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Proceedings Paper

The optimal planning methods of remote sensing experiment in IR-range for the satellite meteorology problems
Author(s): Nikolay V. Uvarov; Anton A. Sokolov
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Paper Abstract

The number of narrow-band spectral channels that are used in satellite instruments has been increasing to hundreds and even thousands, due to recent developments in satellite meteorology. They measure radiation in wide ranges: from ultra-violet to distant infra-red. The comparison of various approaches for selection of the most informative channels represents a certain scientific and practical interest. In our work the techniques of the optimal choice are considered for spectral channels with the fixed and variable widths. Practically, all known methods of the inverse problems solution use the certain a-priori information on required parameters. The following methods of the optimal planning were used for a remote sensing satellites experiments: DRM(analysis of Data resolution Matrix), Weighted functions (Jacobians analyzing), Iterations (selection of the satellite channels is defined by Entropy Reduction), combined channel technique (spectral channel with variable width - based on maximization of the determinant of Fishers information matrix). The methods of the best linear estimation and variational technique were used to solve the inverse problem. The proposed technique was used for remote sensing of the atmosphere (temperature and humidity profiles) and surface parameters (sea surface temperature).

Paper Details

Date Published: 24 May 2018
PDF: 9 pages
Proc. SPIE 10679, Optics, Photonics, and Digital Technologies for Imaging Applications V, 106791P (24 May 2018); doi: 10.1117/12.2306733
Show Author Affiliations
Nikolay V. Uvarov, EOS Data Analytics, Inc. (Ukraine)
Anton A. Sokolov, Lab. l'Atmosphère, CNRS, Univ. du Littoral Côte d’Opale (France)

Published in SPIE Proceedings Vol. 10679:
Optics, Photonics, and Digital Technologies for Imaging Applications V
Peter Schelkens; Touradj Ebrahimi; Gabriel Cristóbal, Editor(s)

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