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Multispectral Optical Reflectometry Method of Forest Resource Monitoring L&E, Vol.30, No.1, 2022

Light & Engineering 30 (1)

Volume 30
Date of publication 02/24/2022
Pages 51–59

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Multispectral Optical Reflectometry Method of Forest Resource Monitoring L&E, Vol.30, No.1, 2022
Articles authors:
Mikhail L. Belov, Alexei M. Belov, Victor A. Gorodnichev, Sergey V. Alkov

Mikhail L. Belov, Doctor of Technical Sciences, Professor. He graduated in 1973 from Bauman Moscow State Technical University. At present, he is the Professor at the same university and member of Editorial Board of the journal Light & Engineering Journal. His research interests are optical and optoelectronic devices and systems

Alexei M. Belov, engineer. In 1997, he graduated from the Moscow Power Engineering Institute (MEI). At present, he is an engineer at Radio-electronics and Laser Engineering Research Institute of Bauman MSTU. His research interests: mathematical modelling of natural environment monitoring systems

Victor A. Gorodnichev, Dr. of Tech. Sciences, Senior Researcher. In 1976, he graduated from Lomonosov Moscow State University. At present, he is the Department Head of NRI of Radioelectronics and Laser Equipment of N.E. Bauman MSTU. His research interests: optical and optoelectronic devices and systems

Sergey V. Alkov, Ph.D. In 1978, he graduated from Kursk Polytechnic Institute. At present, he is the Head of the Faculty of Radio-electronics, Laser and Medical Engineering at Bauman MSTU. His research interests: optical and optoelectronic devices and systems

Abstract:
Potential capabilities of the multispectral optical reflectometry method with use of an optical locator for optical monitoring of forests have been analysed. Mathematical modelling and application of spectral libraries of vegetation reflectance allow us to substantiate selection of information parameters and the number of sensing wavelengths in order to solve different forest monitoring problems. Examples of application of the multispectral optical methods for the temperate zone are presented. It is demonstrated that in most cases it allows to identify forest areas with predominant dry or green deciduous or conifer trees, bogs or pastures in summer with possibility of correct identification Pd → 1 and possibility of false alarms Pa < 0.1.
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