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Forecasting the winter wheat yield based on the vegetation index NDVI dynamic model
Author(s) -
Аleksey G. Bukhovets,
Evgeniy A. Semin,
M. Kucherenko,
Svetlana I. Iablonovskaia
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/848/1/012191
Subject(s) - normalized difference vegetation index , vegetation (pathology) , viewpoints , mathematical model , index (typography) , yield (engineering) , process (computing) , satellite , computer science , environmental science , mathematics , meteorology , leaf area index , statistics , geography , ecology , engineering , medicine , art , visual arts , materials science , pathology , world wide web , metallurgy , biology , aerospace engineering , operating system
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.

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