallow waters of the shelves results in the processes being considerably more complex than offshore. However, ‘coastal variability’ should not always be considered as ‘short spatial scale variability’ but can be the result of signals transmitted along the coast from 1000s km away. Fortunately, thanks to tide gauges being necessarily located at the coast, many aspects of coastal sea level variability can be claimed to be better understood than those in the deep ocean. Nevertheless, certain aspects of coastal variability remain under-researched, including how changes in some processes (e.g., wave setup, river runoff) may have contributed to the historical mean sea level records obtained from tide gauges which are now used routinely in large-scale climate research.

Philip L Woodworth↗
NASA NTRS2013

A Lightweight I/O Scheme to Facilitate Spatial and Temporal Queries of Scientific Data Analytics

In the era of petascale computing, more scientific applications are being deployed on leadership scale computing platforms to enhance the scientific productivity. Many I/O techniques have been designed to address the growing I/O bottleneck on large-scale systems by handling massive scientific data in a holistic manner. While such techniques have been leveraged in a wide range of applications, they have not been shown as adequate for many mission critical applications, particularly in data post-processing stage. One of the examples is that some scientific applications generate datasets composed of a vast amount of small data elements that are organized along many spatial and temporal dimensions but require sophisticated data analytics on one or more dimensions. Including such dimensional knowledge into data organization can be beneficial to the efficiency of data post-processing, which is often missing from exiting I/O techniques. In this study, we propose a novel I/O scheme named STAR (Spatial and Temporal AggRegation) to enable high performance data queries for scientific analytics. STAR is able to dive into the massive data, identify the spatial and temporal relationships among data variables, and accordingly organize them into an optimized multi-dimensional data structure before storing to the storage. This technique not only facilitates the common access patterns of data analytics, but also further reduces the application turnaround time. In particular, STAR is able to enable efficient data queries along the time dimension, a practice common in scientific analytics but not yet supported by existing I/O techniques. In our case study with a critical climate modeling application GEOS-5, the experimental results on Jaguar supercomputer demonstrate an improvement up to 73 times for the read performance compared to the original I/O method.

Temporal Queries↗
NASA NTRS1978

Onboard processing for future space-borne imaging systems

There is a strong rationale for increasing the rate of information return from imaging class experiments aboard both terrestrial and planetary spacecraft. Future imaging systems will be designed with increased spatial resolution, broader spectral range and more spectral channels (or higher spectral resolution). The data rate implied by these improved performance characteristics can be expected to grow more rapidly than the projected telecommunications capability. One solution to this dilemma is the use of improved onboard data processing. The use of onboard classification processing in a multispectral imager can result in orders of magnitude increase in information transfer for very specific types of imaging tasks. Several of these processing functions are included in the conceptual design of an Infrared Multispectral Imager which would map the spatial distribution of characteristic geologic features associated with deposits of economic minerals.

Wellman, J. B.↗
NASA NTRSDate not supplied

Deep Learning System for Efficient Processing of Geostationary Satellite Imagery

Improved capabilities of Earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. Further, a large majority of archived datasets generated by scientific processing is never used. This motivates the development of an efficient machine learning system for end-to-end processing of multi-level satellite datasets, from level 1 top of atmosphere observations to user friendly environmental variables of interest. Using current generation geostationary satellites GOES-16/17 (NOAA/NASA), and Himawari-8/9 (JAXA), we present an interchangeable set of machine models to perform spectral adjustment among sensors, physical model emulation, LEO-GEO emulation, and optical flow in a high performance computing environment. We use these tools on the NASA Earth eXchange (NEX) to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate surface reflectance, surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Thomas Vandal↗
NASA NTRS2019

Forcing Factors Affecting Sea Level Changes at the Coast

We review the characteristics of sea level variability at the coast focussing on how it differs from the variability in the nearby deep ocean. Sea level variability occurs on all timescales, with processes at higher frequencies tending to have a larger magnitude at the coast due to resonance and other dynamics. In the case of some processes, such as the tides, the presence of the coast and the shallow waters of the shelves results in the processes being considerably more complex than offshore. However, ‘coastal variability’ should not always be considered as ‘short spatial scale variability’ but can be the result of signals transmitted along the coast from 1000s km away. Fortunately, thanks to tide gauges being necessar-ily located at the coast, many aspects of coastal sea level variability can be claimed to be better understood than those in the deep ocean. Nevertheless, certain aspects of coastal variability remain under-researched, including how changes in some processes (e.g., wave setup, river runoff) may have contributed to the historical mean sea level records obtained from tide gauges which are now used routinely in large-scale climate research.

