The article describes a mathematical model which represents dynamics of the normalized difference vegetation index for winter wheat plantings in central black soil areas. As opposed to the approaches considered during our theoretical study, which, as a rule, are based on averaged data related to respectively vast territories (districts, regions, agricultural enterprises), this article describes a model which relates to rather small areas, namely to particular fields measuring 30-200 ha. The multiplicative model under consideration takes into account two opposite tendencies in the development of winter wheat: the process of phytomass increase and the process of plastic substances production. Parameters of the suggested model were estimated for winter wheat plantings in central black soil area on the fields with different levels of productivity for 2017 in accordance with normalized difference vegetation index data. We estimated the parameters by least square method. We performed model functional tests on the basis of the data received during remote sounding of the soil at more than one hundred of fields in Central Federal District. The test results are very promising. The suggested model allows for estimation of ripening period and the time of harvesting. The model can be applied for approximation of normalized difference vegetation index missing values, as well as for estimation of time required to attain maximum index value and, consequently, for forecasting of harvesting terms.
The proposed vegetation index NDVI dynamic model allows us to move from describing the plants’ development and growth phenomenological way to model ideas about the vegetation process as a whole. The biological research previously obtained experimental material is linked within a mathematical model framework with the vegetation indices values calculated from satellite images. This makes it possible to quantitatively evaluate the plant development characteristics and indicators in the crops observations framework carried out using spacecraft. This work main task is to explicate the mathematical model main provisions, which allows combining these two viewpoints obtained in different ways: experimentally and through visual analysis. This approach allows explaining how the processes occurring in plants are displayed in a data mathematical model obtained from space. In this paper, we consider an approach based solely on a dynamic model parameter for the current field season and an introduced new integral characteristic that depends on the vegetation index NDVI current values. This approach advantage to yield forecasting is that the forecast is made on the data basis coming from the spacecraft, i.e. is operational. At the same time, the forecast is based on a dynamic model that takes into account the agricultural plants physiological characteristics, in particular, winter wheat.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.