This paper explores the question of classification of a series of space images for analysis of the processes of growing crops, using the spectral channels of minimum dimension. This study attempts to give a partial answer to the question: how to detect the problems in growing processes much faster and with a high level of accuracy? In this paper, we report on the results of the survey conducted to determine the existing methods and tools for spectral analysis of multispectral space images for solving forecasting and search problems of mapping the agricultural objects. The present work extends the use of the general image classification process by the computational procedure of ranking spectral channels according to the value of spectral information. The structure of the classification rule based on the informativity indicator of the spectral channel has been developed. The proposed prototype of a geospatial recognition system will provide a digital stratification landscape plan.

Darya V. Vakulenko
Post-Graduate Student of Volgograd State Technical University
28 Lenin Ave., Volgograd, 400005, Russia
e-mail: dsvklnk@gmail.com

Alla G. Kravets
Doctor of Technical Science, Professor of CAD department
of Volgograd State Technical University
28 Lenin Ave., Volgograd, 400005, Russia
e-mail: agk@gde.ru

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