Classification of crops by multispectral satellite images of sentinel 2 based on the analysis of vegetation signatures
Khamdamov Rustam KhamdamovichTashkent University of Information Technologies, 17A, Buz-2, Tashkent 100125, UzbekistanErgash SalievTashkent University of Information Technologies, 17A, Buz-2, Tashkent 100125, UzbekistanХошим РахмановTashkent University of Information Technologies, 17A, Buz-2, Tashkent 100125, Uzbekistan
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Abstract This article describes crop recognition methods from multispectral satellite imagery of Sentinel 2. The feature space includes taking into account parameters such as brightness and color of optical images over the entire channel of Sentinel 2 spectrozonal satellite imagery. The signs of multispectral images for various terrain classes in satellite images are analyzed. A comparative analysis of the classification results by the methods of “Expectation Maximization” and “k -means” has been compiled.
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Koʻrsatkichlar — AkademScholar · Tez orada