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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Spectroscopic remote sensing for geological applications

Remote sensing is being used with increasing frequency in the development of geologic maps and in the exploration process. Spectral data from airborne and spaceborne multispectral scanners provide information on rock type and vegetation stress, important in geologic applications. Emphasis is now being placed on direct identification of materials rather than discrimination among geologic units. To do this, higher spectral resolution systems with wider spectral coverage than currently available are required. Imaging spectroscopy in the 0.4 - 14 microns region appears to be the answer.

Goetz, A. F. H.↗
NASA NTRS1996

Cloud identification using genetic algorithms and massively parallel computation

As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user's manual was written and distributed nationwide to scientists whose work might benefit from its availability. Several papers, including two journal articles, were produced.

Buckles, Bill P.↗
NASA NTRS2004

Developing an Automated Science Analysis System for Mars Surface Exploration for MSL and Beyond

We are developing an automated science analysis system that could be utilized by robotic or human explorers on Mars (or even in remote locations on Earth) to improve the quality and quantity of science data returned. Three components of this system (our rock, layer, and horizon detectors) [1] have been incorporated into the JPL CLARITY system for possible use by MSL and future Mars robotic missions. Two other components include a multi-spectral image compression (SPEC) algorithm for pancam-type images with multiple filters and image fusion algorithms that identify the in focus regions of individual images in an image focal series [2]. Recently, we have been working to combine image and spectral data, and other knowledge to identify both rocks and minerals. Here we present our progress on developing an igneous rock detection system.

Gulick, V. C.↗
NASA NTRS1973

Extraterrestrial solar energy and its possible variations

Values of the solar constant and solar spectrum have been adopted as design standards for NASA space vehicles and as engineering standards by IES/ASTM. High resolution spectral data for the UV and visible range, normalized to these standards have been derived. Applications of these results for weather analysis, air pollution, ozone production, and atmospheric energy exchange are reviewed. Indications of possible variations in solar energy, total and spectral, and their influence on the earth-atmosphere system are examined. Programs for future studies of these variations from satellites and high-altitude aircraft are discussed.

Thekaekara, M. P.↗
NASA NTRS1979

Forest Classification and Inventory System using Landsat, digital terrain, and ground sample data

Accurate timber inventory data for cost-effective forest management is the primary goal of a Forest Classification and Inventory System (FOCIS) designed to provide estimates of timber volume by species aggregated by compartments, townships, or other spatial management units. FOCIS uses Landsat spectral data, including a synthesized texture channel, and Forest Service ground sample data to produce timber volume-homogeneous classes through a two-step unsupervised clustering process. Registered digital terrain data, including derived slope angle and slope aspect channels, are used to predict species proportions through a trend surface model, again using ground sample data for model calibration. In the final stage of FOCIS, volume estimates and predicted species proportions are merged and aggregated to yield timber volumes by species within management areas.

Strahler, A. H.↗
NASA NTRS1995

Toward Soil Spatial Information Systems (SSIS) for global modeling and ecosystem management

The general objective is to conduct research to contribute toward the realization of a world soils and terrain (SOTER) database, which can stand alone or be incorporated into a more complete and comprehensive natural resources digital information system. The following specific objectives are focussed on: (1) to conduct research related to (a) translation and correlation of different soil classification systems to the SOTER database legend and (b) the inferfacing of disparate data sets in support of the SOTER Project; (2) to examine the potential use of AVHRR (Advanced Very High Resolution Radiometer) data for delineating meaningful soils and terrain boundaries for small scale soil survey (range of scale: 1:250,000 to 1:1,000,000) and terrestrial ecosystem assessment and monitoring; and (3) to determine the potential use of high dimensional spectral data (220 reflectance bands with 10 m spatial resolution) for delineating meaningful soils boundaries and conditions for the purpose of detailed soil survey and land management.

