Unmanned drone multispectral imaging for assessment of wheat and oilseed rape habitus

Marina Stoyanova1, Alexander Kandilarov2, Vesselin Koutev3, Olga Nitcheva4 and Polya Dobreva4
1 ”Nikola Poushkarov” Institute of Soil Science, Agrotechnologies and Plant Protection, 1080 Sofia, Bulgaria
2 Neopterix Ltd, 4000 Plovdiv, Bulgaria
3 University of Forestry, 1797, Sofia, Bulgaria
4 Institute of Mechanics – BAS, 1113, Sofia, Bulgaria


Stoyanova, M., Kandilarov, A., Koutev, V., Nitcheva, O. & Dobreva, P. (2021). Unmanned drone multispectral imaging for assessment of wheat and oilseed rape habitus. Bulg. J. Agric. Sci., 27 (5), 875–879

The use of unmanned drones has been increased in precision farming. From multispectral images of terrain and crops to spraying and sowing, their application and development is becoming more and more popular in the public sector. Using different sensors and equipment farmers could take optimal management decisions.
The aim of the present study is to analyze the data from a multispectral camera, to survey the development of the crops on the field, to perform an agronomic assessment and to make recommendations for optimization of the production by soil and plant sampling in order to increase yields and reducing the cost of production.
Effectiveness of multispectral observation methods on agricultural crops was tested at the end of October 2018 in a pilot study on the territory of Northern Bulgaria. First year results are the part of a planned long-term study to identify problem areas of the terrain by spectral analysis and additional sampling. Five channel multispectral camera Parrot Sequoia was applied on a DJI Matrice 600 Hexocopter. Observed crops were wheat and oilseed rape. NDVI method permitted us to identify areas with good crop development and area with poor vegetation status. Digital elevation models (DEM) were built for both studied areas. Fields area was divided on parts with NDVI higher than 0.7 and with NDVI with lower than 0.7 for optimal fertilizers application.

Keywords: Remote sensing; multispectral survey; NDVI index; DEM; crop habitus; wheat and oilseed rape

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