Assessment of a canopy height model (CHM) in a vineyard using UAV-based multispectral imaging

Abstract

ABSTRACTBiomass is one of the most important parameters in order for the farmer to choose the best canopy management within the field and it can be estimated using plant canopy height. In combination with a non-vegetation ground model, plant height can be obtained by quantifying the height of a canopy using crop surface models (CSMs). A modified Mikrokopter Okto unmanned aerial vehicle (UAV) acquired high-resolution multispectral images (4 cm) and a processing chain was developed to construct a 3D digital surface model (DSM) for the creation of precise digital terrain models (DTMs) based on Structure from Motion (SfM) computer vision algorithms. The DTM was then subtracted from the DSM to obtain a canopy height model (CHM) of a vineyard. The results show a good separation of ground pixels from vine rows, but their elevations were not quite in accordance with the actual height of the vines due to a smoothing effect of the reconstructed CHM. A further comparison between CHM and a vigour map obtained from normalized difference vegetation index (NDVI) values showed a good correlation. A preliminary assessment of biomass volume was made using the average canopy height and vine row width for three different homogeneous classes. This is a preliminary study on how a 3D model developed by UAV images can be useful for a simple and prompt biomass evaluation.