Methodical approaches to plant identification in high-resolution images in multispectral monitoring using UAVS

Abstract

Crop management used in these technologies is one of the main trends in the modernization of agricultural technologies. To implement crop management, growers need accessible and effective information about the state of crops. The aim of the work is to develop a method of plant identification on multispectral images of high resolution for crops of continuous sowing on the example of winter wheat. The research was conducted on 03/17/2019 on winter wheat crops in the tillering vegetation phase, Mukan variety in production fields near the village of Horodyshche, Kyiv region. Aerial monitoring from a height of 100 meters was carried out using a spectral complex Slantrange 3p, mounted on a UAV UAV DJI Matrice 600. To extract the reference graphics data from Slantview made a copy of the screen in full screen mode of the image window. Statistical processing of graphical data of spectral monitoring results was performed in MathCad. It was found that the reliable establishment of the spectral portrait of the soil for its pixel-by-pixel filtering from multispectral images is a difficult task because its color significantly depends on the state of moisture, which may differ in open and shaded by plants. A more promising way to eliminate random inclusions is to use a spectral portrait of plants based on the intensity ratios of its spectral components. A promising parameter for assessing the condition of crops is to assess their area of heir horizontal surface, which can be determined by pixel analysis of the image. A filtering option is proposed, which, as in the solutions implemented in Slantview software, needs to be debugged. In further researches it is expedient to consider questions of methodical maintenance of an estimation of quality of a filtration of data of spectral monitoring of vegetation.