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At least 55 records · Page 3

The use of spectral data in wheat yield estimation - An assessment of techniques explored in LACIE

The object of the paper is to assess the results of the Large Area Crop Inventory Experiment (LACIE) and closely related research on yield estimation techniques based on remote sensing variables. The exploratory research conducted during LACIE substantiated the hypothesis of yield related information contained in Landsat multispectral scanner data and indicated some of its empirical characteristics. It is noted that leaf area and possibly other foliage features can be derived from spectral data for yield estimation through agrometeorological models and that multiple vegetative and grain related features may be discernable by Landsat derived wheat spectra at different points in the crop development.

Stuff, R. G.↗

Assessing the reliability of the NIST library during routine GC-MS analyses: Structure and spectral data corroboration for 5,5-diphenyl-1,3-dioxolan-4-one during a recent OPCW proficiency test

In the field of analytical chemistry, it is the nature of the available instrumentation that makes a specific technique uniquely suited for answering a specific challenge. Often times, instruments equipped with ultrasensitive array of detectors and state-of-the-art separation components have served to highlight their invaluable role in the field. Nonetheless, it is their ultimate ability to predict the structure of an unknown material on the basis of mass spectral data that exponentially magnifies their value. Their efficacy in achieving this prediction is largely based on the size of their internal mass spectral library that conveniently can be accessed by using the software. The library can thus exhaustively correlate an unknown compound's mass spectrum to known compounds in a database and provide the analytical chemist with a probable structure for the unknown analyte. During routine analysis, it is customary that after the appropriate collection of the compound's mass spectrum, the next step involves its comparison with a compound in the instrument's National Institute of Standards and Technology (NIST) library.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning for analysis of atomic spectral data

Physics based forward models are the basis on which many experimental diagnostics are interpreted. For some diagnostics, models can be computationally expensive which precludes their use in real time analysis. Reduced models have the potential to capture sufficient physics thereby enabling the desired real time analysis. Using statistical inference and machine learning techniques the application of reduced models for inversion of atomic spectral data used to diagnose magnetic fields in a plasma will be examined. Two approaches are considered, (a) a reduction of the forward model where traditional inversion can be performed on the proxy model, and (b) a reduction of the direct inverse where parameters are a function of measured signal. The resulting inversion is sufficiently fast to be utilized in an online context for digital twinning, and ultimately real-time prediction, design, and control of plasma systems, such as tokamaks. Furthermore, these methods will be demonstrated on both simulated and experimentally measured data.

74 ATOMIC AND MOLECULAR PHYSICS↗

Rapid Chemometric Filtering of Spectral Data

A method of rapid, programmable filtering of spectral transmittance, reflectance, or fluorescence data to measure the concentrations of chemical species has been proposed. By programmable is meant that a variety of spectral analyses can readily be performed and modified in software, firmware, and/or electronic hardware, without need to change optical filters or other optical hardware of the associated spectrometers. The method is intended to enable real-time identification of single or multiple target chemical species in applications that involve high-throughput screening of multiple samples. Examples of such applications include (but are not limited to) combinatorial chemistry, flow cytometry, bead assays, testing drugs, remote sensing, and identification of targets. The basic concept of the proposed method is to perform real-time crosscorrelations of a measured spectrum with one or more analytical function(s) of wavelength that could be, for example, the known spectra of target species. Assuming that measured spectral intensities are proportional to concentrations of target species plus background spectral intensities, then after subtraction of background levels, it should be possible to determine target species concentrations from cross-correlation values. Of course, the problem of determining the concentrations is more complex when spectra of different species overlap, but the problem can be solved by use of multiple analytical functions in combination with computational techniques that have been developed previously for analyses of this type. The method is applicable to the design and operation of a spectrometer in which spectrally dispersed light is measured by means of an active-pixel sensor (APS) array. The row or column dimension of such an array is generally chosen to be aligned along the spectral-dispersion dimension, so that each pixel intercepts light in a narrow spectral band centered on a wavelength that is a known function of the pixel position. The proposed method admits of two hardware implementations for computing cross-correlations in real time.

Beaman, Gregory↗

Spectral Data Reduction via Wavelet Decomposition

The greatest advantage gained from hyperspectral imagery is that narrow spectral features can be used to give more information about materials than was previously possible with broad-band multispectral imagery. For many applications, the new larger data volumes from such hyperspectral sensors, however, present a challenge for traditional processing techniques. For example, the actual identification of each ground surface pixel by its corresponding reflecting spectral signature is still one of the most difficult challenges in the exploitation of this advanced technology, because of the immense volume of data collected. Therefore, conventional classification methods require a preprocessing step of dimension reduction to conquer the so-called "curse of dimensionality." Spectral data reduction using wavelet decomposition could be useful, as it does not only reduce the data volume, but also preserves the distinctions between spectral signatures. This characteristic is related to the intrinsic property of wavelet transforms that preserves high- and low-frequency features during the signal decomposition, therefore preserving peaks and valleys found in typical spectra. When comparing to the most widespread dimension reduction technique, the Principal Component Analysis (PCA), and looking at the same level of compression rate, we show that Wavelet Reduction yields better classification accuracy, for hyperspectral data processed with a conventional supervised classification such as a maximum likelihood method.