Philip L. Woodworth↗
NASA NTRS1992

Imaging solar flares in hard X-rays using Fourier telescopes

The sun emits hard X-rays (above 10 keV) during solar flares. Imaging hard X-ray sources on the sun with spatial resolutions on the order of 1-5 arcsec and integration times of 1 sec will provide greater insight into the energy release processes during a solar flare. In these events, tremendous amounts of energy stored in the solar magnetic field are rapidly released leading to emission across the electromagnetic spectrum. Two Fourier telescope designs, a spatial modulation collimator and a rotating modulation collimator, were developed to image the full sun in hard X-rays (10-100 keV) in an end-to-end simulation. Emission profiles were derived for two hard X-ray solar flare models taken from the current solar theoretical literature and used as brightness distributions for the telescope simulations. Both our telescope models, tailored to image solar sources, were found to perform equally well, thus offering the designer significant flexibility in developing systems for space-based platforms. Given sufficient sensitive areas, Fourier telescopes are promising concepts for imaging solar hard X-rays.

Campbell, Jonathan W.↗
NASA NTRS1997

Multitemporal and Multiscaled Fractal Analysis of Landsat Satellite Data Using the Image Characterization and Modeling System (ICAMS)

The Image Characterization And Modeling System (ICAMS) is a public domain software package that is designed to provide scientists with innovative spatial analytical tools to visualize, measure, and characterize landscape patterns so that environmental conditions or processes can be assessed and monitored more effectively. In this study ICAMS has been used to evaluate how changes in fractal dimension, as a landscape characterization index, and resolution, are related to differences in Landsat images collected at different dates for the same area. Landsat Thematic Mapper (TM) data obtained in May and August 1993 over a portion of the Great Basin Desert in eastern Nevada were used for analysis. These data represent contrasting periods of peak "green-up" and "dry-down" for the study area. The TM data sets were converted into Normalized Difference Vegetation Index (NDVI) images to expedite analysis of differences in fractal dimension between the two dates. These NDVI images were also resampled to resolutions of 60, 120, 240, 480, and 960 meters from the original 30 meter pixel size, to permit an assessment of how fractal dimension varies with spatial resolution. Tests of fractal dimension for two dates at various pixel resolutions show that the D values in the August image become increasingly more complex as pixel size increases to 480 meters. The D values in the May image show an even more complex relationship to pixel size than that expressed in the August image. Fractal dimension for a difference image computed for the May and August dates increase with pixel size up to a resolution of 120 meters, and then decline with increasing pixel size. This means that the greatest complexity in the difference images occur around a resolution of 120 meters, which is analogous to the operational domain of changes in vegetation and snow cover that constitute differences between the two dates.

Quattrochi, Dale A.↗
NASA NTRS1991

Color heterogeneity of the surface of Phobos - Relationships to geologic features and comparison to meteorite analogs

Color ratio images created from multispectral observations of Phobos are analyzed in order to characterize the spectral properties of Phobos' surface, to assess their spatial distributions and relationships with geologic features, and to compare Phobos' surface materials with possible meteorite analogs. Data calibration and processing is briefly discussed, and the observed spectral properties of Phobos and their lateral variations are examined. Attention is then given to the color properties of different types of impact craters, the origin of lateral variations in surface color, the relation between the spatial distribution of color properties and independently identifiable geologic features, and the relevance of color variation spatial distribution to the origin of the grooves.

Murchie, Scott L.↗
NASA NTRS1993

Systematic chemical variations in large 3AB iron meteorites: Clues to core crystallization

Analysis of numerous individual iron meteorites have shown that fractional crystallization of iron cores result in variations in chemical concentration of the solid core which span several orders of magnitude. The magnitude and direction of the resulting spatial gradients in the core can provide clues to the physical nature of the core crystallization process. We have analyzed suites of samples from three large 3AB irons (Cape York, 58t; Chupaderos, 24t; Morito, 10t) in order to estimate local chemical gradients. Initial results for the concentrations of Ge, Pd, Pt (Massey group), Ir, Au, As, Co, Os, and Rh (Dalhouse group), and P (Arizona group) show significant ranges among the Cape York and Chupaderos samples and marginally significant ranges among the Morito samples. Measurements of Au, Ir, Co, Ni, Cu, Ga, As, W, Re (from UCLA) and Ni and Co (Arizona group) are in progress. We find a spatial Ir gradient in Chupaderos with a magnitude similar to the one reported for Agpalilik (Cape York iron) by Esbensen et al.

