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The paper deals with a new method of testing hypotheses for the distribution of multidimensional remote sensing spectral data. The proposed technique is based on the use of nonparametric algorithms for pattern recognition. Testing the hypothesis of the identity of two laws of distributions of multidimensional random variables is replaced by testing a hypothesis stating that the pattern recognition error equals 0.5. The application of this technique allows doing without the decomposition of thedoi:10.18287/2412-6179-2019-43-2-238-244 fatcat:gyp2jdra5bdaxglbwhi2w7hdli