Monitoring of Rice Agrophytocenoses on the Basis of Remote Sensing

Unmanned aerial vehicles (UAVs) using remote sensing have improved the assessment of the condition of agricultural crops over large areas and, accordingly, reduced the cost of monitoring rice crops. Our research included the study of the production process of rice crops and, on their basis, the development of reliable methods for monitoring the physiological state of agrophytocenoses. In the study of the production process of crops, a methodology for automated mapping and yield forecasting was developed. The connection of optical signs of agrophytocenoses of varieties (vegetation index NDVI) with morphophysiological signs of plants and productivity has been established, which makes it possible to monitor the state of crops. It has been established that the nitrogen status and indicators of plant photosynthesis have a close positive relationship with the value of the vegetation index. As result of the research, a linear regression equation was obtained that estimates the degree of relationship between yield and vegetation index, leaf area index (LAI), and aboveground biomass. The established relationships of dates provide an opportunity to have more reliable information on the physiological state and production process of rice crops, using remote sensing data and ground-based systems for this. The conducted studies make it possible to improve the method of monitoring the state of rice sowing and serve to improve the information system for the use of precision technologies in agricultural production.