Haack, H.↗
NASA NTRS1975

Laser Doppler velocimeter system simulation for sensing aircraft wake vortices. Part 2: Processing and analysis of LDV data (for runs 1023 and 2023)

A data analysis program constructed to assess LDV system performance, to validate the simulation model, and to test various vortex location algorithms is presented. Real or simulated Doppler spectra versus range and elevation is used and the spatial distributions of various spectral moments or other spectral characteristics are calculated and displayed. Each of the real or simulated scans can be processed by one of three different procedures: simple frequency or wavenumber filtering, matched filtering, and deconvolution filtering. The final output is displayed as contour plots in an x-y coordinate system, as well as in the form of vortex tracks deduced from the maxima of the processed data. A detailed analysis of run number 1023 and run number 2023 is presented to demonstrate the data analysis procedure. Vortex tracks and system range resolutions are compared with theoretical predictions.

Meng, J. C. S.↗
NASA NTRS2009

Spatial Modulation Improves Performance in CTIS

Suitably formulated spatial modulation of a scene imaged by a computed-tomography imaging spectrometer (CTIS) has been found to be useful as a means of improving the imaging performance of the CTIS. As used here, "spatial modulation" signifies the imposition of additional, artificial structure on a scene from within the CTIS optics. The basic principles of a CTIS were described in "Improvements in Computed- Tomography Imaging Spectrometry" (NPO-20561) NASA Tech Briefs, Vol. 24, No. 12 (December 2000), page 38 and "All-Reflective Computed-Tomography Imaging Spectrometers" (NPO-20836), NASA Tech Briefs, Vol. 26, No. 11 (November 2002), page 7a. To recapitulate: A CTIS offers capabilities for imaging a scene with spatial, spectral, and temporal resolution. The spectral disperser in a CTIS is a two-dimensional diffraction grating. It is positioned between two relay lenses (or on one of two relay mirrors) in a video imaging system. If the disperser were removed, the system would produce ordinary images of the scene in its field of view. In the presence of the grating, the image on the focal plane of the system contains both spectral and spatial information because the multiple diffraction orders of the grating give rise to multiple, spectrally dispersed images of the scene. By use of algorithms adapted from computed tomography, the image on the focal plane can be processed into an image cube a three-dimensional collection of data on the image intensity as a function of the two spatial dimensions (x and y) in the scene and of wavelength (lambda). Thus, both spectrally and spatially resolved information on the scene at a given instant of time can be obtained, without scanning, from a single snapshot; this is what makes the CTIS such a potentially powerful tool for spatially, spectrally, and temporally resolved imaging. A CTIS performs poorly in imaging some types of scenes in particular, scenes that contain little spatial or spectral variation. The computed spectra of such scenes tend to approximate correct values to within acceptably small errors near the edges of the field of view but to be poor approximations away from the edges. The additional structure imposed on a scene according to the present method enables the CTIS algorithms to reconstruct acceptable approximations of the spectral data throughout the scene.

Bearman, Gregory H.↗
NASA NTRS1989

Jackson State University's Center for Spatial Data Research and Applications: New facilities and new paradigms

Jackson State University recently established the Center for Spatial Data Research and Applications, a Geographical Information System (GIS) and remote sensing laboratory. Taking advantage of new technologies and new directions in the spatial (geographic) sciences, JSU is building a Center of Excellence in Spatial Data Management. New opportunities for research, applications, and employment are emerging. GIS requires fundamental shifts and new demands in traditional computer science and geographic training. The Center is not merely another computer lab but is one setting the pace in a new applied frontier. GIS and its associated technologies are discussed. The Center's facilities are described. An ARC/INFO GIS runs on a Vax mainframe, with numerous workstations. Image processing packages include ELAS, LIPS, VICAR, and ERDAS. A host of hardware and software peripheral are used in support. Numerous projects are underway, such as the construction of a Gulf of Mexico environmental data base, development of AI in image processing, a land use dynamics study of metropolitan Jackson, and others. A new academic interdisciplinary program in Spatial Data Management is under development, combining courses in Geography and Computer Science. The broad range of JSU's GIS and remote sensing activities is addressed. The impacts on changing paradigms in the university and in the professional world conclude the discussion.