Baumgardner, Marion F.↗
DOE OSTI2015

Networked Gamma Radiation Detection System for Rapid Tactical Response

A networked gamma radiation detection system with directional sensitivity and energy spectral data acquisition capability is being developed by the National Security Technologies, LLC, to support the close and intense tactical engagement of law enforcement who carry out counterterrorism missions. In the proposed design, three clusters of 2' × 4' × 16' sodium iodide crystals (4 each) with digiBASE-E (for list mode data collection) would be placed on the passenger side of a minivan. To enhance localization and facilitate rapid identification of isotopes, advanced smart realtime localization and radioisotope identification algorithms like WAVRAD (wavelet-assisted variance reduction for anomaly detection) and NSCRAD (nuisance-rejection spectral comparison ratio anomaly detection) will be incorporated. We are testing a collection of algorithms and analysis on the problem of radiation detection with a distributed sensor network, examining such a network’s associated characteristics, and also the trade-offs between false positive alarm rates, true positive alarm rates, and time to detect multiple radiation sources in a large area. Empirical and simulation analyses of critical system parameters, such as number of sensors, sensor placement, and sensor response functions, are being examined. This networked system will provide an integrated radiation detection architecture and framework with (i) a large nationally recognized search database equivalent that would help generate a common operational picture in a major radiological crisis; (ii) a robust reach back connectivity for search data to be evaluated by home teams; and, finally, (iii) a possibility of integrating search data from multi-agency responders.

false alarm rate↗
DOE OSTI2019

Orientational Dependence of Cofacial Porphyrin–Quinone Electronic Interactions within the Strong Coupling Regime

We examine the relative magnitudes of electronic coupling HDA in two face-to-face rigid and diastereomeric (porphinato)zinc(II)–quinone (PZn–Q) as-semblies, 1β-ZnA and 1β-ZnB, in which the six quinonyl carbon atoms lie in virtually identical arrangements relative to the PZn plane at sub-van der Waals donor–acceptor (D–A) interplanar separations. Steady-state and time-resolved transient optical data and computational studies show that minor differences in relative D–A cofacial orientation give rise to disparate H DA magnitudes for both photoinduced charge separation (CS) and thermal charge recombination (CR). Here, time-dependent density functional theory (TDDFT) computations illuminate the nature of direct charge transfer states and the electronic structural factors that give rise to these differential H DA s. These data show more extensive mixing of locally excited (LE) and CS states in 1β-ZnA relative to 1β-ZnB and that these H DA differences track the magnitudes of electronic coupling matrix elements determined from steady-state electronic spectral data and thermal CR rate constants measured via pump–probe spectroscopy. Collectively, this work shows that electron transfer dynamics may be manipulated in cofacial D–A systems, even at sub-van der Waals contact, provided that conformational rigidity precludes structural fluctuations that modulate D–A interactions on the charge transfer time scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1972

Application of stepwise multiple regression techniques to inversion of Nimbus 'IRIS' observations.

Exploratory studies with Nimbus-3 infrared interferometer-spectrometer (IRIS) data indicate that, in addition to temperature, such meteorological parameters as geopotential heights of pressure surfaces, tropopause pressure, and tropopause temperature can be inferred from the observed spectra with the use of simple regression equations. The technique of screening the IRIS spectral data by means of stepwise regression to obtain the best radiation predictors of meteorological parameters is validated. The simplicity of application of the technique and the simplicity of the derived linear regression equations - which contain only a few terms - suggest usefulness for this approach. Based upon the results obtained, suggestions are made for further development and exploitation of the stepwise regression analysis technique.

Ohring, G.↗
NASA NTRS1971

Determining density of maize canopy. 2: Airborne multispectral scanner data

Multispectral scanner data were collected in two flights over a light colored soil background cover plot at an altitude of 305 m. Energy in eleven reflective wavelength band from 0.45 to 2.6 microns was recorded. Four growth stages of maize (Zea mays L.) gave a wide range of canopy densities for each flight date. Leaf area index measurements were taken from the twelve subplots and were used as a measure of canopy density. Ratio techniques were used to relate uncalibrated scanner response to leaf area index. The ratios of scanner data values for the 0.72 to 0.92 micron wavelength band over the 0.61 to 0.70 micron wavelength band were calculated for each plot. The ratios related very well to leaf area index for a given flight date. The results indicated that spectral data from maize canopies could be of value in determining canopy density.

