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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 5, pp. 9-27

Methodology of data processing for individual trees monitoring based on UAV multispectral measurements

A.A. Lamaka 1 
1 A.N. Sevchenko Institute of Applied Physical Problems of Belarusian State University, Minsk, Belarus
Accepted: 25.08.2023
DOI: 10.21046/2070-7401-2023-20-5-9-27
To date, there is a large number of studies in the field of trees condition monitoring to identify their illness. However, only in a small part of such works researchers set the task of detecting the drying of individual trees at an early stage. This article describes an original approach to monitoring the state of trees based on UAV multispectral camera measurements and subsequent processing of recorded data with specialized new methods. The article describes a new method of geographic data binding using pixel distances between nearby images calculated with the OpenCV library as additional information. This method makes it possible to reduce the average radius of the tree crowns images geographical coordinates spread by 46 % compared with the direct overlay of frames on coordinates formed on the basis of data from global navigation satellite systems, and by 15 % compared with standard software. The paper also describes an approach to semantic image segmentation based on the use of a pre-trained Deep Forest neural network model and additional image analysis of specific vegetation indices using an original algorithm. As a result of this method, the accuracy of tree recognition (F-score) was increased from 75 to 92 %. Together, the described methods form a technique for multispectral images processing for monitoring coniferous plantations condition. This technique allows to analyze the spectral reflectance characteristics of individual trees on the basis of the results of multi-temporal areal measurements.
Keywords: UAV, images, geotagging, key points, semantic segmentation, neural networks, Deep Forest, vegetation indexes
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