A Nonparametric Pattern Recognition Algorithm in the Problems of Analyzing the Data of Remote Sensing over Anthropogenic Territories
A. V. Lapkoa, b, *, V. A. Lapkoa, b, and A. V. Sharuevab
aInstitute of Computational Modelling, Siberian Branch, Russian Academy of Sciences, Krasnoyarsk, 660036 Russia
bReshetnev Siberian State University of Science and Technology, Krasnoyarsk, 660037 Russia
email: *lapko@icm.krasn.ru
Received 11 January, 2024
Abstract— Some results from the application of a new method of verifying the hypothesis about the independence of random variables in the analysis of remote sensing data for anthropogenic territories are reported. The method is based on a nonparametric pattern recognition algorithm corresponding to the maximum likelihood criterion. Linear and nonlinear dependences between the spectral features characterizing anthropogenic territories are determined. The results of recognizing the types of anthropogenic territories by the spectral data of remote sensing are considered.
Keywords:
verifying the hypothesis about the independence of random variables,
pattern recognition,
nonparametric probability density estimation,
anthropogenic territories,
remote sensing
DOI: 10.3103/S8756699025700116