Imaging from manned ultra-light and unmanned aerial vehicles for estimating properties of spring wheat

This study investigates an imaging system based on a Rikola hyperspectral (HSI) and Nikon D800E (CIR) cameras installed on a manned ultralight aircraft Bekas Ch-32 for applications involving precision agriculture. The efficiency of this technical solution is compared with that of using Canon PowerShot SX260HS camera images acquired from helicopter-type unmanned aerial vehicle (UAV) to accomplish similar tasks. The criteria for comparison were the suitability of acquired images for modelling chlorophyll concentration in spring wheat and for estimating the normalized difference red edge (NDRE) index, which is conventionally obtained using OptRx proximal sensors. Hyperspectral image values used as explanatory variables in ordinary least squares regression explain 68 and 61% of the variance in chlorophyll concentration and NDRE, respectively and outperform other images. The advantage of hyperspectral imagery became negligible when applying geographically weighted regression to improve global regression models. The use of ultralight aircraft as a sensor platform for precision agriculture aimed aerial photography projects is suggested as currently the most cost-effective solution in Lithuania.