Abstract
Agriculture is one of the promising areas for the introduction of remote sensing technologies. With its help, you can timely receive a wide range of dynamic information about the conditions for the crops growth and development and make the necessary adjustments to obtain the planned result. The paper presents the results of early forecasting of spring wheat yields based on Dove (PlanetScope) satellite data from Planet Labs and DJI P4 Multispectral unmanned data. The maps of the yield of spring wheat were constructed using satellite and unmanned data with a spatial resolution of 3 m and 5 cm, respectively. A statistical assessment of the inhomogeneity of the spectral optical characteristics of agricultural crops has been carried out. The degree of correlation dependence between the value of the integral of the index (NDVI, VARI, MSAVI2, ClGreen) and the yield in different periods of the growing season has been determined.
Highlights
The widespread introduction of energy-saving technologies for the cultivation of agricultural crops is aimed at reducing material and technical costs in the crop production
The purpose of this study is to develop a precision farming method for early forecasting of grain yield based on remote sensing data and geobotanical studies
Wheat yield was measured in 4 replicates for each type of treatments (64 plots in total)
Summary
The widespread introduction of energy-saving technologies for the cultivation of agricultural crops is aimed at reducing material and technical costs in the crop production. To determine the relationship between the integrals of the index values and the yield of wheat, the coefficient of determination (r2) between these variables was calculated.
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