Aerial images to monitor grapevine vegetative growth

Abstract

Images obtained by Remotely Piloted Aircraft (RPA) used to monitor the crop can help evaluate leaf mass, plant formation, and plant population. In this context, the objectives of this study were to analyze plant growth in a grapevine crop trained in the trellis system, detect failures and determine the plant covered area using images obtained by RPA. The flight was parameterized with frontal overlap of 75%, lateral overlap of 70%, Ground Sample Distance (GSD) of 60 m, and flight speed of 5 m.s-1, using a sensor in the visible range. Processed images showed a stand 3% smaller than projected, an area covered by vine branches occupying 60.8%, undergrowth and invasives represented 5.3%, and exposed soil 33.9%. Vines were identified in the vegetation indices as green points, invasive plants as yellow points, and exposed soil as red points. Image processing obtained with RPA allowed identification of plants in various stages of development, with predominance of vines in the formation process. It was possible to identify the plants and quantify the leaf mass using the MPRI vegetation index, as well as to differentiate exposed soil from plant material. It was also observed that the plot had an incomplete stand at the time the flight was performed.