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Comparison of methods for structural analysis of two-dimensional spectral remote sensing data of forests damaged by the Siberian silkmoth
A.V. Lapko1,2, V.A. Lapko1,2

1Reshetnev Siberian State University of Science and Technology, Prospekt Krasnoyarsky Rabochy 31, Krasnoyarsk, 660037, Russia;
2Institute of Computational Modelling SB RAS, Akademgorodok Str. 50, Bldg. 44, Krasnoyarsk, 660036, Russia

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DOI: 10.18287/COJ1800

Article ID: 1800

Language: Russian

Abstract:
An approach to structural analysis of remote sensing data is presented, based on the partitioning of the domain of values of two-dimensional spectral features using components of the correlation coefficient. Structural data analysis is based on the analysis of the signs of the correlation coefficient components, which correspond to the normalized values of the spectral features of remote sensing data. On this basis, four classes are defined, to which the values of the components of the correlation coefficient correspond: positive, alternating and negative. To analyze remote sensing data, a decision rule is formed that allows classifying control situations into one of four classes. Depending on the studied pairs of spectral features, each class characterizes a unique signature corresponding to a certain type of earth's surface. To conduct additional studies of the obtained classes, a spectral data decomposition technique is proposed. The method is based on the transformation of the components of the correlation coefficient in the form of a product or their Euclidean distance. For the visual presentation of the obtained results, a kernel probability density estimate is used. A method for its optimization is presented. The effectiveness of the proposed decomposition methods is compared with the analysis of remote sensing data based on the use of normalized difference infrared index values. This index transforms information from spectral channels of near and short-wave infrared. A comparison of the results of applying the considered structural analysis methods was carried out on a test plot of a forest area damaged by the Siberian silkmoth, located in the Krasnoyarsk Territory. Maps and numerical characteristics of the obtained results are provided.

Keywords:
structural data analysis, automatic classification, components of the correlation coefficient, kernel probability density estimation, remote sensing data, spectral features, forest massif, NDII index, Siberian silkmoth.

Citation:
Lapko AV, Lapko VA. Comparison of methods for structural analysis of two-dimensional spectral remote sensing data of forests damaged by the Siberian silkmoth. Computer Optics 2026; 50(4): 1800. doi:10.18287/COJ1800.

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