Stoner, E. R.↗
NASA NTRS1986

Atropine unmasks bed-rest effect - A spectral analysis of cardiac interbeat intervals

Heart rate spectral data obtained for 10 male subjects between 35-49 years following orthostatic tolerance testing with lower body negative pressure prebed rest and after 7-10 days of bed rest, while on placebo and after intravenous atropine are analyzed. Comparison of the spectral atropine rms for subjects prebed rest and after bed rest reveal a decrease from 63 + or - 24 ms to 40 + or - 23 ms. It is observed that heart rate interval variability for subjects after bed rest and with atropine is reduced; the heart rate at bed rest with atropine is increased from 70.4 + or - 12.4 beats/min prebed rest to 83.7 + or - 18.9 beats/min; and the exercise tolerance time for subjects in the atropine prebed-rest phase (658 + or - 352 s) is higher than the bed-rest phase (505 + or - 252 s). It is noted that bed rest impairs the cardiovascular capacity to adaptively modulate physiological responses, atropine exposes bed-rest deconditioning effects, and spectral analysis is useful for studying the effects of bed-rest deconditioning on cardiac dynamics.

Goldberger, Ary L.↗
DOE OSTI2021

A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression

Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices. One application of PLSR enables leaf traits to be estimated from hyperspectral optical reflectance data, facilitating rapid, high-throughput, non-destructive plant phenotyping. This technique is of interest and importance in a wide range of contexts including crop breeding and ecosystem monitoring. The lack of a consensus in the literature on how to perform PLSR means that interpreting model results can be challenging, applying existing models to novel datasets can be impossible, and unknown or undisclosed assumptions can lead to incorrect or spurious predictions. We address this lack of consensus by proposing best practices for using PLSR to predict plant traits from leaf-level hyperspectral data, including a discussion of when PLSR is applicable, and recommendations for data collection. Further, we provide a tutorial to demonstrate how to develop a PLSR model, in the form of an R script accompanying this manuscript. This practical guide will assist all those interpreting and using PLSR models to predict leaf traits from spectral data, and advocates for a unified approach to using PLSR for predicting traits from spectra in the plant sciences.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Analysis of STIS time-tag data

Very high time resolution data can be obtained from the Space Telescope Imaging Spectrograph (STIS) Multi-Anode Microchannel Array (MAMA) detectors using the time-tag observing mode. In this mode, the photon events are not accumulated onboard the spacecraft. Instead, each event is recorded internally and transmitted to the ground as an X and Y location with an event time. Event times are recorded in units of 125 microseconds. Analysis of STIS Crab Pulsar data demonstrates that a time resolution of approaching 125 microseconds can be achieved. Furthermore, the time-tag observing mode has been demonstrated to be a very powerful diagnostic tool and can be used to increase the resolution of both imaging and spectral data.

Lindler, Don J.↗
NASA NTRS2007

Processing AIRS Scientific Data Through Level 2

The Atmospheric Infrared Spectrometer (AIRS) Science Processing System (SPS) is a collection of computer programs, denoted product generation executives (PGEs), for processing the readings of the AIRS suite of infrared and microwave instruments orbiting the Earth aboard NASA s Aqua spacecraft. AIRS SPS at an earlier stage of development was described in "Initial Processing of Infrared Spectral Data' (NPO-35243), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 39. To recapitulate: Starting from level 0 (representing raw AIRS data), the PGEs and their data products are denoted by alphanumeric labels (1A, 1B, and 2) that signify the successive stages of processing. The cited prior article described processing through level 1B (the level-2 PGEs were not yet operational). The level-2 PGEs, which are now operational, receive packages of level-1B geolocated radiance data products and produce such geolocated geophysical atmospheric data products such as temperature and humidity profiles. The process of computing these geophysical data products is denoted "retrieval" and is quite complex. The main steps of the process are denoted microwave-only retrieval, cloud detection and cloud clearing, regression, full retrieval, and rapid transmittance algorithm.

Oliphant, Robert↗
NASA NTRS2011

Airborne Observation of the Hayabusa Sample Return Capsule Re-Entry

NASA Ames Research Center and the SETI Institute collaborated on an effort to observe the Earth re-entry of the Japan Aerospace Exploration Agency's Hayabusa sample return capsule. Hayabusa was an asteroid exploration mission that retrieved a sample from the near-Earth asteroid Itokawa. Its sample return capsule re-entered over the Woomera Prohibited Area in southern Australia on June 13, 2010. Being only the third sample return mission following NASA's Genesis and Stardust missions, Hayabusa's return was a rare opportunity to collect aerothermal data from an atmospheric entry capsule returning at superorbital speeds. NASA deployed its DC-8 airborne laboratory and a team of international researchers to Australia for the re-entry. For approximately 70 seconds, spectroscopic and radiometric imaging instruments acquired images and spectra of the capsule, its wake, and destructive re-entry of the spacecraft bus. Once calibrated, spectra of the capsule will be interpreted to yield data for comparison with and validation of high fidelity and engineering simulation tools used for design and development of future atmospheric entry system technologies. A brief summary of the Hayabusa mission, the preflight preparations and observation mission planning, mission execution, and preliminary spectral data are documented.

