Application of Physical and Neural Network Methods in Operational Water Surface Detection.

Autor:	Kuchma, M. O.
Předmět:	CONVOLUTIONAL neural networks SOLAR spectra COMMUNIST countries RADIATIVE transfer ELECTROMAGNETIC radiation
Zdroj:	Russian Meteorology & Hydrology; Apr2024, Vol. 49 Issue 4, p328-335, 8p
Abstrakt:	The paper presents some methods of satellite data preprocessing for the elimination of atmospheric effects on the electromagnetic radiation detected by the target equipment of a satellite and subsequent detection of floods in the Amur River basin. The atmospheric correction algorithm that has been used for the preprocessing is based on the use of a lookup table obtained by applying the Second Simulation of a Satellite Signal in the Solar Spectrum, which is a model of atmosphere radiative transfer. The subsequent flood detection in the Amur River basin water bodies builds on a neural network algorithm, the core of which is the upgraded U-Net. The developed algorithms for atmospheric correction and subsequent flood detection make it possible to receive information in an automatic near-real-time mode for monitoring flood conditions. Some groundwork has been made for applying the algorithm to the data of the Russian satellite instruments for spacecraft planned for launch. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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