Kaewpijit, S.↗

Notes for the improvement of the spatial and spectral data classification method

This report examines the spatial and spectral clustering technique for the unsupervised automatic classification and mapping of earth resources satellite data, and makes theoretical analysis of the decision rules and tests in order to suggest how the method might best be applied to other flight data such as Skylab and Spacelab.

Dalton, C. C.↗

Atmosphere-biosphere exchange flux of carbon dioxide in a tallgrass prairie modeled with satellite spectral data

The estimation of the rate of net CO2 uptake of vegetated land surfaces is essential for studies of global carbon cycle. The present paper demonstrates the use of spectral reflectance data from satellite remote sensing to model net CO2 flux (NCF) of a tallgrass canopy at the Konza prairie, Kansas. A bidirectional reflectance canopy model was used to estimate seasonal changes in canopy leaf area index (LAI) from surface reflectances remotely sensed by SPOT 1 and Landsat 5 satellites. The radiation model was also coupled with leaf conductance-photosynthesis models to scale up stomatal conductance and NCF from individual leaves to canopy level according to radiation distribution inside the canopy. The satellite-data-driven model was able to closely simulate the seasonal change in LAI as well as the short-term variation of canopy LAI caused by the dry period during late July and early August in the area. Modeled canopy stomatal conductance (g(sub c)) and NCF agree with measurements within 0.16 cm/s and 0.28 mg m(exp -2)/s, respectively, during the growth season from late May to late August. In October both measured and modeled NCF turned to small negative values as canopy photosynthesis diminished and predicted LAI approached zero. In addition to data scatter, some of the differences between modeled and measured g(sub c) and NCF may be attributed to uncertainties in seasonal changes of plant physiological status that were not detected by satellite data; some of the differences were caused by inadequate description of the dependence of nighttime CO2 flux of soil respiration on near-surface turbulent mixing.

Gao, W.↗

Partial dynamical symmetry versus quasi dynamical symmetry examination within a quantum chaos analyses of spectral data for even–even nuclei

Statistical analyses of the spectral distributions of rotational bands in 51 deformed prolate even–even nuclei in the 152 ≤ A ≤ 250 mass region $R_{{4_{1}^{ + } /2_{1}^{ + } }} \ge 3.00$ are examined in terms of nearest neighbor spacing distributions. Specifically, the focus is on data for 0 + , 2 + , and 4 + energy levels of the ground, gamma, and beta bands. The chaotic behavior of the gamma band, especially the position of the $2_{\gamma }^{ + }$ band-head compared to other levels and bands, is clear. The levels are analyzed within the framework of two models, namely, a SU(3)-partial dynamical symmetry Hamiltonian and a SU(3) two-coupled quasi-dynamical symmetry Hamiltonian, with results that are further analyzed using random matrix theory. The partial and quasi dynamics both yield outcomes that are in reasonable agreement with the known experimental results. However, due to the degeneracy of the beta and gamma bands within the simplest SU(3) picture, the theory cannot be used to describe the fluctuation properties of excited bands. By changing relative weights of the different terms in the partial and quasi dynamical Hamiltonians, results are obtained that show more GOE-like statistics in the partial dynamical formalism as the strength of the pairing term is increased. Also, in the quasi-dynamical symmetry limit, more correlations are found because of the stronger couplings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Effect of DCB extraction on Mossbauer and spectral data for a Hawaiian palagonitic soil (PN-9): Iden tification of pigmentary phases

The study of palagonitic soils is an active area of research in martian geoscience because the spectral and magnetic properties of a subset are spectral and/or magnetic analogues of martian bright regions. An understanding of the composition, distribution, and mineralogy of ferric-bearing phases for palagonitic soils forms, through spectral and magnetic data, a basis for inferring the nature of ferric-bearing phases on Mars. Progress has been made in this area, but the data set is incomplete, especially with respect to the nature of pigmenting phases. The purpose of this study is to identify the nature of the pigment for Hawaiian palagonitic soil PN-9 by using extraction procedures to selectively remove iron oxide phases. This soil was collected at the same locale as samples Hawaii 34 and VOL02. All three soils are good spectral analogues for martian bright regions.

