Application of UAS Technology for the Development of Precision Agriculture

Sergiu-Bogdan  POP; Tudor  SĂLĂGEAN; Elemer Emanuel  ȘUBA; Nicolae  POP; Teodor  RUSU

Sergiu-Bogdan POP Faculty of Agriculture, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Mănăștur St. No. 3-5., Cluj-Napoca, Cluj, 400372
Tudor SĂLĂGEAN Faculty of Forestry and Cadastre, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Mănăștur St. No. 3-5., Cluj-Napoca, Cluj, 400372
Elemer Emanuel ȘUBA Faculty of Forestry and Cadastre, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Mănăștur St. No. 3-5., Cluj-Napoca, Cluj, 400372
Nicolae POP Faculty of Forestry and Cadastre, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Mănăștur St. No. 3-5., Cluj-Napoca, Cluj, 400372
Teodor RUSU Faculty of Agriculture, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Mănăștur St. No. 3-5., Cluj-Napoca, Cluj, 400372

Keywords: precision agriculture, vegetation indices, orthophoto map, UAS

Abstract

Precision agriculture often uses digital techniques such as satellites, UAS (unmanned aerial systems) and sensors to optimize agricultural production processes while reducing negative environmental impacts. Smart agriculture is data-driven, so a UAS can accurately receive and fairly distribute this information, allowing producers to take action based on individual soil circumstances. The paper aims to highlight the main advantages of UAS used in agriculture, depending on the type of wing (single-rotor, multi-rotor, fixed-wing and VTOL) and the sensors used. Also, within the work, the stages of making the digital orthophoto map at the Hoia farm, belonging to USAMV Cluj-Napoca, were analysed, with a view to further analyses on the state of the vegetation, using a DJI Phantom 4 Pro UAS model. Vegetation status can be assessed and quantified by different vegetation indices from images acquired in the visible, red and near-infrared spectral bands. Depending on their formulation, they can show a strong correlation with land cover and leaf and green area index (LAI and GAI), crop nitrogen uptake (QN), chlorophyll content, water stress detection, plant structure, photosynthesis, yield and growing conditions. Modern agricultural technology plays a vital role in increasing productivity to meet the demand for food for a growing global population, conservation and management of agricultural resources.