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Spectral bands

About: Spectral bands is a research topic. Over the lifetime, 5406 publications have been published within this topic receiving 116689 citations.


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Journal ArticleDOI
TL;DR: In this article, three types of hyperspectral predictors were tested: optimum multiple narrow band reflectance (OMNBR), narrow band normalized difference vegetation index (NDVI), and the soil-adjusted vegetation indices.

1,132 citations

Journal ArticleDOI
TL;DR: The utility of multispectral remote sensing techniques for discriminating among materials is based on the differences that exist among their spectral properties as distinct from spectral variations that occur as a consequence of target condition and environmental factors, intrinsic spectral features that appear in the form of bands and slopes in the visible and near infrared (325 to 25 μm) bidirectional reflection spectra of minerals as mentioned in this paper.
Abstract: The utility of multispectral remote sensing techniques for discriminating among materials is based on the differences that exist among their spectral properties As distinct from spectral variations that occur as a consequence of target condition and environmental factors, intrinsic spectral features that appear in the form of bands and slopes in the visible and near infrared (325 to 25 μm) bidirectional reflection spectra of minerals (and, consequently, rocks) are caused by a variety of electronic and vibrational processes These processes, such as crystal field effects, charge‐transfer, color centers, transitions to the conduction band, and overtone and combination tone vibrational transitions are discussed and illustrated with reference to specific minerals Spectral data collected from a large selection of minerals are used to generate a “spectral signature” diagram that summarizes the optimum intrinsic information available from the spectra of particulate minerals The diagram provides a ready refe

1,121 citations

Journal ArticleDOI
TL;DR: In this paper, the infrared emission features (UIR bands) are attributed to a collection of partially hydrogenated, positively charged polycyclic aromatic hydrocarbons (PAHs) based on a spectroscopic analysis of the UIR bands.
Abstract: The unidentified infrared emission features (UIR bands) are attributed to a collection of partially hydrogenated, positively charged polycyclic aromatic hydrocarbons (PAHs). This assignment is based on a spectroscopic analysis of the UIR bands. Comparison of the observed interstellar 6.2 and 7.7-micron bands with the laboratory measured Raman spectrum of a collection of carbon-based particulates (auto exhaust) shows a very good agreement, supporting this identification. The infrared emission is due to relaxation from highly vibrationally and electronically excited states. The excitation is probably caused by UV photon absorption. The infrared fluorescence of one particular, highly vibrationally excited PAH (chrysene) is modeled. In this analysis the species is treated as a molecule rather than bulk material and the non-thermodynamic equilibrium nature of the emission is fully taken into account. From a comparison of the observed ratio of the 3.3 to 11.3-micron UIR bands with the model calculations, the average number of carbon atoms per molecule is estimated to be about 20. The abundance of interstellar PAHs is calculated to be about 2 x 10 to the -7th with respect to hydrogen.

1,089 citations

Journal ArticleDOI
TL;DR: It is shown that the cyclostationarity attribute, as it is reflected in the periodicities of (second-order) moments of the signal, can be interpreted in terms of the property that allows generation of spectral lines from the signal by putting it through a (quadratic) nonlinear transformation.
Abstract: It is shown that the cyclostationarity attribute, as it is reflected in the periodicities of (second-order) moments of the signal, can be interpreted in terms of the property that allows generation of spectral lines from the signal by putting it through a (quadratic) nonlinear transformation. The fundamental link between the spectral-line generation property and the statistical property called spectral correlation, which corresponds to the correlation that exists between the random fluctuations of components of the signal residing in distinct spectral bands, is explained. The effects on the spectral-correlation characteristics of some basic signal processing operations, such as filtering, product modulation, and time sampling, are examined. It is shown how to use these results to derive the spectral-correlation characteristics for various types of man-made signals. Some ways of exploiting the inherent spectral redundancy associated with spectral correlation to perform various signal processing tasks involving detection and estimation of highly corrupted man-made signals are described. >

1,012 citations

Journal ArticleDOI
TL;DR: The Landsat 8 Operational Land Imager (OLI) atmospheric correction algorithm is developed using the Second Simulation of the Satellite Signal in the Solar Spectrum Vectorial (6SV) model, refined to take advantage of the narrow OLI spectral bands, improved radiometric resolution and signal-to-noise.

983 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202348
202296
2021162
2020251
2019247
2018219