Davis, Bruce E.↗
NASA NTRSDate not supplied

Fabrication and Characterization of A Lunar Simulant-Based Sintered Construction Material

In-situ resource utilization (ISRU) is critical to enable future efforts to have a long-term human presence on the Moon as well as Mars. ISRU technologies are being developed for radiation protection, dust mitigation, thermal insulation, and other applications. One such ISRU technology for creating construction materials out of lunar and Martian regolith is sintering, which is a thermal-based construction process that bonds finely grained material together at temperatures below the melting point. However, the conditions employed during the sintering, such as temperature, atmospheric composition, duration of the process, and pressure, can have a significant impact on the quality and strength of the resulting materials. In parallel, the development of methods for characterizing the quality, porosity, density, and other properties of these materials is critical. X-ray computed tomography (X-ray CT) can image large changes in density within a material, such as the presence of pores throughout an otherwise uniform medium, with relatively high spatial resolution. Similarly, Terahertz time-domain spectroscopic (THz-TDS) imaging is sensitive to density variations within samples, but is restricted to non-conducting materials. Specifically, previous work has shown that the refractive index (n eff ) values obtained through the analysis of THz-TDS images increases with increasing density within plastic samples. Even further, this work showed that it is possible to create a calibration curve for a given material from samples of different, but known density, which can enable one to directly convert n eff to density for samples having the same composition, but unknown density. Here, we report on the fabrication of a lunar simulant-based sintered construction material using vacuum hot pressed (VHP) sintering, then show X-ray CT and THz-TDS imaging results of the sample, which show spatial variations in the material. This has important implications for efforts to improve these types of lunar construction material processes and verify the quality of these materials in terms of consolidation. To the best of our knowledge, there is no previous work utilizing VHP sintering to make lunar simulant-based construction materials or exploring the feasibility of THz imaging to spatially map the density variation through a lunar simulant-based construction material.

Terahertz time-domain spectroscopic imaging↗
NASA NTRS2012

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

Tan, Bin↗
NASA NTRS1993

Optical beam forming techniques for phased array antennas

Conventional phased array antennas using waveguide or coax for signal distribution are impractical for large scale implementation on satellites or spacecraft because they exhibit prohibitively large system size, heavy weight, high attenuation loss, limited bandwidth, sensitivity to electromagnetic interference (EMI) temperature drifts and phase instability. However, optical beam forming systems are smaller, lighter, and more flexible. Three optical beam forming techniques are identified as applicable to large spaceborne phased array antennas. They are (1) the optical fiber replacement of conventional RF phased array distribution and control components, (2) spatial beam forming, and (3) optical beam splitting with integrated quasi-optical components. The optical fiber replacement and the spatial beam forming approaches were pursued by many organizations. Two new optical beam forming architectures are presented. Both architectures involve monolithic integration of the antenna radiating elements with quasi-optical grid detector arrays. The advantages of the grid detector array in the optical process are the higher power handling capability and the dynamic range. One architecture involves a modified version of the original spatial beam forming approach. The basic difference is the spatial light modulator (SLM) device for controlling the aperture field distribution. The original liquid crystal light valve SLM is replaced by an optical shuffling SLM, which was demonstrated for the 'smart pixel' technology. The advantages are the capability of generating the agile beams of a phased array antenna and to provide simultaneous transmit and receive functions. The second architecture considered is the optical beam splitting approach. This architecture involves an alternative amplitude control for each antenna element with an optical beam power divider comprised of mirrors and beam splitters. It also implements the quasi-optical grid phase shifter for phase control and grid amplifier for RF power. The advantages are no SLM is required for this approach, and the complete antenna system is capable of full monolithic integration.

Wu, Te-Kao↗
NASA NTRS1995

Combined hyperspatial and hyperspectral imaging spectrometer concept

There is a user need for increasing spatial and spectral resolution in Earth Observation (EO) optical instrumentation. Higher spectral resolution will be achieved by the introduction of spaceborne imaging spectrometers. Higher spatial resolutions of 1 - 3m will be achieved also, but at the expense of sensor redesign, higher communications bandwidth, high data processing volumes, and therefore, at the risk of time delays due to large volume data-handling bottlenecks. This paper discusses a design concept whereby the hyperspectral properties of a spaceborne imaging spectrometer can be used to increase the image spatial resolution, without such adverse cost impact.

Burke, Ian↗
NASA NTRS2019

Redefining Temperate Forest Responses to Climate and Disturbance in the Eastern United States: New Insights at the Mesoscale

Climate and disturbance alter forest dynamics, from individual trees to biomes and from years to millennia, leaving legacies that vary with local, meso and macroscales. Motivated by recent insights in temperate forests, we argue that temporal and spatial extents equivalent to that of the underlying drivers are necessary to characterize forest dynamics across scales. We focus specifically on characterizing mesoscale forest dynamics because they bridge fine‐scale (local) processes and the continental scale (macrosystems) in ways that are highly relevant for climate change science and ecosystem management. We revisit ecological concepts related to spatial and temporal scales and discuss approaches to gain a better understanding of climate–forest dynamics across scales.

climate↗