Spectroscopy↗
DOE OSTI2015

Networked Gamma Radiation System for Tactical Deployment

A networked gamma radiation detection system with directional sensitivity and energy spectral data acquisition capability is being developed by the National Security Technologies, LLC, Remote Sensing Laboratory to support the close and intense tactical engagement of law enforcement who carry out counterterrorism missions. In the proposed design, three clusters of 2" × 4" × 16" sodium iodide crystals (4 each) with digiBASE-E (for list mode data collection) would be placed on the passenger side of a minivan. To enhance localization and facilitate rapid identification of isotopes, advanced smart real-time localization and radioisotope identification algorithms like WAVRAD (wavelet-assisted variance reduction for anomaly detection) and NSCRAD (nuisance-rejection spectral comparison ratio anomaly detection) will be incorporated. We will test a collection of algorithms and analysis that centers on the problem of radiation detection with a distributed sensor network. We will study the basic characteristics of a radiation sensor network and focus on the trade-offs between false positive alarm rates, true positive alarm rates, and time to detect multiple radiation sources in a large area. Empirical and simulation analyses of critical system parameters, such as number of sensors, sensor placement, and sensor response functions, will be examined. This networked system will provide an integrated radiation detection architecture and framework with (i) a large nationally recognized search database equivalent that would help generate a common operational picture in a major radiological crisis; (ii) a robust reach back connectivity for search data to be evaluated by home teams; and, finally, (iii) a possibility of integrating search data from multi-agency responders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Functional Data Analysis for Extracting the Intrinsic Dimensionality of Spectra: Application to Chemical Homogeneity in the Open Cluster M67

High-resolution spectroscopic surveys of the Milky Way have entered the Big Data regime and have opened avenues for solving outstanding questions in Galactic archeology. However, exploiting their full potential is limited by complex systematics, whose characterization has not received much attention in modern spectroscopic analyses. In this work, we present a novel method to disentangle the component of spectral data space intrinsic to the stars from that due to systematics. Using functional principal component analysis on a sample of 18,933 giant spectra from APOGEE, we find that the intrinsic structure above the level of observational uncertainties requires ≈10 functional principal components (FPCs). Our FPCs can reduce the dimensionality of spectra, remove systematics, and impute masked wavelengths, thereby enabling accurate studies of stellar populations. To demonstrate the applicability of our FPCs, we use them to infer stellar parameters and abundances of 28 giants in the open cluster M67. We employ Sequential Neural Likelihood, a simulation-based Bayesian inference method that learns likelihood functions using neural density estimators, to incorporate non-Gaussian effects in spectral likelihoods. By hierarchically combining the inferred abundances, we limit the spread of the following elements in M67: Fe ≲ 0.02 dex; C ≲ 0.03 dex; O, Mg, Si, Ni ≲ 0.04 dex; Ca ≲ 0.05 dex; N, Al ≲ 0.07 dex (at 68% confidence). Our constraints suggest a lack of self-pollution by core-collapse supernovae in M67, which has promising implications for the future of chemical tagging to understand the star formation history and dynamical evolution of the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

Atmospheric effects in multispectral remote sensor data

The problem of radiometric variations in multispectral remote sensing data which occur as a result of a change in geometric and environmental factors is studied. The case of spatially varying atmospheres is considered and the effect of atmospheric scattering is analyzed for realistic conditions. Emphasis is placed upon a simulation of LANDSAT spectral data for agricultural investigations over the United States. The effect of the target-background interaction is thoroughly analyzed in terms of various atmospheric states, geometric parameters, and target-background materials. Results clearly demonstrate that variable atmospheres can alter the classification accuracy and that the presence of various backgrounds can change the effective target radiance by a significant amount. A failure to include these effects in multispectral data analysis will result in a decrease in the classification accuracy.

Turner, R. E.↗