Morris, Richard V.↗

Preliminary Analysis of AIS Spectral Data Acquired from Semi-arid Shrub Communities in the Owens Valley, California

Spectral characteristics of semic-arid plant communities using 128 channel airborne imaging spectrometer (AIS) data acquired on October 30, 1984. Both field and AIS spectra of vegetation were relatively featureless and differed from substrate spectra primarily in albedo. Unvegetated sand dunes were examined to assess spectral variation resulting from topographic irregularity. Although shrub cover as low as 10% could be detected on relatively flat surfaces, such differences were obscured in more heterogeneous terrain. Sagebrush-covered fans which had been scarred by fire were studied to determine the effect of changes in plant density on reflectance. Despite noise in the atmospherically corrected spectra, these provide better resolution of differences in plant density than spectra which are solar-corrected only. A high negative correlation was found between reflectance and plant cover in areas which had uniform substrates and vegetation types. A lower correlation was found where vegetation and substrates were more diverse.

Ustin, S. L.↗

Estimating reflected and emitted components of the radiation balance using remotely-sensed spectral data from KUREX-91

The estimation of incoming and outgoing radiation streams using bidirectional spectral reflectances and bidirectional thermal emittances is described. Good agreement between measured and modeled estimates of the radiation balance is obtained. The data used were collected over selected grassland sites on the Streletskaya Steppe Reserve in Russia in July 1991. Results from this study compare well with results obtained during the first ISLSCP field experiment (FIFE) study in Kansas in 1987-89.

Blad, B. L.↗

Method for evaluating moisture tensions of soils using spectral data

A method is disclosed which permits evaluation of soil moisture utilizing remote sensing. Spectral measurements at a plurality of different wavelengths are taken with respect to sample soils and the bidirectional reflectance factor (BRF) measurements produced are submitted to regression analysis for development therefrom of predictable equations calculated for orderly relationships. Soil of unknown reflective and unknown soil moisture tension is thereafter analyzed for bidirectional reflectance and the resulting data utilized to determine the soil moisture tension of the soil as well as providing a prediction as to the bidirectional reflectance of the soil at other moisture tensions.

Peterson, John B.↗

Effect of the HITRAN 92 spectral data on the retrieval of NO2 mixing ratios from Nimbus 7 LIMS

To ensure spectral consistency when comparing Nimbus 7 Limb Infrared Monitor of the Stratosphere Experiment (LIMS) NO2 distributions with those from Atmosphere Trace Molecule Spectroscopy (ATMOS) and Upper Atmosphere Research Satellite Experiments (UARS), 1 day (May 5, 1979) of LIMS measurements were reprocessed using the NO2 line list on the HITRAN 92 tape compiled by the Airforce Geophysics Laboratory (AFGL). The revised NO2 mixing ratios are smaller by up to 20%. The decrease is not constant with height, latitude, or time of day but depends on the absolute amount of NO2 in the profile, as a result of a change in the degree of saturation for the strong NO2 spectral lines. The revised NO2 agrees better with correlative measurements and with NO2 distributions from the Stratospheric Aerosol and Gas Experiment (SAGE) and Halogen Occultation Experiment (HALOE) satellite experiments but not with those from ATMOS 85. Profiles of the day/night ratio of revised NO2 are now larger near 5 hPa. There is also some improvement between observed and modeled ozone in the upper stratosphere, when the revised nighttime NO2 profile is used as the estimate of NO(y) for the model calculations.

Remsburg, Ellis E.↗

Satellite spectral data and archaeological reconnaissance in western Greece

A Macro-geographical reconnaissance of the Western Peloponnesos adopts spectral signatures taken by Landsat-5 Thematic Mapper as a new instrument of archaeological survey in Greece. Ancient records indicate that indigenous resources contributed to the prosperity of the region. Natural resources and Ancient, Medieval, and Pre-modern Folklife in the Western Peloponnesos describes the principal lines of research. For a supervised classification of attested ancient resources, a variety of biophysical surface features were pinpointed: stone quarries, coal mines, forests of oak and silver fir, terracotta-producing clay beds, crops, and various wild but exploited shrubs such as flax.

Cooper, Frederick A.↗

Solar surface albedo estimation using remotely sensed spectral data

A solar albedo model based on converting narrow-band satellite-derived reflectance to four major spectral regions (ultraviolet, visible, near-infrared, and shortwave middle-infrared) and weighted by the relative supply of global solar radiation is studied and developed. Narrow-band to broad-band conversions within visible and near-infrared regions are shown to be accurate; however, the transformations are indicated to be surface-feature dependent. Atmospheric aerosol and illumination effects are indicated to be nearly insensitive to spectral region integrations for solar albedo estimation, but are shown to be significant factors affecting the spectral and canopy albedo. The erectophile and spherical canopy albedos were sensitive to atmospheric and illumination condition, whereas the planophile was relatively insensitive. The contribution of a shortwave middle-infrared reflectance to the canopy albedo is shown to be an important component, accounting for albedo changes to 16 percent with increasing vegetation.

Toll, David L.↗