Control of the State of Agrocenoses Based on Earth Remote Sensing Data

Abstract

The purpose of this work is to present new results of using Earth remote sensing data in the problem of managing agricultural technology in real time. The main reason for the low efficiency of modern precision farming technologies is the lack of an adequate theory of agricultural technology management. At the same time, when creating such a theory, one should take into account the fact that the object of management, which is agricultural technology, includes agrocenoses, in which, in addition to sowing a crop, weeds are also included. Failure to take this factor into account leads to a deterioration in management efficiency, a decrease in sowing productivity and an over expenditure of mineral fertilizers and herbicides. In the presented work, for the first time, a complete theory of managing the state of agrocenoses is presented. This theory makes it possible to obtain a given yield with the required reliability. Such management is formed on the basis of estimates of the parameters of the state of sowing crops and weeds, formed according to remote sensing data in real time. The presented theory is based on new mathematical models of parameters of the state of agricultural crops, the soil environment, and weeds, as well as models of the relationship of these parameters with remote sensing data. Mineral fertilizers, herbicides, and irrigation are control factors in agricultural technology. Naturally, the parameters of technological operations are the doses of applied mineral fertilizers and herbicides, as well as irrigation rates. These operations are carried out at the onset of certain phenological phases of sowing crops. Remote sensing data are entered precisely at such moments of time, and the parameters of the state of crops and weeds are estimated on their basis. The presented theory is based on classical control principles used in modern dynamic systems. According to the proposed theory, a specialized software package was developed, with the help of which the control system was tested on the example of spring wheat sowing.