|Title||Detecting Rumex Obtusifolius weed plants in grasslands from UAV RGB imagery using deep learning|
|Author(s)||Valente, J.; Doldersum, M.; Roers, C.; Kooistra, L.|
|Source||In: ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands. - ISPRS (ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ) - p. 179 - 185.|
|Event||4th ISPRS Geospatial Week 2019, Enschede, 2019-06-10/2019-06-14|
Laboratory of Geo-information Science and Remote Sensing
|Publication type||Contribution in proceedings|
|Keyword(s)||Aerial surveying - Deep learning - DJI Phantom - Grasslands - Machine vision - Plant detection - Rumex - Weeding|
Broad-leaved dock (Rumex obtusifolius) is a fast growing and spreading weed and is one of the most common weeds in production grasslands in the Netherlands. The heavy occurrence, fast growth and negative environmental-agricultural impact makes Rumex a species important to control. Current control is done directly in the field by mechanical or chemical actuation methods as soon as the plants are found in situ by the farmer. In nature conservation areas control is much more difficult because spraying is not allowed. This reduces the amount of grass and its quality. Rumex could be rapidly detected using high-resolution RGB images obtained from a UAV and optimize the plant control practices in wide nature conservation areas. In this paper, a novel approach for Rumex detection from orthomosaics obtained using a commercial available quadrotor (DJI Phantom 3 PRO) is proposed. The results obtained shown that Rumex can be detected up to 90% from a 6 mm/pixel ortho-mosaic generated from an aerial survey and using deep learning.