Paper
31 January 2002 Recognition of composition and of microphysical characteristics of aerosol clouds in multifrequency sounding
Boris G. Bravy, German K. Vasiliev, Vladimir Ya. Agroskin
Author Affiliations +
Proceedings Volume 4539, Remote Sensing of Clouds and the Atmosphere VI; (2002) https://doi.org/10.1117/12.454419
Event: International Symposium on Remote Sensing, 2001, Toulouse, France
Abstract
The recognition of composition and of microphysical characteristics of aerosol impurities is one of the most urgent tasks in monitoring of atmosphere. Some approaches to its solution are considered in the work. At first stage we were limited to five substances: fine-dispersion water and dust as background aerosol components of atmosphere; coarse- dispersion tributilamin, turbine oil and petroleum as possible impurities. Tributilamin was chosen as spectral analog of V gases. The modeling of input spectra and the recognition were carried out on 12 discrete lines in 2.9 - 4 micrometers spectral rage. As is well known, in this range the considered impurities have the pronounced spectral dependences of aerosol backscattering, the so-called spectral resonances. Spectra of aerosol backscattering for these substances were calculated with Mie theory. We applied evolutionary algorithm (genetic algorithm) and also more traditional optimization methods, namely gradient descent method, for recognition procedure. The comparative analysis of the mentioned methods was done; the concrete results of recognition and the dependence of recognition efficiency on the number of wavelength channels and on the accuracy of spectrum recording are given.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Boris G. Bravy, German K. Vasiliev, and Vladimir Ya. Agroskin "Recognition of composition and of microphysical characteristics of aerosol clouds in multifrequency sounding", Proc. SPIE 4539, Remote Sensing of Clouds and the Atmosphere VI, (31 January 2002); https://doi.org/10.1117/12.454419
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Cited by 4 scholarly publications.
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KEYWORDS
Aerosols

Atmospheric particles

Backscatter

Evolutionary algorithms

Atmospheric modeling

Air contamination

Clouds

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