Development of a mathematical model for assessing the state of plant biomass using the integration of multispectral sensors of optical and radio ranges

Abstract

The use of various modern technologies is increasingly being used in agriculture, which has formed such a direction as precision farming. At the same time, the goal of this direction is to increase productivity while optimizing the use of pesticides and fertilizers while minimizing costs. The main analyzed indicator is the state of the biomass, for the assessment of which, mainly, the indications of the optical range are used, on the basis of which various vegetation indices are calculated. These readings are collected, as a rule, using UAVs. However, the introduction of Internet of Things (IoT) technologies also makes it possible to obtain a number of soil indicators that are significant for the state of biomass. At the same time, the integration of various sources of information is not performed. The use of information integration makes it possible to refine the readings of the optical range and cut off a number of necessary analyzes to normalize the state of the biomass. The authors have proposed a mathematical model based on the fuzzy clustering algorithm for identifying the state of biomass, which makes it possible to integrate optical and radio data. The experiment showed that the proposed model allows not only to assess whether a biomass site belongs to a certain state, but also to track transient processes by calculating the degree of correspondence to clusters.